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Xu, Xiangxiang; Lu, P.C.; German, Randall M.

doi:10.1023/a:1013110328307

Cited by 29 publications

(5 citation statements)

References 12 publications

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“…In solid state sintering, the particle size, distribution and morphology plays an importance role in determining the physical properties of sintered sample. The spherical shape powder giver the higher compressibility [15]. In this study, the results of bulk density and percentage of apparent porosity are influenced by the spherical shape of F-75 powder particles.…”

Section: Resultsmentioning

confidence: 73%

Characterization of Co-Cr-Mo (F-75) Alloy Produced by Solid State Sintering

Daud

Jamaludin

Bari

2010

AMR

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This research was carried out to fabricate and characterize Co-Cr-Mo (F-75) alloy. The samples have been prepared via solid state sintering. The lab work comprises the mixing of F-75 alloy powder with 2 wt. % of binder. The mixture was cold compacted using uniaxially press at 500 MPa. The samples were sintered at three different temperatures (1250 °C, 1300 °C and 1350 °C) in inert environment for 90 minutes of sintering time. The sintered samples were characterized by using Scanning Electron Microscope (SEM), Energy Dispersive X-ray Spectroscopy (EDS) and optical microscope (OM) Olympus BX41M. Bulk density, apparent porosity, percentage of linear shrinkage, and microhardness of the samples were also characterized. The average of the grain sizes were measured by line intercepts method. The optical micrographs showed the difference grain size in all sintered samples after etching with Marble reagent. The result shows the percentage of linear shrinkage, bulk density value and porosity increase with increasing the sintering temperature. Beside that, higher sintering temperature yields coarser grain structure.

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Section: Resultsmentioning

confidence: 73%

Characterization of Co-Cr-Mo (F-75) Alloy Produced by Solid State Sintering

Daud

Jamaludin

Bari

2010

AMR

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“…Common debinding techniques are classified into two groups: thermal debinding and solvent debinding. In the final stage, sintering produces a dense product via particle diffusion, which induce bonds between adjacent particles [12].…”

Section: Introductionmentioning

confidence: 99%

Fabrication of tungsten-based composites by solid binder mixing and sintering

Suh

Shin

2015

Powder Technology

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“…In Ref. [5], the in situ strength during sintering was determined by the competition among interparticle neck growth, densification, and thermal softening.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process-Based Model to Optimize Additively Manufactured Powder Microstructures From Phase Field Modeling

Batabyal

Sagar

Zhang

et al. 2021

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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A persistent problem in the selective laser sintering process is to maintain the quality of additively manufactured parts, which can be attributed to the various sources of uncertainty. In this work, a two-particle phase-field microstructure model has been analyzed. The sources of uncertainty as the two input parameters were surface diffusivity and inter-particle distance. The response quantity of interest (QOI) was selected as the size of the neck region that develops between the two particles. Two different cases with equal and unequal sized particles were studied. It was observed that the neck size increased with increasing surface diffusivity and decreased with increasing inter-particle distance irrespective of particle size. Sensitivity analysis found that the inter-particle distance has more influence on variation in neck size than that of surface diffusivity. The machine learning algorithm Gaussian Process Regression was used to create the surrogate model of the QOI. Bayesian Optimization method was used to find optimal values of the input parameters. For equal-sized particles, optimization using Probability of Improvement provided optimal values of surface diffusivity and inter-particle distance as 23.8268 and 40.0001, respectively. The Expected Improvement as an acquisition function gave optimal values 23.9874 and 40.7428, respectively. For unequal sized particles, optimal design values from Probability of Improvement were 23.9700 and 33.3005, respectively, while those from Expected Improvement were 23.9893 and 33.9627, respectively. The optimization results from the two different acquisition functions seemed to be in good agreement.

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Untitled

Cited by 29 publications

References 12 publications

Characterization of Co-Cr-Mo (F-75) Alloy Produced by Solid State Sintering

Characterization of Co-Cr-Mo (F-75) Alloy Produced by Solid State Sintering

Fabrication of tungsten-based composites by solid binder mixing and sintering

Gaussian Process-Based Model to Optimize Additively Manufactured Powder Microstructures From Phase Field Modeling

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