Joshua Schrier

2 months ago | onlinelibrary.wiley.com | SeongMin Kim |Joshua Schrier |Yousung Jung

Supporting Information As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.

May 16, 2024 | dialnet.unirioja.es | Joshua Schrier

Comment on “Comparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases”[1]Fordham University, United StatesLocalización: Journal of chemical education, ISSN 0021-9584, Vol. 101, Nº 5, 2024, págs. 1782-1784Idioma: inglésEnlacesTexto completoResumenIn a recent paper in this Journal ( J. Chem. Educ. 2023, 100, 3934−3944), Clark et al. evaluated the performance of the GPT-3.5 large language model (LLM) on ten undergraduate pH calculation problems.

Apr 29, 2024 | pubs.acs.org | SeongMin Kim |Yousung Jung |Joshua Schrier |Geun Ho

Synthesizing novel compositions of matter is a prerequisite for scientific and practical breakthroughs. (1) Discovery would be accelerated if one could predict whether a hypothetical compound could be made and what precursors should be used to make it. Human experts have developed physical theories and heuristic rules for these tasks, (2−6) but increasingly machine learning (ML) is used to predict synthesizability (7−11) and select precursors.