9 citations · 56 across the 21 of their papers we have counts for
12 papers · 1 filter
LLMs Can Assist with Proposal Selection at Large User Facilities
Lijie Ding, Janell Thomson, Jon Taylor +1
We explore how large language models (LLMs) can enhance the proposal selection process at large user facilities, offering a scalable, consistent, and cost-effective alternative to…
Optimal Binning for Small-Angle Neutron Scattering Data Using the Freedman-Diaconis Rule
Jessie E. An, Chi-Huan Tung, Changwoo Do +1
Small-Angle Neutron Scattering (SANS) data analysis often relies on fixed-width binning schemes that overlook variations in signal strength and structural complexity. We introduce…
ToPolyAgent: AI Agents for Coarse-Grained Topological Polymer Simulations
Lijie Ding, Jan-Michael Carrillo, Changwoo Do
We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions…
SasAgent: Multi-Agent AI System for Small-Angle Scattering Data Analysis
Lijie Ding, Changwoo Do
We introduce SasAgent, a multi-agent AI system powered by large language models (LLMs) that automates small-angle scattering (SAS) data analysis by leveraging tools from the SasVie…
Deciphering the Small-Angle Scattering of Polydisperse Hard Spheres using Deep Learning
Lijie Ding, Changwoo Do
We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard spheres system. We use a variational autoencoder-based neural network to learn…
Universal Convergence Metric for Time-Resolved Neutron Scattering
Chi-Huan Tung, Lijie Ding, Yuya Shinohara +4
This work introduces a model-independent, dimensionless metric for predicting optimal measurement duration in time-resolved Small-Angle Neutron Scattering (SANS) using early-time d…
Experimental evidence of non-equilibrium phase separation in supercritical fluids
Juho Lee, Yeonguk Kim, Jong Dae Jang +3
Supercritical fluids (SCFs) have long been considered homogeneous and structureless, yet recent studies suggest the existence of transient, liquid-like clusters under dynamic proce…
Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning
Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter +2
We present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compres…
Unlocking Hidden Information in Sparse Small-Angle Neutron Scattering Measurement
Chi-Huan Tung, Sidney Yip, Guan-Rong Huang +6
Small-angle neutron scattering (SANS) is a powerful technique for probing the nanoscale structure of materials. However, the fundamental limitations of neutron flux pose significan…
Machine Learning Inversion from Small-Angle Scattering for Charged Polymers
Lijie Ding, Chi-Huan Tung, Jan-Michael Y. Carrillo +2
We develop Monte Carlo simulations for uniformly charged polymers and machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, whic…
Scattering Insights into Shear-Induced Scission of Rod-like Micelles
Guan-Rong Huang, Ryan P. Murphy, Lionel Porcar +3
Hypothesis Understanding the scission of rod-like micelles under mechanical forces is crucial for optimizing their stability and behavior in industrial applications. This study inv…
Elongated particles in flow: Commentary on small angle scattering investigations
Guan-Rong Huang, Lionel Porcar, Ryan P. Murphy +7
This work thoroughly examines several analytical tools, each possessing a different level of mathematical intricacy, for the purpose of characterizing the orientation distribution…