The sustainable materials roadmap M Titirici, SG Baird, TD Sparks, SM Yang, A Brandt-Talbot, O Hosseinaei, ... Journal of physics: Materials 5 (3), 032001, 2022 | 35 | 2022 |
High-dimensional Bayesian optimization of 23 hyperparameters over 100 iterations for an attention-based network to predict materials property: A case study on CrabNet using Ax … SG Baird, M Liu, TD Sparks Computational Materials Science 211, 111505, 2022 | 25* | 2022 |
What is a minimal working example for a self-driving laboratory? SG Baird, TD Sparks Matter 5 (12), 4170-4178, 2022 | 19 | 2022 |
Five degree-of-freedom property interpolation of arbitrary grain boundaries via Voronoi fundamental zone framework SG Baird, ER Homer, DT Fullwood, OK Johnson Computational Materials Science 200, 110756, 2021 | 18 | 2021 |
DiSCoVeR: a materials discovery screening tool for high performance, unique chemical compositions SG Baird, TQ Diep, TD Sparks Digital Discovery 1 (3), 226-240, 2022 | 17 | 2022 |
Compactness matters: Improving Bayesian optimization efficiency of materials formulations through invariant search spaces SG Baird, JR Hall, TD Sparks Computational Materials Science 224, 112134, 2023 | 12* | 2023 |
What is missing in autonomous discovery: Open challenges for the community PM Maffettone, P Friederich, SG Baird, B Blaiszik, KA Brown, SI Campbell, ... Digital Discovery 2 (6), 1644-1659, 2023 | 12 | 2023 |
Generative adversarial networks and diffusion models in material discovery M Alverson, SG Baird, R Murdock, J Johnson, TD Sparks Digital Discovery 3 (1), 62-80, 2024 | 9 | 2024 |
Data-driven materials discovery and synthesis using machine learning methods SG Baird, M Liu, HM Sayeed, TD Sparks Comprehensive Inorganic Chemistry III (Third Edition) 5, 3-23, 2023 | 9 | 2023 |
xtal2png: A Python package for representing crystal structure as PNG files SG Baird, KM Jablonka, MD Alverson, HM Sayeed, MF Khan, ... Journal of Open Source Software 7 (76), 4528, 2022 | 9 | 2022 |
Discovering chemically novel, high-temperature superconductors CC Seegmiller, SG Baird, HM Sayeed, TD Sparks Computational Materials Science 228, 112358, 2023 | 7 | 2023 |
Determining grain boundary position and geometry from EBSD data: Limits of accuracy DT Fullwood, S Sanderson, S Baird, J Christensen, ER Homer, ... Microscopy and Microanalysis 28 (1), 96-108, 2022 | 6 | 2022 |
Inference and uncertainty propagation of GB structure-property models: H diffusivity in [100] tilt GBs in Ni OK Johnson, ER Homer, DT Fullwood, DE Page, KF Varela, SG Baird Acta Materialia 215, 116967, 2021 | 6 | 2021 |
Grain boundary structure-property model inference using polycrystals: The underdetermined case BD Snow, SG Baird, C Kurniawan, DT Fullwood, ER Homer, OK Johnson Acta Materialia 209, 116769, 2021 | 5 | 2021 |
Grain boundary structure–property model inference using polycrystals: the overdetermined case C Kurniawan, S Baird, DT Fullwood, ER Homer, OK Johnson Journal of materials science 55 (4), 1562-1576, 2020 | 4 | 2020 |
Self-Driving Laboratories for Chemistry and Materials Science G Tom, SP Schmid, SG Baird, Y Cao, K Darvish, H Hao, S Lo, ... | 3 | 2024 |
Building a “Hello World” for self-driving labs: The Closed-loop Spectroscopy Lab Light-mixing demo SG Baird, TD Sparks STAR protocols 4 (2), 102329, 2023 | 3 | 2023 |
Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept S Lo, SG Baird, J Schrier, B Blaiszik, N Carson, I Foster, A Aguilar-Granda, ... Digital Discovery 3 (5), 842-868, 2024 | 2* | 2024 |
Materials science optimization benchmark dataset for multi-objective, multi-fidelity optimization of hard-sphere packing simulations SG Baird, R Issa, TD Sparks Data in Brief 50, 109487, 2023 | 2* | 2023 |
Structure feature vectors derived from Robocrystallographer text descriptions of crystal structures using word embeddings HM Sayeed, SG Baird, TD Sparks | 2 | 2023 |