An electrochemical series for materials

T Mueller, J Montoya, W Ye, X Lei, L Hung… - Proceedings of the …, 2024 - pnas.org
The electrochemical series is a useful tool in electrochemistry, but its effectiveness in
materials chemistry is limited by the fact that the standard electrochemical series is based on …

Navigation through High-dimensional Chemical Space: Discovery of Ba 5 Y 13 [SiO 4] 8 O 8.5 and Ba 3 Y 2 [Si 2 O 7] 2

N Hulai, M Zanella, C Robertson, D Ritchie… - Chemical …, 2024 - pubs.rsc.org
Two compounds were discovered in the well-studied BaO-Y2O3-SiO2 phase field. Two
different experimental routines were used for the exploration of this system due to the …

Leveraging Language Model Multitasking To Predict C–H Borylation Selectivity

R Kotlyarov, K Papachristos, GPF Wood… - Journal of Chemical …, 2024 - ACS Publications
C–H borylation is a high-value transformation in the synthesis of lead candidates for the
pharmaceutical industry because a wide array of downstream coupling reactions is …

Descriptor Design for Perovskite Material with Compatible Molecules via Language Model and First-Principles

Y Huang, L Zhang - Journal of Chemical Theory and Computation, 2024 - ACS Publications
Directly applying big language models for material and molecular design is not
straightforward, particularly for real-scenario cases, where experimental validation accuracy …

[HTML][HTML] https://2DMat. ChemDX. org: Experimental data platform for 2D materials from synthesis to physical properties

JH Yang, H Kang, HJ Kim, T Kim, H Ahn, TG Rhee… - Digital …, 2024 - pubs.rsc.org
We present a comprehensive data platform for 2D materials research, https://2DMat.
ChemDX. org, and a newly constructed 2D database collected through the platform. This …

[HTML][HTML] Ionic species representations for materials informatics

A Onwuli, KT Butler, A Walsh - APL Machine Learning, 2024 - pubs.aip.org
High-dimensional representations of the elements have become common within the field of
materials informatics to build useful, structure-agnostic models for the chemistry of materials …

CSPBench: a benchmark and critical evaluation of Crystal Structure Prediction

L Wei, SS Omee, R Dong, N Fu, Y Song… - arXiv preprint arXiv …, 2024 - arxiv.org
Crystal structure prediction (CSP) is now increasingly used in discovering novel materials
with applications in diverse industries. However, despite decades of developments and …

Generative Design of inorganic compounds using deep diffusion language models

R Dong, N Fu, EMD Siriwardane… - The Journal of Physical …, 2024 - ACS Publications
Due to the vast chemical space, discovering materials with a specific function is challenging.
Chemical formulas are obligated to conform to a set of exacting criteria, such as charge …

[HTML][HTML] Data-driven exploration and first-principles analysis of perovskite material

L Zhang, J Zhou, X Chen - Journal of Materials Informatics, 2024 - oaepublish.com
In this study, we employ data-driven and first-principles methods (machine learning, density-
functional theory and language model) to comprehensively explore crystal structures …