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drthyang/README.md

Tsung-Han Yang

Experimental & computational materials scientist building research tools for scattering, refinement, quantum materials, and agentic AI.

🌐 drthyang.github.io · 💼 LinkedIn · ✉️ thyang.careers@gmail.com

This GitHub is a working bench: part hobby space, part research toolbox, part learning archive. I use it to try new ideas, grow scientific tools, and build toward agentic AI workflows for scattering, refinement, and materials research.

I like building at the boundary between experiments and computation: neutron/X-ray scattering, DFT, phonons, reverse Monte Carlo, browser-based visualization, AI-assisted analysis, and small software systems that make research feel less fragile.

Featured Research Tools

The more polished pieces of the bench: zero-install scientific web apps whose analysis pipelines run client-side, so unpublished data never leaves your machine. Click a tool name to launch it in your browser.

Tool What it does Highlights
Materia Workbench · source Refines crystal and magnetic structures — single-crystal & powder, X-ray & neutron (CW and TOF) — entirely in the browser. AI-native by design: an MCP server exposes the same pure, tested core to LLM agents. Symmetry-constrained least squares, a magnetic space-group / k-vector workflow, validation against GSAS-II.
NEBULA3D · source Cleans 3D reciprocal-space neutron diffuse-scattering volumes and computes 3D-ΔPDF maps. Local Pyodide pipeline with float64 analysis and large-volume support; an LLM reasoning review grades each reduction.
RMC Monitor · source Monitors and interprets RMCProfile fits straight from a run folder. Live diagnostics, interactive charts, space-group detection, 3D atomic-density views, and an LLM-based AI assistant.
RMC-PH · source Extracts lattice dynamics from RMC ensembles fitted to experimental scattering data. Phonon bands, DOS, animated 3D modes, and simulated INS spectra with WebGPU acceleration.

Agentic AI for Materials

I am building toward agentic AI for scattering and materials discovery: systems that go beyond chat and can use domain tools, understand scientific files, run refinement workflows, inspect intermediate results, and help decide what to try next.

Materia is the concrete center of that effort — an AI-native foundation for materials science, built to be driven by LLM agents as well as by people. Its scientific core is pure, side-effect-free TypeScript, so the same engine that backs the UI is exposed to agents as tools. The first agent milestone has shipped: an MCP server that lets an agent parse, build, and refine a structure, then assess the result the way an expert would — parameter correlations, at-bound values, unexplained residuals — and suggest what to try next, rather than just reporting a scalar wR.

I am still learning and prototyping in this space, but it is a direction I care about: growing Materia into both a useful standalone workbench and a tool/skill layer for research agents working on scattering, structure refinement, and materials analysis.

What You Will Find Here

  • Research tools that grew out of real materials-science problems
  • Browser-native apps for data analysis, visualization, and modeling
  • Refinement packages and agent-ready toolsets for scattering and materials analysis
  • Experiments with Pyodide, WebGPU, Three.js, scientific user experience, and agentic AI workflows
  • Prototypes, notes, and learning projects from topics I am curious about

How I Tend To Build

  • Start from a real research pain point, not from a technology demo
  • Keep unpublished data local whenever possible
  • Make intermediate states visible, inspectable, and easier to debug
  • For AI-assisted workflows, make tool calls, assumptions, and uncertainty visible
  • Prefer a useful, honest prototype over a polished black box
  • Use modern web technology when it makes scientific workflows easier to share

If you are interested in quantum materials, scattering, scientific visualization, agentic AI, or research software, this is where I keep the things I am actively testing and building. If you are looking for someone who can move between domain science and implementation, the projects here are meant to show both the questions I care about and how I like to solve them.

Current Stack

Python · NumPy · SciPy · pandas · TypeScript/React · WebGPU/WGSL · Pyodide · MCP / agent tools · FastAPI/Flask · Three.js · pytest · GitHub Actions CI

For publications, research background, and CV, visit drthyang.github.io.

Popular repositories Loading

  1. rmc-phonon-dynamics rmc-phonon-dynamics Public

    Phonon calculations from RMC configurations ensemble.

    JavaScript

  2. rmc-toolkits rmc-toolkits Public

    Browser-based RMCProfile dashboard, with interactive plots, KDE, 3D structures, symmetry tools, and LLM-based AI Assistant support.

    JavaScript

  3. drthyang.github.io drthyang.github.io Public

    Personal website — experimental & computational materials scientist.

    JavaScript

  4. nebula3d nebula3d Public

    Data processing pipeline for diffuse scattering measurements.

    Python

  5. drthyang drthyang Public

  6. scattering-ai-sdk scattering-ai-sdk Public

    SDK for building agentic workflows, domain-specific skills, and analysis tools for scattering data.

    Python