Poisson-Nernst-Planck Models of Nonequilibrium Ion Electrodiffusion through a Protegrin Transmembrane Pore. - Dan S. Bolintineanu; Abdallah Sayyed-Ahmad; H. Ted Davis; Yiannis N. Kaznessis (PLoS Comput. Biol., 2009)

LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. - Aidan P. Thompson; Hasan Metin Aktulga; Richard Berger; Dan S. Bolintineanu; W. Michael Brown; Paul S. Crozier; Pieter J. in 't Veld; Axel Kohlmeyer; Stan G. Moore; Trung Dac Nguyen; Ray Shan; Mark J. Stevens; et al. (Comput. Phys. Commun., 2022)

ThermoPore: Predicting Part Porosity Based on Thermal Images Using Deep Learning. - Peter Myung-Won Pak; Francis Ogoke; Andrew Polonsky; Anthony Garland; Dan S. Bolintineanu; Dan R. Moser; Michael J. Heiden; Amir Barati Farimani (CoRR, 2024)

Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring. - Francis Ogoke; Sumesh Kalambettu Suresh; Jesse Adamczyk; Dan S. Bolintineanu; Anthony Garland; Michael J. Heiden; Amir Barati Farimani (CoRR, 2024)

Unsupervised Multimodal Fusion of In-process Sensor Data for Advanced Manufacturing Process Monitoring. - Matthew McKinney; Anthony Garland; Dale Cillessen; Jesse Adamczyk; Dan S. Bolintineanu; Michael J. Heiden; Elliott Fowler; Brad L. Boyce (CoRR, 2024)

Uncertainty quantification of neural network models of evolving processes via Langevin sampling. - Cosmin Safta; Reese E. Jones; Ravi G. Patel; Raelynn Wonnacott; Dan S. Bolintineanu; Craig M. Hamel; Sharlotte L. B. Kramer (CoRR, 2025)