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The tungsten heavy alloy green parts are successfully manufactured by an innovative indirect 3D printing technology, powder extrusion printing.

{"Material": ["tungsten heavy alloy"], "Descriptor": ["green parts"], "Synthesis": ["powder extrusion printing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Then the subsequent debinding-sintering process of the printed green parts is optimized to obtain a high-density and suitable-contiguity alloy.

{"Synthesis": ["debinding-sintering"], "Descriptor": ["green part"], "Operation": ["optimized"], "Result": ["high", "suitable"], "Property": ["density", "contiguity"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Finally, a 96W-2.7Ni-1.3Fe alloy with a high density of ~99.1%, suitable contiguity of ~ 0.63, strength of ~801 MPa and elongation of ~22.1% is prepared by a two-step sintering process under H2 atmosphere.

{"Material": ["96W-2.7Ni-1.3Fe"], "Descriptor": ["alloy", "two-step"], "Property": ["density", "contiguity", "strength", "elongation"], "Number": ["~99.1", "~ 0.63", "~801", "~22.1"], "Amount Unit": ["%", "MPa"], "Synthesis": ["sintering process"], "Environment": ["H2 atmosphere"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

After proper heat treatment, the strength and elongation of the as-sintered specimen are further improved to 838 MPa and 26.1%, respectively, which can be attributed to the reduction in the contiguity value of specimen, the enhancement of interfacial bonding force of W- γ interface, and the formation of the bridging mechanism of cracks.

{"Property": ["strength", "elongation", "contiguity", "bonding force"], "Descriptor": ["as-sintered"], "Material": ["specimen"], "Result": ["improved", "reduction", "enhancement"], "Number": ["838", "26.1"], "Amount Unit": ["MPa", "%"], "Phase": ["W", "\u03b3"], "Mesostructure or Macrostructure": ["interface", "cracks"], "Phenomenon": ["formation", "bridging mechanism"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Rapid cooling rates and stochastic interactions between the heat source and feedstock in additive manufacturing (AM) result in strong anisotropy and process-induced defects deteriorating the tensile ductility and fatigue resistance of printed parts.

{"Environment": ["Rapid cooling rates", "heat source", "feedstock"], "Phenomenon": ["stochastic interactions"], "Synthesis": ["additive manufacturing", "AM"], "Result": ["strong", "deteriorating"], "Property": ["anisotropy", "tensile ductility", "fatigue resistance"], "Descriptor": ["process-induced"], "Mesostructure or Macrostructure": ["defects", "printed parts"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

We show that by deliberately introducing a high density of lack of fusion (LoF) defects, a processing regime that has been avoided so far, followed by hot isostatic pressing (HIP), we can print Ti-6Al-4V with reduced texture and combinations of strength (TS=1.0 ± 3E-2 GPa) and ductility (εfailure=20 ± 1%) surpassing that of wrought, cast, forged, annealed, solution-treated and aged counterparts.

{"Operation": ["introducing"], "Property": ["high density", "texture", "strength", "ductility"], "Descriptor": ["lack of fusion", "LoF"], "Mesostructure or Macrostructure": ["defects"], "Synthesis": ["hot isostatic pressing", "HIP"], "Material": ["Ti-6Al-4V"], "Result": ["reduced"], "Number": ["1.0 \u00b1 3E-2", "20 \u00b1 1"], "Amount Unit": ["GPa", "%"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Such improvement is achieved through the formation of low aspect ratio α-grains around LoF defects upon healing, surrounded by α-laths.

{"Result": ["improvement"], "Phenomenon": ["formation", "healing"], "Descriptor": ["low aspect ratio"], "Phase": ["\u03b1"], "Microstructure": ["grains", "laths"], "Environment": ["around", "surrounded by"], "Mesostructure or Macrostructure": ["LoF defects"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

This occurrence is attributed to surface energy reduction and recrystallization events taking place during the healing of LoF defects via HIP post-processing.

{"Property": ["surface energy"], "Result": ["reduction"], "Phenomenon": ["recrystallization", "healing"], "Mesostructure or Macrostructure": ["LoF defects"], "Synthesis": ["HIP post-processing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

During additive manufacturing process of alloys, element segregation is vital in determines the solidification structure and mechanical properties of components.

{"Synthesis": ["additive manufacturing"], "Phenomenon": ["element segregation"], "Mesostructure or Macrostructure": ["solidification structure"], "Property": ["mechanical properties"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In this work, the solute trapping behavior and Nb segregation during laser additive manufacturing of a nickel-based superalloy are studied via a multi-scale model.

{"Phenomenon": ["solute trapping", "segregation"], "Participating Material": ["Nb"], "Synthesis": ["laser additive manufacturing"], "Material": ["nickel-based superalloy"], "Operation": ["multi-scale model"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The temperature evolution of the molten pool is estimated by the macro-scale mass and heat transfer simulation, and the solute dynamics during solidification and the distribution of Nb element during terminal solidification are predicted by the micro-scale phase-field simulation.

