About SMAD

SMAD (Superconducting Materials Automated Discovery) is a platform for running, tracking, and visualising the full computational pipeline behind superconducting materials research — live at smad.live.

What smad.live does

SMAD ties together structure generation, first-principles calculation, molecular dynamics, statistical sampling, and result visualisation into one workspace, so a screening campaign for superconducting materials can go from an idea to a plotted result without leaving the browser. The platform is organised around four core modules:

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DFT

Configure and launch electronic-structure calculations (SCF, band structure, DOS/PDOS, phonons, XANES/EELS/ARPES and related spectroscopies) on the connected HPC cluster.

∿

MD Simulations

Run and monitor molecular dynamics trajectories — energy/temperature/pressure tracking, radial distribution functions, mean-squared displacement, and velocity autocorrelation.

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Monte Carlo

Sample model Hamiltonians and thermodynamic ensembles for phase behaviour and statistical properties that complement the DFT and MD results.

📈

Analysis

A unified plotting suite across every module: band structures, DOS/PDOS, phonon dispersion, RDF/MSD/VACF, parity and learning curves for ML force fields, XRD, charge density, and more — each with drag-and-drop file upload and export.

Compute infrastructure

Behind the browser interface, SMAD jobs land on a purpose-built high-performance computing cluster — a multi-node rack that runs DFT, molecular dynamics, Monte Carlo sampling, and force-field training without leaving the platform workflow.

SMAD high-performance computing cluster: multi-shelf rack of compute nodes, network switch, and power supplies — The SMAD HPC cluster — networked compute nodes, switch fabric, and shared power, built to host the live calculations behind smad.live.

Modules are pluggable — institutions can swap in their own codes, schedulers, or surrogate models behind the same interface.

Team

Jay Rwaka

Creator, SMAD

Jay Rwaka created SMAD to bring structure generation, DFT, molecular dynamics, Monte Carlo sampling, and analysis into a single workspace for superconducting materials research — cutting down the time between a candidate structure and a plotted, citable result.

Replace this bio with fuller background, affiliation, and links (email, GitHub, Google Scholar) once available.

Terms of use

SMAD is intended for research and educational purposes. Access may be restricted to members of a specific institution, collaboration, or project.

Data responsibility: Users are responsible for verifying and interpreting results.
Compliance: All usage must comply with institutional HPC policies and software licenses.
Security: Do not store sensitive personal data; SSH access should use keys and strong practices.
Attribution: Publications must acknowledge SMAD and relevant funding sources.

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How to cite SMAD

If you use SMAD in a publication, please cite it so that others can trace the computational infrastructure behind your results. A suggested citation format is:

Text citation: "This work used the SMAD (Superconducting Materials Automated Discovery) platform for high‑throughput screening and analysis of superconducting materials."

BibTeX (example):

@misc{smad_platform,
  title        = {SMAD: A Platform for Automated Discovery of Superconducting Materials},
  author       = {Jay Rwaka and Collaborators},
  year         = {2026},
  howpublished = {\url{https://smad.live}},
  note         = {High-performance computing and AI-assisted materials discovery platform}
}

Update authors, year, and other fields once a formal software paper or institutional report is available.