Convert between image formats (PNG, JPG, WEBP)

Extract audio track from MP4 video to MP3 or WAV format

Compress an MP4 video using FFmpeg with quality settings

Download a specific time range from a YouTube video as an MP4 clip

while maintaining its current format

File operation and conversion endpoints

Estimate USD/kg cost from the structure's composition using elemental market prices. Returns cost per kg, per-element breakdown, molecular weight, and which elements lack price data.

Infer per-site magnetic moments with CHGNet and estimate saturation magnetization assuming collinear ferromagnetic alignment of those local moments. Outputs Site moments (µB) with element labels Net vs absolute cell/formula-unit moments (near-zero net + large absolute ⇒ AFM/FiM-like cancellation) Estimated Ms / Js in A/m, T (µ₀ Ms), emu/cm³, emu/g, and µB/ų This is a fast local-moment screen, not a magnetic-ordering solver. Pair with Curie-temperature prediction for a fuller magnet dossier.

Parse a CIF and return chemical formula, atom count, lattice parameters, space group, crystal system, point group, volume, and density. Optional and control symmetry analysis.

Research endpoints

and return a CIF file. Size : presets , , (bulk) or , , (in-plane / 2D). : custom (overrides ). Use e.g. for monolayers like MoS2. Vacuum (2D / slabs) : minimum total vacuum in Å along (default axis = c). Expands the cell if needed and centers the slab. Typical values: 15–20 Å. Does not extract a monolayer from bulk; pads whatever layers are already in the cell. Limits: each dimension 1–20; result capped at 2000 atoms. Response includes the CIF plus lattice parameters and resolved vacuum for both the input and supercell.

Fast endpoints for working with crystal structures (CIF). Extract symmetry and composition, expand supercells with optional vacuum padding, estimate raw material cost from elemental market prices, and predict magnetic properties (Curie temperature and site moments / estimated Ms) using CHGNet-based models.

Predict the ferromagnetic Curie temperature (K) of a crystal structure. Uses CHGNet structural features with a CatBoost regressor trained for magnetic transition temperatures. Input: CIF file. Output: temperature in kelvin.

Convert between image formats (PNG, JPG, WEBP)

Extract audio track from MP4 video to MP3 or WAV format

Compress an MP4 video using FFmpeg with quality settings

Download a specific time range from a YouTube video as an MP4 clip

while maintaining its current format

File operation and conversion endpoints

Estimate USD/kg cost from the structure's composition using elemental market prices. Returns cost per kg, per-element breakdown, molecular weight, and which elements lack price data.

Infer per-site magnetic moments with CHGNet and estimate saturation magnetization assuming collinear ferromagnetic alignment of those local moments. Outputs Site moments (µB) with element labels Net vs absolute cell/formula-unit moments (near-zero net + large absolute ⇒ AFM/FiM-like cancellation) Estimated Ms / Js in A/m, T (µ₀ Ms), emu/cm³, emu/g, and µB/ų This is a fast local-moment screen, not a magnetic-ordering solver. Pair with Curie-temperature prediction for a fuller magnet dossier.

Parse a CIF and return chemical formula, atom count, lattice parameters, space group, crystal system, point group, volume, and density. Optional and control symmetry analysis.

Research endpoints

and return a CIF file. Size : presets , , (bulk) or , , (in-plane / 2D). : custom (overrides ). Use e.g. for monolayers like MoS2. Vacuum (2D / slabs) : minimum total vacuum in Å along (default axis = c). Expands the cell if needed and centers the slab. Typical values: 15–20 Å. Does not extract a monolayer from bulk; pads whatever layers are already in the cell. Limits: each dimension 1–20; result capped at 2000 atoms. Response includes the CIF plus lattice parameters and resolved vacuum for both the input and supercell.

Fast endpoints for working with crystal structures (CIF). Extract symmetry and composition, expand supercells with optional vacuum padding, estimate raw material cost from elemental market prices, and predict magnetic properties (Curie temperature and site moments / estimated Ms) using CHGNet-based models.

Predict the ferromagnetic Curie temperature (K) of a crystal structure. Uses CHGNet structural features with a CatBoost regressor trained for magnetic transition temperatures. Input: CIF file. Output: temperature in kelvin.