{"Property": ["temperature evolution", "distribution"], "Mesostructure or Macrostructure": ["molten pool"], "Descriptor": ["macro-scale", "mass", "heat", "micro-scale"], "Phenomenon": ["transfer", "solute dynamics", "solidification", "terminal solidification"], "Operation": ["simulation", "phase-field simulation"], "Participating Material": ["Nb"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The results show that Nb concentration is closely related to the molten pool site-specific solidification conditions.

{"Participating Material": ["Nb"], "Property": ["concentration"], "Mesostructure or Macrostructure": ["molten pool"], "Descriptor": ["site-specific"], "Environment": ["solidification conditions"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

From the bottom to the top of the molten pool, the average Nb concentration of the interdendritic region decreases gradually with the increase of the cooling rate.

{"Descriptor": ["From the bottom to the top", "average", "gradually"], "Mesostructure or Macrostructure": ["molten pool", "interdendritic region"], "Participating Material": ["Nb"], "Property": ["concentration"], "Result": ["decreases"], "Operation": ["increase of the cooling rate"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The droplet-like Nb distribution is found in the interdendritic region of the long-chain Laves phase.

{"Descriptor": ["droplet-like", "long-chain"], "Participating Material": ["Nb"], "Property": ["distribution"], "Mesostructure or Macrostructure": ["interdendritic region"], "Phase": ["Laves phase"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In situ monitoring is required to improve the understanding and increase the reliability of additive manufacturing methods such as laser powder bed fusion (LPBF).

{"Descriptor": ["n situ"], "Operation": ["monitoring"], "Result": ["improve the understanding", "increase the reliability"], "Synthesis": ["laser powder bed fusion", "LPBF"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Current diagnostic methods for LPBF capture optical images, X-ray radiographs, or measure the emission of thermal or acoustic signals from the component.

{"Descriptor": ["Current diagnostic methods"], "Mesostructure or Macrostructure": ["optical images"], "Characterization": ["X-ray radiographs", "emission of thermal", "acoustic signals"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Herein, a methodology based on the thermal emission of electrons - thermionic emission - from the metal surface during LPBF is proposed which can resolve laser-material interaction dynamics.

{"Operation": ["methodology"], "Phenomenon": ["thermal emission of electrons", "thermionic emission", "laser-material interaction"], "Mesostructure or Macrostructure": ["metal surface"], "Synthesis": ["LPBF"], "Property": ["dynamics"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The high sensitivity of thermionic emission to surface temperature and surface morphology is revealed to enable precise determination of the transition between conduction and keyhole mode melting regimes.

{"Result": ["high sensitivity", "transition"], "Phenomenon": ["thermionic emission", "conduction", "keyhole mode"], "Environment": ["surface temperature"], "Mesostructure or Macrostructure": ["surface morphology"], "Descriptor": ["melting regimes"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Increases in thermionic emission are correlated to laser scanning conditions that give rise to pore formation and regions where surface defects are pronounced.

{"Result": ["Increase", "pronounced"], "Phenomenon": ["thermionic emission"], "Operation": ["laser scanning conditions"], "Mesostructure or Macrostructure": ["pore formation", "surface defects"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Additive manufacturing (AM) has gained considerable academic and industrial interest due to its ability to produce parts with complex geometries with the potential for local microstructural control.

{"Synthesis": ["Additive manufacturing", "AM"], "Mesostructure or Macrostructure": ["complex geometries"], "Microstructure": ["local microstructural"], "Result": ["control"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

There is a fundamental gap in understanding how changes in process variables and alloy composition and thermodynamics affect additively manufactured parts.

{"Descriptor": ["fundamental gap in understanding"], "Operation": ["changes"], "Environment": ["process variables", "thermodynamics"], "Property": ["alloy composition"], "Result": ["affect"], "Synthesis": ["additively manufactured"], "Mesostructure or Macrostructure": ["parts"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The present systematic study sheds light on the effects of alloying composition and corresponding phase diagram features on the printability and solidification microstructures of four binary nickel-based alloys, namely, Ni-20 at% Cu, Ni-5 at% Al, Ni-5 at% Zr, and Ni-8.8 at% Zr.

{"Operation": ["effects"], "Property": ["alloying composition", "printability"], "Microstructure": ["solidification microstructures"], "Descriptor": ["binary", "nickel-based", "alloys"], "Material": ["Ni-20 at% Cu", "Ni-5 at% Al", "Ni-5 at% Zr", "Ni-8.8 at% Zr"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

These compositions are selected to represent binary isomorphous, weak solute partitioning, strong solute partitioning, and eutectic alloying conditions, respectively.

{"Property": ["compositions"], "Descriptor": ["binary", "weak", "strong"], "Mesostructure or Macrostructure": ["isomorphous"], "Phenomenon": ["solute partitioning"], "Phase": ["eutectic"], "Environment": ["alloying conditions"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Single track and bulk experiments are conducted to quantify the effects of varying material thermodynamic properties such as solidification temperature ranges, alloy melting temperatures, and other solidification conditions on resultant microstructures across the laser powder bed fusion (L-PBF) parameter space.

