GitHub organization
Agent skills by learningmatter-mit, page 2
Skills by learningmatter-mit, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 49 | Extract continuous X-Y data from experimental spectrum images (Raman, XRD, UV-Vis, IR, etc.) via hybrid VLM + CV pipeline and agent-in-the-loop workflow. | learningmatter-mit/ | 176 | — | ~2.8k | Automated safety check: Pass | MIT | today |
| 50 | Generate and iteratively refine PowerPoint presentations from simulation results using python-pptx. | learningmatter-mit/ | 176 | — | ~979 | Automated safety check: Pass | MIT | today |
| 51 | Avoid bot-blocking publisher websites by routing paper retrieval through legal open-access APIs and mirrors. | learningmatter-mit/ | 176 | — | ~1.6k | Automated safety check: Pass | MIT | today |
| 52 | Generate amorphorized structures from crystalline starting points using a melt-quench MD protocol. | learningmatter-mit/ | 176 | — | ~1.3k | Automated safety check: Pass | MIT | today |
| 53 | Calculate and plot multi-component temperature-composition phase diagrams from Thermodynamic Database (.tdb) files using CALPHAD methods. | learningmatter-mit/ | 176 | — | ~660 | Automated safety check: Pass | MIT | today |
| 54 | Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models. | learningmatter-mit/ | 176 | — | ~533 | Automated safety check: Pass | MIT | today |
| 55 | 55.Mat DB Mp Query Materials Project database for crystal structures, computed properties, elastic/magnetic data, and structurally similar materials using the MP API. | learningmatter-mit/ | 176 | — | ~3k | Automated safety check: Pass | MIT | today |
| 56 | Query the NIST Chemistry WebBook (which includes JANAF thermochemical tables) for standard experimental thermochemistry properties. | learningmatter-mit/ | 176 | — | ~518 | Automated safety check: Pass | MIT | today |
| 57 | Query the Crystallography Open Database (COD) and other OPTIMADE-compliant databases for experimental crystal structures. | learningmatter-mit/ | 176 | — | ~634 | Automated safety check: Pass | MIT | today |
| 58 | Calculate point-defect formation energies (vacancies, substitutions, interstitials) using MLIPs. | learningmatter-mit/ | 176 | — | ~1.7k | Automated safety check: Pass | MIT | today |
| 59 | Calculate charged defect formation energies and transition level diagrams using pymatgen-analysis-defects and atomate2 VASP workflows. | learningmatter-mit/ | 176 | — | ~1.6k | Automated safety check: Pass | MIT | today |
| 60 | Computes electron-phonon coupling to calculate temperature-dependent bandgap renormalization using atomate2. | learningmatter-mit/ | 176 | — | ~768 | Automated safety check: Pass | MIT | today |
| 61 | Compute electronic transport properties (mobility, conductivity, Seebeck coefficient) using DFT and AMSET via atomate2. | learningmatter-mit/ | 176 | — | ~865 | Automated safety check: Pass | MIT | today |
| 62 | Calculate the spontaneous ferroelectric polarization across a non-polar to polar structure transition using the Berry Phase method. | learningmatter-mit/ | 176 | — | ~738 | Automated safety check: Pass | MIT | today |
| 63 | Construct computational flows for VASP electronic structure projection via LOBSTER to calculate chemical bonding insights (COHP, atomic charges, DOS). | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 64 | Energy corrections needed when using certain MLIPs for phase diagram construction / formation energy calculations. | learningmatter-mit/ | 176 | — | ~1k | Automated safety check: Pass | MIT | today |
| 65 | 65.Mat Dft Vasp Prepare VASP input files, run DFT calculations (locally or remotely via atomate2), and parse VASP output results. | learningmatter-mit/ | 176 | — | ~1.1k | Automated safety check: Pass | MIT | today |
| 66 | Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP. | learningmatter-mit/ | 176 | — | ~1.5k | Automated safety check: Pass | MIT | today |
| 67 | Calculate ionic diffusion coefficients and activation energy from MD trajectories using pymatgen. | learningmatter-mit/ | 176 | — | ~1k | Automated safety check: Pass | MIT | today |
| 68 | 68.Mat Disorder Generate ordered structures from disordered starting points with partial occupancies. | learningmatter-mit/ | 176 | — | ~1k | Automated safety check: Pass | MIT | today |
| 69 | Compute defect-limited carrier mobility and electron-defect scattering matrix elements in 2D and 3D semiconductors from first principles with Quantum ESPRESSO and the EDI plugin. | learningmatter-mit/ | 176 | — | ~4.7k | Automated safety check: Pass | MIT | today |
| 70 | Calculate the full elastic tensor and mechanical properties (bulk modulus, shear modulus, Young's modulus, Poisson's ratio) using MLIPs. | learningmatter-mit/ | 176 | — | ~2.6k | Automated safety check: Pass | MIT | today |
| 71 | Calculate the intrinsic electrochemical stability window (ECW) of a material using standard phase diagram thermodynamic methods. | learningmatter-mit/ | 176 | — | ~1.4k | Automated safety check: Pass | MIT | today |
