Publications

Showing 157 results for Author: Changwoo Do

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  • Feb, 2026

    Journal

    Signatures of Thermoreversible Associations in X-ray and Neutron Scattering from Dilute POlyzwitterion Solutions

    In aqueous solutions of polyzwitterions (PZs), an interplay between dipole–dipole interactions and hydration of zwitterionic groups can lead to thermoreversible associations, which have been difficult to detect in experiments. Here, we investigated dilute aqueous solutions of poly(1-(3-sulphonatopropyl)-2-vinylpyridinium) (P2VPPS) using small-angle X-ray and neutron scatte…

  • Feb, 2026

    Journal

    ToPolyAgent: AI Agents for Coarse-Grained Bead-Spring Topological Polymer Simulations

    We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions. By integrating large language models (LLMs) with domain-specific computational tools, ToPolyAgent supports both interactive and autonomous simulation workflows across diverse polymer architectu…

  • Dec, 2025

    ORNL Report

    ESAC v1: Enhanced AI-Powered Chatbot for EQ-SANS Experiment Automation Improvements and Updates

    ESAC (EQ-SANS Assisting Chatbot) is an advanced AI-powered application designed to streamline the workflow of neutron scattering experiments at the Spallation Neutron Source (SNS). This report documents the significant advancements in ESAC v1, which include the integration of a combined In-Context Learning (ICL) + Retrieval-Augmented Generation (RAG) capability, a robust i…

  • Dec, 2025

    Journal

    Bayesian Gaussian Process Inference for Neutron Spin Echo Measurement

    Neutron spin echo (NSE) spectroscopy provides unique access to microscopic dynamics, but its application is often constrained by low neutron flux, long acquisition times, and significant noise. We present a Bayesian inference approach based on Gaussian process regression (GPR) to reconstruct high-quality spin echo signals from sparse and noisy data by exploiting correlatio…

  • Oct, 2025

    Journal

    Minimal implicit-solvent coarse-grained simulation of Pluronic block copolymers with ionic liquids

    Pluronic block copolymers, composed of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO) in a triblock structure (PEO–PPO–PEO), are well known for their amphiphilic character and ability to self‐assemble into micelles in aqueous solution. The addition of ionic liquids (ILs) can further modulate the core–shell structures of these copolymers, influencing their stabi…

  • Oct, 2025

    Journal

    Experimental evidence of non-equilibrium phase separation in supercritical fluids

    Supercritical fluids (SCFs), widely utilized in many industries, have long been regarded as homogeneous single-phase media. Recent simulation studies identified different phases (more gas-like or liquid-like) in SCFs at equilibrium, expanding the previous notion but still not addressing non-equilibrium properties of SCFs. Here we reveal the existence of long-lived liquid-l…

  • Oct, 2025

    Journal

    Bayesian inference of anisotropic 2D small-angle scattering from sparse measurement

    We present a Bayesian inference framework for reconstructing anisotropic two-dimensional small-angle scattering (2D SAS) patterns from sparse, noisy, or partially missing data. The method combines a symmetry-aware angular basis with radial Gaussian process priors to enable accurate, training-free interpolation and denoising. Computational benchmarks demonstrate reliable re…

  • Oct, 2025

    Journal

    Toward Thermally Stimuli-Responsive Polymeric Vesicles Fabricated by Block Copolymer Blends for Nanocarriers

    Polymeric vesicles, characterized by enhanced colloidal stability, excellent mechanical properties, controllable surface functionality, and adjustable membrane thickness, are extremely useful in nano- and bio-technology for potential applications as nanosized carriers for drugs and enzymes. However, a few preparative steps are necessary to achieve a unilamellar vesicle wit…

  • Oct, 2025

    Journal

    Machine Learning Inversion from Scattering for Mechanically Driven Polymers

    A machine learning inversion method is developed for analyzing scattering functions of mechanically driven polymers and extracting the corresponding feature parameters, which include energy parameters and conformation variables. The polymer is modeled as a chain of fixed-length bonds constrained by bending energy, and it is subject to external forces such as stretching and…

  • Sep, 2025

    Journal

    Deciphering the small-angle scattering of polydisperse hard spheres using deep learning

    We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard sphere system. We use a variational autoencoder-based neural network to learn the bidirectional mapping between the scattering function and the system parameters, including the volume fraction and polydispersity. Such that the trained model serves both as a generator that p…

  • Sep, 2025

    Journal

    Desmearing two-dimensional small-angle neutron scattering data by central moment expansions

    Resolution smearing is a critical challenge in the quantitative analysis of two-dimensional small-angle neutron scattering (SANS) data, particularly in studies of soft-matter flow and deformation using SANS. We present a central moment expansion technique to address smearing in anisotropic scattering spectra, offering a model-free desmearing methodology. By accounting for…

  • Aug, 2025

    Journal

    Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

    Solid polymer electrolytes (SPEs) hold great promise for the advancement of next-generation energy storage devices. However, the ion transport mechanism in SPEs remains poorly understood. In this study, we investigate blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (P(MTFSI)Li) of varying molar r…

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