{"Mesostructure or Macrostructure": ["Single track", "bulk"], "Operation": ["effects"], "Property": ["thermodynamic properties", "solidification temperature ranges", "alloy melting temperatures"], "Microstructure": ["microstructures"], "Synthesis": ["laser powder bed fusion", "L-PBF"], "Environment": ["parameter space"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A simple framework for developing processing maps detailing porosity formation and microsegregation across the laser power – scan speed parameter space is established and validated for each of these alloys to determine how material properties affect printability and microstructure in L-PBF.

{"Result": ["processing maps"], "Phenomenon": ["porosity formation", "microsegregation"], "Environment": ["laser power", "scan speed"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

To balance the relationship between weldability and properties, a series of Ni-based superalloys with varying amount of Cr-like elements were designed using a “cluster-plus-glue-atom” model, and fabricated by laser additive manufacturing (LAM).

{"Result": ["balance"], "Property": ["weldability", "properties", "varying amount"], "Material": ["Ni-based superalloys"], "Participating Material": ["Cr-like elements"], "Operation": ["designed", "\u201ccluster-plus-glue-atom\u201d model", "fabricated"], "Synthesis": ["laser additive manufacturing", "LAM"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The microstructure of the as-deposited superalloys consists of few topological close packet (TCP) phases distributed between γ-Ni dendrites with epitaxial growth characteristic.

{"Microstructure": ["microstructure", "dendrites"], "Descriptor": ["as-deposited", "epitaxial growth characteristic"], "Material": ["superalloys"], "Phase": ["topological close packet", "TCP", "\u03b3-Ni"], "Result": ["distributed between"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

With the increase of Cr-like elements amount, TCP phases change from granular Laves phase to long-striped Laves phase plus acicular σ phase, and exhibit a trend of first decreasing and then increasing in amount.

{"Operation": ["increase", "change from"], "Participating Material": ["Cr-like elements"], "Phase": ["TCP", "\u03c3"], "Mesostructure or Macrostructure": ["granular", "long-striped", "acicular"], "Descriptor": ["Laves phase"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Performance tests reveal that the NiCrlike-2 alloy (Ni54.8Fe20.3Cr17.3Mo1.50Al1.56 Nb3.47Ti1.22 at.%), which has the fewest amount of TCP phases, presents a novel combination of strength, ductility, high temperature oxidation-resistance, and good weldability.

{"Characterization": ["Performance tests"], "Material": ["NiCrlike-2 alloy"], "Property": ["Ni54.8Fe20.3Cr17.3Mo1.50Al1.56 Nb3.47Ti1.22 at.%", "strength", "ductility", "high temperature oxidation-resistance", "weldability"], "Descriptor": ["fewest amount", "good"], "Phase": ["TCP"], "Result": ["novel combination"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Laser powder bed fusion is a dominant metal 3D printing technology.

{"Synthesis": ["Laser powder bed fusion", "3D printing technology"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

However, porosity defects remain a challenge for fatigue-sensitive applications.

{"Mesostructure or Macrostructure": ["porosity defects"], "Result": ["challenge"], "Application": ["fatigue-sensitive applications"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Some porosity is associated with deep and narrow vapor depressions called keyholes, which occur under high-power, low–scan speed laser melting conditions.

{"Mesostructure or Macrostructure": ["porosity", "vapor depressions", "keyholes"], "Descriptor": ["deep", "narrow"], "Environment": ["high-power", "low\u2013scan speed"], "Operation": ["laser melting"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

High-speed x-ray imaging enables operando observation of the detailed formation process of pores in Ti-6Al-4V caused by a critical instability at the keyhole tip.

{"Descriptor": ["High-speed"], "Characterization": ["x-ray imaging"], "Result": ["operando observation"], "Phenomenon": ["formation"], "Mesostructure or Macrostructure": ["pores", "keyhole tip"], "Material": ["Ti-6Al-4V"], "Environment": ["critical instability"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

We found that the boundary of the keyhole porosity regime in power-velocity space is sharp and smooth, varying only slightly between the bare plate and powder bed.

{"Mesostructure or Macrostructure": ["boundary"], "Environment": ["keyhole porosity regime", "power-velocity space"], "Descriptor": ["sharp", "smooth"], "Result": ["varying only slightly"], "Participating Material": ["bare plat", "powder bed"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The critical keyhole instability generates acoustic waves in the melt pool that provide additional yet vital driving force for the pores near the keyhole tip to move away from the keyhole and become trapped as defects.

{"Phenomenon": ["keyhole instability"], "Mesostructure or Macrostructure": ["acoustic waves", "melt pool", "pores", "keyhole tip"], "Result": ["additional yet vital driving force", "move away", "become trapped"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

High-entropy alloys (HEAs) have attracted great attention due to their many unique properties and potential applications.

{"Material": ["High-entropy alloys", "HEAs"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The nature of interatomic interactions in this unique class of complex multicomponent alloys is not fully developed or understood.

