ENT-00001901 · Scientific AI Model

NequIP

NequIP is a equivariant neural network potential associated with NequIP authors.

Level IV — ConnectedActiveConnected

Human readable record

Overview

NequIP is a scientific AI system associated with NequIP authors. The record focuses on its role in domain-specific prediction, scientific analysis, biological modeling, materials discovery or research-oriented machine learning.

Timeline

2023NequIP public documentation anchor
NequIP appears in public documentation or stable reference sources as a equivariant neural network potential associated with NequIP authors.

Capabilities

Model capabilityResearch referenceBenchmarkable system

Known limitations

The record describes the public identity and documented role of the entity, not private implementation details.Capabilities depend on version, deployment context, access conditions and the available public documentation.

Technical and registry detail

Technical description

Structured record for NequIP. The technical layer identifies entity type, classification, creator or organization, public source anchors, timeline entry, capabilities, limitations, registry status and graph relationships. Source anchor: https://github.com/mir-group/nequip.

Controlled tags

AI ModelResearch SystemTechnical Record

Relationship graph

NequIP

Created byNequIP authors

NequIP is associated with NequIP authors through its documented source context.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

{
    "@context": "https://schema.org",
    "@type": "Thing",
    "identifier": "ENT-00001901",
    "name": "NequIP",
    "alternateName": [],
    "additionalType": "Scientific AI Model",
    "description": "NequIP is a equivariant neural network potential associated with NequIP authors.",
    "creator": "NequIP authors",
    "url": "entity.php?id=ENT-00001901",
    "sameAs": "https://github.com/mir-group/nequip",
    "lxkeysWorld": {
        "classification": "equivariant neural network potential",
        "organization": "NequIP authors",
        "originContext": "Public AI and technical record",
        "firstPublicAppearance": "2023",
        "currentStatus": "Active",
        "registryStatus": "Connected",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV — Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:29+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:29+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:29+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "capabilities": [
            "Model capability",
            "Research reference",
            "Benchmarkable system"
        ],
        "limitations": [
            "The record describes the public identity and documented role of the entity, not private implementation details.",
            "Capabilities depend on version, deployment context, access conditions and the available public documentation."
        ],
        "tags": [
            "AI Model",
            "Research System",
            "Technical Record"
        ],
        "timeline": [
            {
                "date": "2023",
                "title": "NequIP public documentation anchor",
                "description": "NequIP appears in public documentation or stable reference sources as a equivariant neural network potential associated with NequIP authors."
            }
        ],
        "relationships": [
            {
                "target": "NequIP authors",
                "type": "Created by",
                "description": "NequIP is associated with NequIP authors through its documented source context.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Model card, paper, official page or repository",
                "url": "https://github.com/mir-group/nequip",
                "source_type": "Official Repository",
                "verification_status": "verified"
            }
        ]
    }
}

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