متابعة
Chandramouli Nyshadham
Chandramouli Nyshadham
Kebotix Inc.
بريد إلكتروني تم التحقق منه على kebotix.com
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Machine-learned multi-system surrogate models for materials prediction‏
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...‏
npj Computational Materials 5 (1), 51, 2019‏
1372019
A computational high-throughput search for new ternary superalloys‏
C Nyshadham, C Oses, JE Hansen, I Takeuchi, S Curtarolo, GLW Hart‏
Acta Materialia 122, 438-447, 2017‏
892017
Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications‏
A Hunter, BA Moore, M Mudunuru, V Chau, R Tchoua, C Nyshadham, ...‏
Computational Materials Science 157, 87-98, 2019‏
55*2019
The AFLOW fleet for materials discovery‏
C Toher, C Oses, D Hicks, E Gossett, F Rose, P Nath, D Usanmaz, ...‏
Handbook of Materials Modeling: Methods: Theory and Modeling, 1785-1812, 2020‏
352020
In Handbook of Materials Modeling: Methods: Theory and Modeling; Andreoni, W., Yip, S., Eds‏
C Toher, C Oses, D Hicks, E Gossett, F Rose, P Nath, D Usanmaz, ...‏
Springer International Publishing: Cham, 2018‏
72018
Systems and methods for template-free reaction predictions‏
D Sheberla, C Kreisbeck, K Ryan, C Nyshadham, XU Hengyu‏
US Patent App. 17/579,844, 2022‏
12022
Superalloys compositions including at least one ternary intermetallic compound and applications thereof‏
C Nyshadham, JE Hansen, GLW Hart‏
US Patent 11,214,851, 2022‏
12022
Insights on materials space‏
C Nyshadham, K Lincoln, G Hart‏
APS March Meeting Abstracts 2019, K18. 008, 2019‏
12019
DFT-45B---a fertile soil (data) for your seeds (machine learning algorithms)‏
C Nyshadham, C Kreisbeck, G Hart‏
Bulletin of the American Physical Society 65, 2020‏
2020
Predicting γ′-Phase Stability in Co-Based Superalloys‏
H Oliver, C Nyshadham, B Bekker, G Hart‏
Bulletin of the American Physical Society 65, 2020‏
2020
Accelerating superalloy discovery using moment tensor potentials‏
H Oliver, B Bekker, C Nyshadham, CA Leon Chinchay, G Hart‏
APS March Meeting Abstracts 2019, X19. 003, 2019‏
2019
Exploring Materials Space with Machine Learning‏
B Bekker, H Oliver, C Nyshadham, A Shapeev, G Hart‏
APS March Meeting Abstracts 2019, X19. 005, 2019‏
2019
Materials prediction using high-throughput and machine learning techniques‏
C Nyshadham‏
Brigham Young University, 2019‏
2019
Studying Cobalt Based Superalloys with Machine Learning‏
B Bekker, C Nyshadham, G Hart‏
Bulletin of the American Physical Society 63, 2018‏
2018
General machine learning models for materials prediction‏
C Nyshadham, M Rupp, B Bekker, A Shapeev, T Mueller, C Rosenbrock, ...‏
Bulletin of the American Physical Society 63, 2018‏
2018
Restricted Boltzmann Machines for Learning Multiple Observables‏
P Hamilton, C Nyshadham, G Hart‏
Bulletin of the American Physical Society 63, 2018‏
2018
Investigating superalloys using machine learning‏
H Oliver, C Nyshadham, G Hart‏
Bulletin of the American Physical Society 63, 2018‏
2018
The best features to know when you first meet a material‏
K Lincoln, C Nyshadham, G Hart‏
Bulletin of the American Physical Society 63, 2018‏
2018
3D Scattering Transform Representation of Materials: From Molecules to Crystals‏
A Nguyen, C Nyshadham, C Rosenbrock, G Hart‏
APS March Meeting Abstracts 2018, R12. 008, 2018‏
2018
Materials prediction using machine learning: comparing MBTR, MTP and deep learning‏
C Nyshadham, W Morgan, B Bekker, G Hart‏
APS March Meeting Abstracts 2018, E34. 011, 2018‏
2018
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مقالات 1–20