{"Phenomenon": ["interatomic interactions"], "Material": ["complex multicomponent alloys"], "Result": ["not fully developed or understood"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

We report a theoretical modeling technique to enable in-depth analysis of their electronic structures and interatomic bonding, and predict HEA properties based on the use of the quantum mechanical metrics, the total bond order density (TBOD) and the partial bond order density (PBOD).

{"Operation": ["theoretical modeling", "predict"], "Microstructure": ["electronic structures"], "Property": ["interatomic bonding", "total bond order density", "TBOD", "partial bond order density", "PBOD"], "Descriptor": ["quantum mechanical metrics"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Application to 13 biocompatible multicomponent HEAs yields many new and insightful results, including the inadequacy of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with experiment data, modeling porosity to reduce Young’s modulus.

{"Operation": ["Application", "modeling"], "Number": ["13"], "Descriptor": ["biocompatible", "multicomponent", "large"], "Material": ["HEAs"], "Result": ["inadequacy of using", "quantification", "validation", "experiment data", "reduce"], "Property": ["valence electron count", "lattice distortion", "mechanical properties", "Young\u2019s modulus"], "Mesostructure or Macrostructure": ["porosity"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Cobalt in a 23wt.% Cobalt containing Ni-base superalloy was systematically substituted for by Ni in order to investigate the effects of stacking fault energy (SFE) on dynamic strain aging.

{"Participating Material": ["Cobalt", "Ni"], "Number": ["23"], "Amount Unit": ["wt.%"], "Material": ["Ni-base superalloy"], "Operation": ["substituted", "investigate"], "Property": ["stacking fault energy", "SFE"], "Phenomenon": ["dynamic strain aging"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The results showed that adding Co had little effect on the phase constituents, but the SFE of γ matrix decreased continuously with increasing Co content.

{"Operation": ["adding"], "Participating Material": ["Co"], "Result": ["little effect", "decreased"], "Phase": ["phase constituents", "\u03b3 matrix"], "Property": ["SFE"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Mechanical properties tests showed that all the alloys exhibited serrated flow during tensile deformation due to dynamic strain aging (DSA) within a temperature ranges of 200°C-500°C.

{"Characterization": ["Mechanical properties tests"], "Phenomenon": ["serrated flow", "tensile deformation", "dynamic strain aging", "DSA"], "Environment": ["temperature ranges"], "Number": ["200", "500"], "Amount Unit": ["\u00b0C"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The starting temperature for serration improved from 200°C to 300°C with increasing the Co content from 5wt% Co in Alloy1 to 23wt% Co in Alloy3.

{"Property": ["starting temperature", "Co content"], "Phenomenon": ["serration"], "Result": ["improved"], "Number": ["200", "300", "5", "23"], "Amount Unit": ["\u00b0C", "wt%"], "Operation": ["increasing"], "Participating Material": ["Co"], "Material": ["Alloy1", "Alloy3"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In the serrated flow regime, all the alloys clearly exhibited the normal and inverse DSA behaviors.

{"Phenomenon": ["serrated flow regime", "DSA"], "Descriptor": ["normal", "inverse"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The tensile properties such as yield stress, ultimate tensile strength and fracture feature in DSA regime were not influenced by temperature, strain rate and Co content.

{"Property": ["yield stress", "ultimate tensile strength", "fracture", "temperature", "strain rate", "content"], "Phenomenon": ["DSA regime"], "Result": ["not influenced"], "Participating Material": ["Co"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A relation between high density of SF and the inverse DSA effect was found in Alloy3 with low stacking fault energy.

{"Result": ["relation", "low"], "Property": ["high density", "SF", "stacking fault energy"], "Descriptor": ["inverse"], "Phenomenon": ["DSA"], "Material": ["Alloy3"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Analysis of the results suggested that the mechanism for the inverse DSA is related to the locking of the mobile dislocation by substitutional elements.

{"Descriptor": ["inverse"], "Phenomenon": ["DSA", "locking"], "Result": ["related"], "Microstructure": ["mobile dislocation"], "Participating Material": ["substitutional elements"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Additive manufacturing is increasingly considered for production of high quality, metallic, aerospace parts.

{"Synthesis": ["Additive manufacturing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Despite the high potential of this manufacturing process to reduce weight and lead time, the fundamental understanding of additive manufactured Ti–6Al–4V material is still at an early stage, especially in the area of fatigue and damage tolerance.

{"Material": ["Ti\u20136Al\u20134V"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

This paper covers the effects of inherent surface roughness on the fatigue life.

{"Descriptor": ["inherent"], "Property": ["surface roughness", "fatigue life"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In the as built condition, metallic parts have a poor surface texture, which is generally removed in fatigue critical areas.

{"Descriptor": ["as built condition", "metallic parts"], "Result": ["poor surface texture"], "Operation": ["removed"], "Mesostructure or Macrostructure": ["fatigue critical areas"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

It is shown that the fatigue properties of Ti–6Al–4V samples, produced by direct metal laser sintering and electron beam melting, are dominated by surface roughness effects.

