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.
The more polished pieces of the bench: zero-install scientific web apps whose analysis pipelines run client-side, so unpublished data never leaves your machine.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), reciprocal-space & real-space PDF — entirely in the browser. | AI-native by design: 33 contract-tested MCP tools expose the same pure core to LLM agents. Symmetry-constrained least squares, magnetic space-group / k-vector workflows, symmetry-mode PDF fitting, mPDF validated against diffpy.mpdf, and Bayesian posterior sampling — 1111 tests in CI, validated 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. |
| RMCProfile Workbench · source | Monitors and interprets RMCProfile fits straight from a run folder. | Live diagnostics, interactive charts, space-group detection, 3D atomic-density views, PCA thermal ellipsoids reported in the crystallographic frame, solid-angle displacement-direction maps, 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 — bands and the S(Q,E)-derived DOS share one meV energy axis, so computed dispersion and measured spectrum read against each other. |
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 agent surface is now 33 contract-tested MCP tools spanning the powder, single-crystal, and PDF tracks: an agent can parse, build, and refine a structure, assess the result the way an expert would — parameter correlations, at-bound values, unexplained residuals — and sample the posterior for credible intervals, rather than just reporting a scalar wR.
Athanor is the exploratory end of the same question: a closed-loop agent that states a chemical hypothesis, proposes candidate compositions, screens them with physics-grounded surrogates — charge-balance filters, CHGNet relaxation, convex-hull stability, MEGNet band gaps — reflects in a lab notebook, and iterates, on local models by default. Every campaign is benchmarked against non-LLM baselines at equal compute, so "the agent helps" stays a claim with a control group. An early prototype, and reported as one.
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.
- 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
- 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.
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.
All projects here are personal work, developed and maintained in my personal capacity.