Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Li, Kangming"'
Autor:
Zhang, Runze, Sur, Debashish, Li, Kangming, Witt, Julia, Black, Robert, Whittingham, Alexander, Scully, John R., Hattrick-Simpers, Jason
Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of a metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes the system
Externí odkaz:
http://arxiv.org/abs/2407.20297
Autor:
Li, Kangming, Rubungo, Andre Niyongabo, Lei, Xiangyun, Persaud, Daniel, Choudhary, Kamal, DeCost, Brian, Dieng, Adji Bousso, Hattrick-Simpers, Jason
Scientific machine learning (ML) endeavors to develop generalizable models with broad applicability. However, the assessment of generalizability is often based on heuristics. Here, we demonstrate in the materials science setting that heuristics based
Externí odkaz:
http://arxiv.org/abs/2406.06489
Publikováno v:
J. Mater. Chem. A, 2024,12, 12412-12422
High-entropy materials (HEMs) have recently emerged as a significant category of materials, offering highly tunable properties. However, the scarcity of HEM data in existing density functional theory (DFT) databases, primarily due to computational ex
Externí odkaz:
http://arxiv.org/abs/2403.15579
Autor:
Zhang, Jiahui, Jiang, Runbo, Li, Kangming, Chen, Pengyu, Shang, Xiao, Liu, Zhiying, Hattrick-Simpers, Jason, Simonds, Brian J., Wei, Qianglong, Wang, Hongze, Sun, Tao, Rollett, Anthony D., Zou, Yu
The keyhole phenomenon is widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final produc
Externí odkaz:
http://arxiv.org/abs/2402.16190
Autor:
Choudhary, Kamal, Wines, Daniel, Li, Kangming, Garrity, Kevin F., Gupta, Vishu, Romero, Aldo H., Krogel, Jaron T., Saritas, Kayahan, Fuhr, Addis, Ganesh, Panchapakesan, Kent, Paul R. C., Yan, Keqiang, Lin, Yuchao, Ji, Shuiwang, Blaiszik, Ben, Reiser, Patrick, Friederich, Pascal, Agrawal, Ankit, Tiwary, Pratyush, Beyerle, Eric, Minch, Peter, Rhone, Trevor David, Takeuchi, Ichiro, Wexler, Robert B., Mannodi-Kanakkithodi, Arun, Ertekin, Elif, Mishra, Avanish, Mathew, Nithin, Baird, Sterling G., Wood, Mitchell, Rohskopf, Andrew Dale, Hattrick-Simpers, Jason, Wang, Shih-Han, Achenie, Luke E. K., Xin, Hongliang, Williams, Maureen, Biacchi, Adam J., Tavazza, Francesca
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leade
Externí odkaz:
http://arxiv.org/abs/2306.11688
Autor:
Zhang, Runze, Black, Robert, Sur, Debashish, Karimi, Parisa, Li, Kangming, DeCost, Brian, Scully, John, Hattrick-Simpers, Jason
Electrochemical Impedance Spectroscopy (EIS) is a powerful tool for electrochemical analysis; however, its data can be challenging to interpret. Here, we introduce a new open-source tool named AutoEIS that assists EIS analysis by automatically propos
Externí odkaz:
http://arxiv.org/abs/2305.04841
Autor:
Li, Kangming, Persaud, Daniel, Choudhary, Kamal, DeCost, Brian, Greenwood, Michael, Hattrick-Simpers, Jason
Publikováno v:
Nature Communications 14, 7283 (2023)
Extensive efforts to gather materials data have largely overlooked potential data redundancy. In this study, we present evidence of a significant degree of redundancy across multiple large datasets for various material properties, by revealing that u
Externí odkaz:
http://arxiv.org/abs/2304.13076
Autor:
Li, Kangming
This thesis is a theoretical study of thermodynamic, point-defect formation and diffusion properties in Fe-Ni alloys with a focus on the magnetochemical effects. The results are derived from density functional theory (DFT) calculations and Monte Carl
Externí odkaz:
http://arxiv.org/abs/2302.00186
Publikováno v:
npj Comput Mater 9, 55 (2023)
Recent advances in machine learning (ML) methods have led to substantial improvement in materials property prediction against community benchmarks, but an excellent benchmark score may not imply good generalization of performance. Here we show that M
Externí odkaz:
http://arxiv.org/abs/2210.13597
Publikováno v:
Phys. Rev. B 106, 024106 (2022)
We investigate phase stability and vacancy formation in fcc Fe-Ni alloys over a broad composition-temperature range, via a density functional theory parametrized effective interaction model, which includes explicitly spin and chemical variables. On-l
Externí odkaz:
http://arxiv.org/abs/2203.04688