6 papers
Improving Combined Detection and Classification of TEM Defects via Mask-Conditioned Latent Diffusion Augmentation
Ni Li, Nuohao Liu, Ryan Jacobs +5
Analyzing microstructural defects in transmission electron microscopy (TEM) images, particularly in irradiated metal alloys, is often limited by the availability of high-quality, l…
Regression with Large Language Models for Materials and Molecular Property Prediction
Ryan Jacobs, Maciej P. Polak, Lane E. Schultz +3
We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviation from the conventional LLM use case.…
Kolmogorov-Arnold Networks Applied to Materials Property Prediction
Ryan Jacobs, Lane E. Schultz, Dane Morgan
Kolmogorov-Arnold Networks (KANs) were proposed as an alternative to traditional neural network architectures based on multilayer perceptrons (MLP-NNs). The potential advantages of…
Effects of Yttrium Doping on Oxygen Conductivity in Ba(Fe, Co, Zr, Y)O_{3-δ} Cathode Materials for Proton Ceramic Fuel Cells
Chiyoung Kim, Ryan Jacobs, Jack H. Duffy +3
Proton ceramic fuel cells (PCFCs) achieve high efficiency at reduced operating temperatures, but their performance is often limited by slow oxygen reduction reaction (ORR) kinetics…
A General Approach for Determining Applicability Domain of Machine Learning Models
Lane E. Schultz, Yiqi Wang, Ryan Jacobs +1
Knowledge of the domain of applicability of a machine learning model is essential to ensuring accurate and reliable model predictions. In this work, we develop a new and general ap…
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…