| 72 | Calculate electronic band structure and density of states using atomate2 and VASP. | learningmatter-mit/ | 176 | — | ~2.1k | Automated safety check: Pass | MIT | today |
| 73 | A library of ground-state element structures and their energies calculated from MLIPs. | learningmatter-mit/ | 176 | — | ~646 | Automated safety check: Pass | MIT | today |
| 74 | Compute phonon-limited carrier mobility and mode-resolved electron-phonon coupling in 2D materials from first principles with Quantum ESPRESSO and EPW. | learningmatter-mit/ | 176 | — | ~3.3k | Automated safety check: Pass | MIT | today |
| 75 | Calculate equation of state (bulk modulus, equilibrium volume) using MLIPs. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 76 | Calculate grain boundary energies for tilt/twist grain boundaries (Σ-CSL boundaries) using MLIPs; output γGB vs. | learningmatter-mit/ | 176 | — | ~2k | Automated safety check: Pass | MIT | today |
| 77 | Run Grand Canonical Monte Carlo (GCMC) simulations with cluster expansion models to map composition-temperature phase diagrams via chemical potential sweeps. | learningmatter-mit/ | 176 | — | ~1.8k | Automated safety check: Pass | MIT | today |
| 78 | Calculate the average intercalation voltage of cathode materials using MLIPs. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 79 | Discover new crystal structures by data-mined ionic substitution — propose candidates from existing structures (forward) or find potential structures for a target composition (reverse). | learningmatter-mit/ | 176 | — | ~1.4k | Automated safety check: Pass | MIT | today |
| 80 | Simulate long-time kinetics using rejection-free kinetic Monte Carlo (KMC) with event catalog construction, rate assignment via TST/Arrhenius, detailed-balance validation, superbasin handling, and… | learningmatter-mit/ | 176 | — | ~3.8k | Automated safety check: Pass | MIT | today |
| 81 | Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 82 | Calculate lattice thermal conductivity of materials with MLIPs. | learningmatter-mit/ | 176 | — | ~969 | Automated safety check: Pass | MIT | today |
| 83 | Calculate magnetic moments and spin density from spin-polarized DFT calculations using VASP. | learningmatter-mit/ | 176 | — | ~2.7k | Automated safety check: Pass | MIT | today |
| 84 | Calculate and visualize the probability density of diffusing ions from a Molecular Dynamics (MD) trajectory. | learningmatter-mit/ | 176 | — | ~928 | Automated safety check: Pass | MIT | today |
| 85 | Calculate the melting temperature of a material using the solid-liquid interface (coexistence) method. | learningmatter-mit/ | 176 | — | ~2.1k | Automated safety check: Pass | MIT | today |
| 86 | Retrieve and visualize pre-computed phase diagrams from Materials Project for thermodynamic stability analysis. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 87 | Simulate conservative phase-fields (spinodal decomposition and phase separation) using the Cahn-Hilliard equation. | learningmatter-mit/ | 176 | — | ~748 | Automated safety check: Pass | MIT | today |
| 88 | Simulate non-conservative phase-fields (grain growth and phase transformations) using the Allen-Cahn equation. | learningmatter-mit/ | 176 | — | ~812 | Automated safety check: Pass | MIT | today |
| 89 | 89.Mat Phonon Calculate vibrational properties (phonon dispersions, density of states, thermal properties) using MLIPs. | learningmatter-mit/ | 176 | — | ~851 | Automated safety check: Pass | MIT | today |
| 90 | Calculate Pourbaix (pH-voltage) diagrams for aqueous electrochemical stability using water-corrected MLIP energies and pymatgen. | learningmatter-mit/ | 176 | — | ~2.6k | Automated safety check: Pass | MIT | today |
| 91 | Calculate Quasi-Harmonic Approximation (QHA) thermal properties using MLIPs. | learningmatter-mit/ | 176 | — | ~952 | Automated safety check: Pass | MIT | today |
| 92 | Calculate Raman-active phonon mode frequencies and simulate Raman spectra from MLIP phonon calculations; optionally compute full Raman intensities with DFT Born charges via atomate2. | learningmatter-mit/ | 176 | — | ~2.3k | Automated safety check: Pass | MIT | today |
| 93 | Generate random crystal structures for a given composition (AIRSS-style) and relax with MLIPs to find low-energy candidates. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 94 | Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions. | learningmatter-mit/ | 176 | — | ~833 | Automated safety check: Pass | MIT | today |
| 95 | Sample off-equilibrium potential energy surface (PES), used for benchmarking and fine-tuning MLIPs. | learningmatter-mit/ | 176 | — | ~850 | Automated safety check: Pass | MIT | today |
| 96 | Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure. | learningmatter-mit/ | 176 | — | ~1.7k | Automated safety check: Pass | MIT | today |