{"Property": ["fatigue properties"], "Material": ["Ti\u20136Al\u20134V"], "Synthesis": ["direct metal laser sintering", "electron beam melting"], "Result": ["dominated"], "Phenomenon": ["surface roughness effects"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

X-ray tomography has emerged as a uniquely powerful and non-destructive tool to analyze defects in additive manufacturing.

{"Characterization": ["X-ray tomography"], "Descriptor": ["non-destructive"], "Result": ["analyze"], "Mesostructure or Macrostructure": ["defects"], "Synthesis": ["additive manufacturing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Defects include unintended porosity, rough surfaces and deviations from design, which can have different root causes and can vary significantly among samples.

{"Mesostructure or Macrostructure": ["Defects", "porosity"], "Descriptor": ["unintended"], "Property": ["rough surfaces"], "Result": ["deviations from design", "vary significantly"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Powder material properties, non-uniform delivery of the powder layer, deformation during manufacturing, deviations from optimal process-parameters caused by changes in the laser beam, the optical components and the scanning system operation, may result in lack of fusion pores, metallurgical pores, keyhole pores, etc.

{"Participating Material": ["Powder material"], "Property": ["properties"], "Result": ["non-uniform"], "Operation": ["delivery", "deviations", "changes"], "Mesostructure or Macrostructure": ["powder layer", "pores"], "Phenomenon": ["deformation"], "Synthesis": ["manufacturing"], "Descriptor": ["optimal", "lack of fusion", "metallurgical", "keyhole"], "Environment": ["process-parameters", "laser beam", "optical components", "scanning system"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

These different types of pores have different typical sizes, shapes and 3D distributions.

{"Mesostructure or Macrostructure": ["pores"], "Result": ["different"], "Property": ["sizes", "shapes", "3D distributions"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

All types of defects have effects on the mechanical properties of a final part.

{"Property": ["mechanical properties"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The use of X-ray tomography to visualize pores in parts (non-destructively) prior to mechanical testing has allowed us to improve our understanding of the effect of this porosity on the mechanical properties of the part (also referred to as “effect of defect”).

{"Characterization": ["X-ray tomography", "mechanical testing"], "Operation": ["visualize", "effect"], "Mesostructure or Macrostructure": ["pores", "porosity"], "Descriptor": ["non-destructively"], "Result": ["improve our understanding"], "Property": ["mechanical properties"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

This can provide the possibility to discriminate critical defects from harmless ones,and thereby build confidence in additive manufacturing processes.

{"Operation": ["discriminate"], "Descriptor": ["critical", "harmless"], "Mesostructure or Macrostructure": ["defects"], "Result": ["build confidence"], "Synthesis": ["additive manufacturing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

This paper reviews the current state of knowledge with regard to the “effect of defect” in metal additive manufacturing, and highlights some relevant examples from our recent work.

{"Synthesis": ["metal additive manufacturing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Internal flow behaviour during melt-pool-based metal manufacturing remains unclear and hinders progression to process optimisation.

{"Phenomenon": ["Internal flow behaviour"], "Synthesis": ["melt-pool-based metal manufacturing"], "Result": ["unclear", "hinders progression"], "Operation": ["process optimisation"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In this contribution, we present direct time-resolved imaging of melt pool flow dynamics from a high-energy synchrotron radiation experiment.

{"Descriptor": ["direct"], "Characterization": ["time-resolved imaging"], "Mesostructure or Macrostructure": ["melt pool"], "Property": ["flow dynamics"], "Environment": ["high-energy", "synchrotron radiation"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

We track internal flow streams during arc welding of steel and measure instantaneous flow velocities ranging from 0.1 m s−1 to 0.5 m s−1.

{"Descriptor": ["internal", "instantaneous"], "Mesostructure or Macrostructure": ["flow streams"], "Synthesis": ["arc welding"], "Material": ["steel"], "Property": ["flow velocities"], "Number": ["0.1 ", "0.5"], "Amount Unit": ["m s\u22121"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

When the temperature-dependent surface tension coefficient is negative, bulk turbulence is the main flow mechanism and the critical velocity for surface turbulence is below the limits identified in previous theoretical studies.

{"Descriptor": ["temperature-dependent", "flow mechanism", "identified in previous theoretical studies"], "Property": ["surface tension coefficient", "critical velocity"], "Result": ["negative", "below the limits"], "Phenomenon": ["bulk turbulence", "surface turbulence"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

When the alloy exhibits a positive temperature-dependent surface tension coefficient, surface turbulence occurs and derisory oxides can be entrapped within the subsequent solid as result of higher flow velocities.

{"Material": ["alloy"], "Result": ["positive", "higher"], "Descriptor": ["temperature-dependent", "derisory", "subsequent"], "Property": ["surface tension coefficient", "flow velocities"], "Phenomenon": ["surface turbulence", "entrapped"], "Participating Material": ["oxides", "solid"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The widely used arc welding and the emerging arc additive manufacturing routes can be optimised by controlling internal melt flow through adjusting surface active elements.

