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Meredig, Bryce
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1

A multiobjective closed-loop approach towards autonomous di..:

Kavalsky, Lance ; Hegde, Vinay I. ; Meredig, Bryce.
Digital Discovery.  3 (2024)  5 - p. 999-1010 , 2024
Link: https://doi.org/10.1039/..
 
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2

Quantifying the performance of machine learning models in m..:

Borg, Christopher K. H. ; Muckley, Eric S. ; Nyby, Clara...
Digital Discovery.  2 (2023)  2 - p. 327-338 , 2023
Link: https://doi.org/10.1039/..
 
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3

By how much can closed-loop frameworks accelerate computati..:

Kavalsky, Lance ; Hegde, Vinay I. ; Muckley, Eric...
Digital Discovery.  2 (2023)  4 - p. 1112-1125 , 2023
Link: https://doi.org/10.1039/..
 
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4

Artificial Intelligence in Materials Education: A Roundtabl..:

Tyler, Kaitlin ; Chen, Enze ; Meredig, Bryce.
JOM.  , 2023
Link: https://doi.org/10.1007/..
 
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5

Interpretable models for extrapolation in scientific machin..:

Muckley, Eric S. ; Saal, James E. ; Meredig, Bryce..
Digital Discovery.  2 (2023)  5 - p. 1425-1435 , 2023
Link: https://doi.org/10.1039/..
 
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6

AutoMat: Automated materials discovery for electrochemical ..:

Annevelink, Emil ; Kurchin, Rachel ; Muckley, Eric...
MRS Bulletin.  47 (2022)  10 - p. 1036-1044 , 2022
Link: https://doi.org/10.1557/..
 
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7

Utilization of machine learning to accelerate colloidal syn..:

Fong, Anthony Y. ; Pellouchoud, Lenson ; Davidson, Malcolm...
The Journal of Chemical Physics.  154 (2021)  22 - p. , 2021
Link: https://doi.org/10.1063/..
 
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8

High-throughput characterization of Lu-doped zirconia:

Huang, Ruiyun ; Antono, Erin ; Meredig, Bryce...
Solid State Ionics.  368 (2021)  - p. 115698 , 2021
Link: https://doi.org/10.1016/..
 
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9

Machine-learned metrics for predicting the likelihood of su..:

Kim, Yoolhee ; Kim, Edward ; Antono, Erin..
npj Computational Materials.  6 (2020)  1 - p. , 2020
Link: https://doi.org/10.1038/..
 
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10

Expanded dataset of mechanical properties and observed phas..:

Borg, Christopher K. H. ; Frey, Carolina ; Moh, Jasper...
Scientific Data.  7 (2020)  1 - p. , 2020
Link: https://doi.org/10.1038/..
 
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11

Single-Crystal Automated Refinement (SCAR): A Data-Driven M..:

Viswanathan, Gayatri ; Oliynyk, Anton O. ; Antono, Erin...
Inorganic Chemistry.  58 (2019)  14 - p. 9004-9015 , 2019
Link: https://doi.org/10.1021/..
 
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12

Five High-Impact Research Areas in Machine Learning for Mat..:

Meredig, Bryce
Chemistry of Materials.  31 (2019)  23 - p. 9579-9581 , 2019
Link: https://doi.org/10.1021/..
 
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13

Data‐driven glass/ceramic science research: Insights from t..:

De Guire, Eileen ; Bartolo, Laura ; Brindle, Ross...
Journal of the American Ceramic Society.  102 (2019)  11 - p. 6385-6406 , 2019
Link: https://doi.org/10.1111/..
 
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14

Strategies for accelerating the adoption of materials infor..:

Ward, Logan ; Aykol, Muratahan ; Blaiszik, Ben...
MRS Bulletin.  43 (2018)  9 - p. 683-689 , 2018
Link: https://doi.org/10.1557/..
 
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15

The 2019 materials by design roadmap:

Alberi, Kirstin ; Nardelli, Marco Buongiorno ; Zakutayev, Andriy...
Journal of Physics D: Applied Physics.  52 (2018)  1 - p. 013001 , 2018
Link: https://doi.org/10.1088/..
 
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