Zobrazeno 1 - 10
of 272
pro vyhledávání: '"Bartel, Christopher"'
The surface properties of solid-state materials often dictate their functionality, especially for applications where nanoscale effects become important. The relevant surface(s) and their properties are determined, in large part, by the materials synt
Externí odkaz:
http://arxiv.org/abs/2312.11708
Autor:
Zeng, Yan, Szymanski, Nathan J., He, Tanjin, Jun, KyuJung, Gallington, Leighanne C., Huo, Haoyan, Bartel, Christopher J., Ouyang, Bin, Ceder, Gerbrand
Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable ma
Externí odkaz:
http://arxiv.org/abs/2309.05800
Autor:
McDermott, Matthew J., McBride, Brennan C., Regier, Corlyn, Tran, Gia Thinh, Chen, Yu, Corrao, Adam A., Gallant, Max C., Kamm, Gabrielle E., Bartel, Christopher J., Chapman, Karena W., Khalifah, Peter G., Ceder, Gerbrand, Neilson, James R., Persson, Kristin A.
Synthesis is a major challenge in the discovery of new inorganic materials. Currently, there is limited theoretical guidance for identifying optimal solid-state synthesis procedures. We introduce two selectivity metrics, primary and secondary competi
Externí odkaz:
http://arxiv.org/abs/2308.11816
This study investigates the use of machine learning (ML) to correct the enthalpy of formation (Hf) from two separate DFT functionals, PBE and SCAN, to the experimental Hf across 1011 solid-state compounds. The ML model uses a set of 25 properties tha
Externí odkaz:
http://arxiv.org/abs/2307.07609
Publikováno v:
Nature Communications 14, 6956 (2023)
To aid in the automation of inorganic materials synthesis, we introduce an algorithm (ARROWS3) that guides the selection of precursors used in solid-state reactions. Given a target phase, ARROWS3 iteratively proposes experiments and learns from their
Externí odkaz:
http://arxiv.org/abs/2304.09353
Autor:
Deng, Bowen, Zhong, Peichen, Jun, KyuJung, Riebesell, Janosh, Han, Kevin, Bartel, Christopher J., Ceder, Gerbrand
The simulation of large-scale systems with complex electron interactions remains one of the greatest challenges for the atomistic modeling of materials. Although classical force fields often fail to describe the coupling between electronic states and
Externí odkaz:
http://arxiv.org/abs/2302.14231
Publikováno v:
Sci. Adv. 9, eadg8180 (2023)
Synthesis prediction is a key accelerator for the rapid design of advanced materials. However, determining synthesis variables such as the choice of precursor materials is challenging for inorganic materials because the sequence of reactions during h
Externí odkaz:
http://arxiv.org/abs/2302.02303
Autor:
Kothakonda, Manish, Kaplan, Aaron D., Isaacs, Eric B., Bartel, Christopher J., Furness, James W., Ning, Jinliang, Wolverton, Chris, Perdew, John P., Sun, Jianwei
A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The r$^2$SCAN revision of the strongly constrained and appropriately normed (
Externí odkaz:
http://arxiv.org/abs/2208.02841
Autor:
Huo, Haoyan, Bartel, Christopher J., He, Tanjin, Trewartha, Amalie, Dunn, Alexander, Ouyang, Bin, Jain, Anubhav, Ceder, Gerbrand
Publikováno v:
Chemistry of Materials, 2022
There currently exist no quantitative methods to determine the appropriate conditions for solid-state synthesis. This not only hinders the experimental realization of novel materials but also complicates the interpretation and understanding of solid-
Externí odkaz:
http://arxiv.org/abs/2204.08151