{"Synthesis": ["arc welding", "arc additive manufacturin"], "Result": ["optimised"], "Operation": ["controlling", "adjusting"], "Phenomenon": ["internal melt flow"], "Participating Material": ["surface active elements"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

To improve the efficiency of advanced power systems, integrated computational materials engineering (ICME) tools are being developed at QuesTek Innovations LLC for the design of high-performance alloys for gas turbine.

{"Synthesis": ["integrated computational materials engineering", "ICME"], "Material": ["high-performance alloys"], "Application": ["gas turbine"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In this article, we detail progress on the design of a low-Re, castable, creep-resistant, single-crystal Ni-based superalloy (QTSX).

{"Property": ["low-Re", "creep-resistant"], "Descriptor": ["castable", "Ni-based superalloy"], "Microstructure": ["single-crystal"], "Material": ["QTSX"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

CALPHAD-based indicators for castability (liquid buoyancy) and creep resistance (γ′ coarsening rate constant) were simultaneously employed to predict an optimum alloy composition.

{"Descriptor": ["CALPHAD-based", "indicators"], "Property": ["castability", "liquid buoyancy", "creep resistance", "coarsening rate constant", "composition"], "Phase": ["\u03b3\u2032"], "Operation": ["predict"], "Result": ["optimum alloy"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Component-level QTSX trail castings have been fabricated, and characterization of the castings has demonstrated freckle-free solidification and creep resistance comparable to CMSX4 and ReneN5, which validates this accelerated ICME approach.

{"Descriptor": ["Component-level", "trail castings", "freckle-free"], "Material": ["QTSX"], "Characterization": ["characterization"], "Phenomenon": ["solidification"], "Property": ["creep resistance"], "Result": ["comparable"], "Participating Material": ["CMSX4", "ReneN5"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Advanced in situ characterization is essential for determining the underlying dynamics of laser-material interactions central to both laser welding and the rapidly expanding field of additive manufacturing.

{"Characterization": ["Advanced in situ characterization"], "Property": ["dynamics"], "Phenomenon": ["laser-material interactions"], "Synthesis": ["laser welding", "additive manufacturing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Traditional characterization techniques leave a critical experimental gap in understanding the complex subsurface fluid flow and metal evaporation dynamics inherent in laser-induced heating of the metal.

{"Phenomenon": ["subsurface fluid flow", "metal evaporation"], "Property": ["dynamics"], "Descriptor": ["laser-induced"], "Operation": ["heating"], "Participating Material": ["metal"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Herein, in situ ultra-high-speed transmission X-ray imaging is revealed to be essential for bridging this information gap, particularly via comparison with and validation of advanced multiphysics simulations.

{"Descriptor": ["in situ", "ultra-high-speed", "transmission", "multiphysics"], "Characterization": ["X-ray imaging"], "Operation": ["comparison", "validation", "simulations"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Imaging on submicrosecond timescales enables correlation between dynamics of the laser-generated vapor–liquid interface and melt pool surface instabilities in industrially relevant alloys.

{"Characterization": ["Imaging"], "Environment": ["submicrosecond timescales"], "Result": ["correlation"], "Property": ["dynamics"], "Descriptor": ["laser-generated", "industrially relevant"], "Mesostructure or Macrostructure": ["vapor\u2013liquid interface", "melt pool surface"], "Phenomenon": ["instabilities"], "Material": ["alloys"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

X-ray imaging and complimentary simulations reveal vapor depression oscillations and rapid expansion due to reflection of the processing laser from the front surface of the vapor depression.

{"Characterization": ["X-ray imaging"], "Operation": ["simulations"], "Mesostructure or Macrostructure": ["vapor depression", "front surface"], "Property": ["oscillations"], "Phenomenon": ["rapid expansion", "reflection"], "Environment": ["processing laser"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Pore formation studies at steady state and during prompt removal of laser heating at the end of track reveal that the rapidly solidifying melt pool traps pores near the base of the vapor-filled depression.

{"Phenomenon": ["Pore formation", "rapidly solidifying", "traps"], "Environment": ["steady state", "laser heating"], "Operation": ["prompt removal"], "Mesostructure or Macrostructure": ["at the end of track", "melt poo", "pores", "near the base", "vapor-filled depression"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Moreover, pores within the melt pool are entrained by Marangoni convection which overcomes the force of buoyancy and forces the pores downward from the surface immediately before solidification.

{"Mesostructure or Macrostructure": ["pores", "melt pool"], "Result": ["entrained", "overcomes", "downward from the surface"], "Phenomenon": ["Marangoni convection", "buoyancy"], "Operation": ["forces"], "Environment": ["immediately before solidification"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Observed solidification kinetics, consistent with previous results, give insight into surface morphology and porosity in the processed material.

