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Model Context Protocol · By learningmatter-mit

33 skills found.
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1
1.Chem Solution Md

Set up and run molecular dynamics simulations of molecules in explicit solvent boxes using Packmol for box construction and MLIPs for dynamics.

learningmatter-mit/AtomisticSkills176—~1.9kAutomated safety check: PassMITyesterday
2
2.Chem Sorption Relax

Prepares supercells for porous frameworks based on minimum interplanar distance and relaxes them using standard MLIP relaxation tools.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
3
3.Drug Ligand Prep

Prepare small-molecule ligands for docking and analysis via optional state enumeration, 3D conformer generation, MMFF/UFF minimization, and export to SDF + AutoDock PDBQT.

learningmatter-mit/AtomisticSkills176—~772Automated safety check: PassMITyesterday
4
4.Drug Protein Prep

Prepare macromolecular receptor structures (PDB/mmCIF or RCSB PDB ID) for docking or simulation by fixing common structure issues and adding hydrogens.

learningmatter-mit/AtomisticSkills176—~1.1kAutomated safety check: PassMITyesterday
5
5.General Atomisticskills Setup

Set up, check or troubleshoot how AtomisticSkills runs on this machine -- creating its Python environments, connecting its MCP servers, choosing uv or a container runtime, and configuring API keys.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: NotesMITyesterday
6
6.Mat Amorphization

Generate amorphorized structures from crystalline starting points using a melt-quench MD protocol.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITyesterday
7
7.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/AtomisticSkills176—~3kAutomated safety check: PassMITyesterday
8
8.Mat Defect Energy

Calculate point-defect formation energies (vacancies, substitutions, interstitials) using MLIPs.

learningmatter-mit/AtomisticSkills176—~1.7kAutomated safety check: PassMITyesterday
9
9.Mat Defect Energy Dft

Calculate charged defect formation energies and transition level diagrams using pymatgen-analysis-defects and atomate2 VASP workflows.

learningmatter-mit/AtomisticSkills176—~1.6kAutomated safety check: PassMITyesterday
10
10.Mat Dft Lobster

Construct computational flows for VASP electronic structure projection via LOBSTER to calculate chemical bonding insights (COHP, atomic charges, DOS).

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
11
11.Mat Dft Vasp

Prepare VASP input files, run DFT calculations (locally or remotely via atomate2), and parse VASP output results.

learningmatter-mit/AtomisticSkills176—~1.1kAutomated safety check: PassMITyesterday
12
12.Mat Dielectric Response

Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP.

learningmatter-mit/AtomisticSkills176—~1.5kAutomated safety check: PassMITyesterday
13
13.Mat Electronic Structure

Calculate electronic band structure and density of states using atomate2 and VASP.

learningmatter-mit/AtomisticSkills176—~2.1kAutomated safety check: PassMITyesterday
14
14.Mat Grain Boundary

Calculate grain boundary energies for tilt/twist grain boundaries (Σ-CSL boundaries) using MLIPs; output γGB vs.

learningmatter-mit/AtomisticSkills176—~2kAutomated safety check: PassMITyesterday
15
15.Mat Intercalation Voltage

Calculate the average intercalation voltage of cathode materials using MLIPs.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
16
16.Mat Kinetic Monte Carlo

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/AtomisticSkills176—~3.8kAutomated safety check: PassMITyesterday
17
17.Mat Magnetic Density

Calculate magnetic moments and spin density from spin-polarized DFT calculations using VASP.

learningmatter-mit/AtomisticSkills176—~2.7kAutomated safety check: PassMITyesterday
18
18.Mat Melting Point

Calculate the melting temperature of a material using the solid-liquid interface (coexistence) method.

learningmatter-mit/AtomisticSkills176—~2.1kAutomated safety check: PassMITyesterday
19
19.Mat Pourbaix Diagram

Calculate Pourbaix (pH-voltage) diagrams for aqueous electrochemical stability using water-corrected MLIP energies and pymatgen.

learningmatter-mit/AtomisticSkills176—~2.6kAutomated safety check: PassMITyesterday
20
20.Mat Raman Spectra

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/AtomisticSkills176—~2.3kAutomated safety check: PassMITyesterday
21
21.Mat Random Structure Search

Generate random crystal structures for a given composition (AIRSS-style) and relax with MLIPs to find low-energy candidates.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
22
22.Mat Stability

Calculate the thermodynamic stability and energy above the convex hull (Ehull) of a material at 0K.

learningmatter-mit/AtomisticSkills176—~2.2kAutomated safety check: PassMITyesterday
23
23.Mat Surface Energy

Calculate surface energy of various (hkl) planes and generate the equilibrium crystal shape (Wulff shape).

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITyesterday
24
24.ML Bayesian Optimization

Iteratively optimize expensive black-box objectives — such as materials properties, experimental yields, or simulation outputs — by learning from past evaluations to select the most promising next…

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITyesterday
25
25.ML Cluster Expansion

train a Cluster Expansion (CE) for lattice-based Monte Carlo simulation of disordered materials.

learningmatter-mit/AtomisticSkills176—~2.1kAutomated safety check: PassMITyesterday
26
26.ML Committee Uncertainty

Quantify prediction uncertainty of MACE MLIPs using committee (ensemble) models; flag high-uncertainty structures for DFT verification.

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITyesterday
27
27.ML Mlip Benchmark

Benchmark MLIP accuracy against a labeled dataset — compute MAE/RMSE for energy/atom and forces, and generate parity plots.

learningmatter-mit/AtomisticSkills176—~1.7kAutomated safety check: PassMITyesterday
28
28.Drug Admet Prediction

Compute RDKit physicochemical descriptors and rule-based drug-likeness heuristics (Ro5, Veber, QED) from SMILES.

learningmatter-mit/AtomisticSkills176—~1.1kAutomated safety check: PassMITyesterday
29
29.Drug Molecular Fingerprints

Compute Morgan/ECFP fingerprints, Tanimoto similarity, and optional Butina clusters/heatmaps for small-molecule comparison.

learningmatter-mit/AtomisticSkills176—~1kAutomated safety check: PassMITyesterday
30
30.General Deep Research

Perform iterative, deep, and comprehensive literature research on a specific materials/chemistry topic.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
31
31.General Workflow Planner

Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.

learningmatter-mit/AtomisticSkills176—~936Automated safety check: PassMITyesterday
32
32.Mat Md Monitors

Real-time monitoring tools for stability, equilibration, and diffusion during ASE molecular dynamics simulations.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITyesterday
33
33.ML Foundation Potentials

Guide for selecting the most appropriate foundation MLIP model based on simulation requirements.

learningmatter-mit/AtomisticSkills176—~1.5kAutomated safety check: PassMITyesterday

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