Alexander Dunn

Lawrence Berkeley National Laboratory — United States

Materials Science · Physical Sciences

14h-index3.0kcitations23works276.02yr avg
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Research Topics

Machine Learning in Materials Science(12), Topic Modeling(5), Diamond and Carbon-based Materials Research(4), Fusion materials and technologies(4), Computational Drug Discovery Methods(3)

Publications23 total

Accelerated data-driven materials science with the Materials Project
Nature Materials·2025· 85 citedOpen Access
Structured information extraction from scientific text with large language models
Nature Communications·2024· 467 citedOpen Access
Author response for "Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs"
2023
EP069 A new kid on the block: Erector spinae plane block (ESPB) ‘tea-trolley’ teaching
2023Open Access
Author response for "Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs"
2023
Extracting Structured Seed-Mediated Gold Nanorod Growth Procedures from Literature with GPT-3
arXiv (Cornell University)·2023· 2 citedOpen Access
Extracting structured seed-mediated gold nanorod growth procedures from scientific text with LLMs
Digital Discovery·2023· 22 citedOpen Access
Structured information extraction from complex scientific text with fine-tuned large language models
arXiv (Cornell University)·2022· 65 citedOpen Access
Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions
Chemistry of Materials·2022· 64 citedOpen Access
Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science
Patterns·2022· 140 citedOpen Access
The Impact of Domain-Specific Pre-Training on Named Entity Recognition Tasks in Materials Science
SSRN Electronic Journal·2021· 29 citedOpen Access
Experimental validation of high thermoelectric performance in RECuZnP<sub>2</sub> predicted by high-throughput DFT calculations
Materials Horizons·2020· 63 citedOpen Access
Author Correction: Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm
npj Computational Materials·2020· 12 citedOpen Access
Gapped metals as thermoelectric materials revealed by high-throughput screening
Journal of Materials Chemistry A·2020· 33 citedOpen Access
Machine Learning Chemical Guidelines for Engineering Electronic Structures in Half-Heusler Thermoelectric Materials
Research·2020· 50 citedOpen Access
Unsupervised word embeddings capture latent knowledge from materials science literature
Nature·2019· 1.0k citedOpen Access
Rocketsled: a software library for optimizing high-throughput computational searches
Journal of Physics Materials·2019· 20 citedOpen Access
Matminer: An open source toolkit for materials data mining
Computational Materials Science·2018· 928 citedOpen Access
A molecular dynamics study of diamond and graphite under tritium bombardment
Journal of Applied Physics·2011· 10 cited
A molecular dynamics study of diamond as a plasma facing material for fusion
UCL Discovery (University College London)·2011· 1 cited
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Frequent Co-authors

Anubhav Jain(17), Kristin A. Persson(11), Gerbrand Ceder(11), John Dagdelen(9), Nicholas Walker(8), Kevin Cruse(6), Samuel Gleason(4), A. Paul Alivisatos(4), Sang‐Hoon Lee(3), Andrew Rosen(3), Amalie Trewartha(3), Haoyan Huo(3), Alex M. Ganose(3), Sanghoon Lee(3), Dorothy M. Duffy(3), Qi Wang(2), Maxwell Dylla(2), Mark Asta(2), G. Jeffrey Snyder(2), Sang-Hoon Lee(2)