{"Phenomenon": ["solidification"], "Property": ["kinetics", "morphology"], "Result": ["insight"], "Mesostructure or Macrostructure": ["surface", "porosity"], "Material": ["processed material"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Powder-fed laser additive manufacturing (LAM) based on directed energy deposition (DED) technology is used to produce S316-L austenitic, and S410-L martensitic stainless steel structures by 3D-printing through a layer-upon-layer fashion.

{"Descriptor": ["Powder-fed", "stainless steel"], "Synthesis": ["laser additive manufacturing", "LAM", "directed energy deposition", "DED"], "Material": ["S316-L", "S410-L"], "Phase": ["austenitic", "martensitic"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The microstructural features and crystallographic textural components are studied via electron backscattering diffraction (EBSD) analysis, hardness indentation and tensile testing.

{"Microstructure": ["microstructural features"], "Property": ["crystallographic textural components"], "Characterization": ["electron backscattering diffraction", "EBSD", "hardness indentation", "tensile testing"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The results are compared with commercial rolled sheets of austenitic and martensitic stainless steels.

{"Result": ["results"], "Operation": ["compared"], "Descriptor": ["commercial", "rolled sheets"], "Phase": ["austenitic", "martensitic"], "Participating Material": ["stainless steels"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A well-developed <200> direction solidification texture (with a J-index of ∼11.5) is observed for the austenitic structure produced by the LAM process, compared to a J-index of ∼2.0 for the commercial austenitic rolled sheet.

{"Number": ["<200>", "\u223c11.5", "\u223c2.0"], "Amount Unit": ["direction"], "Property": ["solidification texture", "J-index"], "Mesostructure or Macrostructure": ["austenitic structure"], "Synthesis": ["LAM"], "Operation": ["compared"], "Descriptor": ["commercial"], "Participating Material": ["austenitic rolled sheet"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Such a texture in the LAM process is caused by equiaxed grain formation in the middle of each layer followed by columnar growth during layer-upon-layer deposition.

{"Property": ["texture"], "Synthesis": ["LAM"], "Phenomenon": ["equiaxed grain formation", "columnar growth"], "Mesostructure or Macrostructure": ["middle of each layer"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A quite strong preferred orientation (J-index of 17.5) is noticed for martensitic steel developed by LAM.

{"Property": ["orientation", "J-index"], "Number": ["17.5"], "Material": ["martensitic steel"], "Synthesis": ["LAM"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Large laths of martensite exhibit a dominant textural component of {011} <111> in the α-phase, which is mainly controlled by transformation during layer-by-layer deposition.

{"Mesostructure or Macrostructure": ["laths", "\u03b1-phase"], "Phase": ["martensite"], "Property": ["textural component"], "Number": ["{011} <111>"], "Phenomenon": ["transformation"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

On the other hand, the martensitic commercial sheet consists of equiaxed grains without any preferred orientation or completely random orientations.

{"Participating Material": ["martensitic commercial sheet"], "Mesostructure or Macrostructure": ["equiaxed grains"], "Result": ["without any preferred", "completely random"], "Property": ["orientation", "orientations"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In the case of the austenitic steel, mechanical properties such as tensile strength, hardness and ductility were severely deteriorated during the LAM deposition.

{"Material": ["austenitic steel"], "Property": ["tensile strength", "hardness", "ductility"], "Result": ["severely deteriorated"], "Synthesis": ["LAM deposition"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A ductility loss of about 50% is recorded compared to the commercially rolled sheets that is attributed to the cast/solidified structure.

{"Property": ["ductility"], "Result": ["loss"], "Number": ["50"], "Amount Unit": ["%"], "Operation": ["compared to"], "Participating Material": ["commercially rolled sheets"], "Mesostructure or Macrostructure": ["cast/solidified structure"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

However, LAM manufacturing of martensitic stainless steel structures leads to a considerably enhanced mechanical strength (more than double) at the expense of reduced ductility, because of martensitic phase transformations under higher cooling rates.

{"Synthesis": ["LAM"], "Material": ["martensitic stainless steel"], "Property": ["mechanical strength", "ductility"], "Result": ["more than double", "reduced"], "Phenomenon": ["martensitic phase transformations"], "Descriptor": ["higher"], "Environment": ["cooling rates"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In high entropy alloys (HEAs), the addition of large-size atoms results in lattice distortion and further leads to solid solution strengthening or precipitation strengthening.

{"Material": ["high entropy alloys", "HEAs"], "Operation": ["addition"], "Descriptor": ["large-size"], "Participating Material": ["atoms"], "Phenomenon": ["lattice distortion", "solid solution strengthening", "precipitation strengthening"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

However, the relationship between atomic radius, solid solution strengthening and precipitation strengthening has not been discerned yet.

{"Property": ["atomic radius"], "Phenomenon": ["solid solution strengthening", "precipitation strengthening"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

In this work, CoCrFeNiX0.4 (X = Al, Nb, Ta, with an equi-atomic radius) HEAs were prepared by powder plasma arc additive manufacturing (PPA-AM) and evaluated for their mechanical properties.

