logo
Loading...
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions
Chemistrynpj Computational Materials

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

E. R. Antoniuk, G. Cheon, et al.

Explore the groundbreaking SynthNN, a deep learning model developed by Evan R. Antoniuk and colleagues, that revolutionizes the prediction of synthesizability in inorganic crystalline materials, outpacing traditional methods and experts alike in speed and accuracy.... show more
GeneralSummaryMetrics
Introduction
Literature Review
Methodology
Key Findings
Discussion
Conclusion
Limitations
Related Publications

Explore these studies to deepen your understanding

Adjacent work that informs or extends this paper's methodology and findings.

Predicting Synthesizability of Crystalline Materials via Deep Learning
Engineering and Technology

Predicting Synthesizability of Crystalline Materials via Deep Learning

A. Davariashtiyani, Z. Kadkhodaie, et al.

The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic
Interdisciplinary Studies

The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic

M. B. Marshall, S. Pinfield, et al.

Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data
Computer Science

Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data

C. H. Martin, T. (. Peng, et al.

Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data
Computer Science

Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data

M. Ho, P. Mantello, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 22+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny
    Predicting the synthesizability of crystalline | ResearchBunny