{"Material": ["CoCrFeNiX0.4"], "Participating Material": ["Al", "Nb", "Ta"], "Descriptor": ["equi-atomic"], "Property": ["radius"], "Synthesis": ["powder plasma arc additive manufacturing", "PPA-AM"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Compression and nano-indentation hardness tests showed that the HEA with Ta showed the best properties.

{"Descriptor": ["Compression", "nano-indentation"], "Characterization": ["hardness tests"], "Material": ["HEA"], "Participating Material": ["Ta"], "Result": ["best properties"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The influence of atomic radius and solid solubility on solid solution strengthening was investigated and the main strengthening mechanism that determines the mechanical properties of the developed HEAs was analyzed.

{"Result": ["influence"], "Property": ["atomic radius", "solid solubility", "mechanical properties"], "Phenomenon": ["solid solution strengthening", "strengthening mechanism"], "Operation": ["investigated", "analyzed"], "Material": ["HEAs"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The results showed that (i) the CoCrFeNiAl0.4 alloy did not show any solid solution strengthening effect and that a clear relation between solid solution strengthening and atomic size was not observed; (ii) in both CoCrFeNiTa0.4 and CoCrFeNiNb0.4 HEAs, precipitation strengthening and grain boundary strengthening effects are observed, wherein the difference in mechanical properties between both the alloys can be mainly attributed to the formation of fine eutectic structure in CoCrFeNiTa0.4; and (iii) from the microstructural analyses, it was identified that, in the CoCrFeNiTa0.4 HEA, the location containing a fine eutectic structure is accompanied by the formation of low-angle grain boundaries (LAGBs), which is also the region where deformed grains gather, giving rise to improved mechanical strengthening.

{"Material": ["CoCrFeNiAl0.4", "CoCrFeNiTa0.4", "CoCrFeNiNb0.4"], "Result": ["did not show", "clear relation", "not observed", "difference", "accompanied by", "improved"], "Phenomenon": ["solid solution strengthening", "precipitation strengthening", "grain boundary strengthening", "gather"], "Property": ["atomic size", "mechanical properties", "mechanical strengthening"], "Microstructure": ["fine eutectic structure", "low-angle grain boundaries", "LAGBs"], "Mesostructure or Macrostructure": ["deformed grains"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

Here, we propose a material design strategy to simultaneously optimize multiple targeted properties of multi-component Co-base superalloys via machine learning.

{"Operation": ["design strategy", "machine learning"], "Result": ["optimize"], "Descriptor": ["targeted", "multi-component"], "Property": ["properties"], "Material": ["Co-base superalloys"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The microstructural stability, γ′ solvus temperature, γ′ volume fraction, density, processing window, freezing range, and oxidation resistance were simultaneously optimized.

{"Property": ["microstructural stability", "solvus temperature", "volume fraction", "density", "freezing range", "oxidation resistance"], "Phase": ["\u03b3\u2032"], "Environment": ["processing window"], "Descriptor": ["simultaneously"], "Result": ["optimized"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

A series of novel Co-base superalloys were successfully selected and experimentally synthesized from >210,000 candidates.

{"Descriptor": ["novel", "experimentally"], "Material": ["Co-base superalloys"], "Result": ["selected"], "Synthesis": ["synthesized"], "Number": [">210,000"], "Participating Material": ["candidates"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The best performer, Co-36Ni-12Al-2Ti-4Ta-1W-2Cr, possesses the highest γ′ solvus temperature of 1266.5 °C without the precipitation of any deleterious phases, a γ′ volume fraction of 74.5% after aging for 1000 h at 1000 °C, a density of 8.68 g cm−3 and good high-temperature oxidation resistance at 1000 °C due to the formation of a protective alumina layer.

{"Descriptor": ["best performer", "deleterious", "protective"], "Material": ["Co-36Ni-12Al-2Ti-4Ta-1W-2Cr"], "Result": ["highest", "without", "good"], "Phase": ["\u03b3\u2032", "phases"], "Property": ["solvus temperature", "volume fraction", "density", "oxidation resistance"], "Number": ["1266.5 ", "74.5", "1000", "8.68 "], "Amount Unit": ["\u00b0C", "%", "h", "g cm\u22123"], "Phenomenon": ["precipitation", "formation"], "Synthesis": ["aging"], "Environment": ["high-temperature"], "Participating Material": ["alumina"], "Mesostructure or Macrostructure": ["layer"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.

The laser–matter interaction and solidification phenomena associated with laser additive manufacturing (LAM) remain unclear, slowing its process development and optimisation.

{"Phenomenon": ["laser\u2013matter interaction", "solidification"], "Synthesis": ["laser additive manufacturing", "LAM"], "Result": ["unclear"]}

You will be provided with a string, and your task is to extract keywords from it. The type of each keyword must be one of Material, Participating Material, Synthesis, Characterization, Environment, Phenomenon, Mesostructure or Macrostructure, Microstructure, Phase, Property, Descriptor, Operation, Result, Application, Number, or Amount Unit.