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From characterization to simulation, from inquiry to report

Three engagement models, one platformized pipeline, four application scenarios. Computing tasks that traditionally take 6–12 months, delivered in days.

Engagement Models

Three ways to work together

Recommended

Custom Pipelines

CUSTOM PIPELINES

Hand your project to our agent pipeline: modeling, computation, analysis and reporting in one place — academic-grade reports with full figures.

  • Single-point / adsorption energy / volcano screening
  • Structure optimization · bands / DOS · free-energy steps
  • Deliverables ready for papers and proposals
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Deep Partnership

Collaborative R&D

COLLABORATIVE R&D

For teams with long-term R&D agendas: co-define projects, share IP and publication rights — our AI workbench and automation platforms support the whole journey.

  • Co-authorship and data-rights agreements
  • Q-nergy workbench attached to the project
  • Optional validation on automated lab platforms
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Flexible

Software & Model Subscription

SUBSCRIPTION

Subscribe to the latest software releases, continuously updated model libraries and platform features — run daily R&D tasks yourself on Q-nergy and the computing platform.

  • Latest software versions, continuously updated
  • Evolving model libraries and features
  • Team collaboration · multiple deployment modes
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How It Works

A six-step platformized pipeline, fully trackable

STEP 01

Submit

Describe the project & material system

STEP 02

Assess

Feasibility & quote within 48 hours

STEP 03

Execute

MLIP pre-screening + mainstream engines

STEP 04

Quality Gate

Multi-engine cross-validation · human review

STEP 05

Deliver

Academic-grade report & full figures

STEP 06

Follow-up

Q&A support & optional iterations

48 h
Response & solution assessment
5–10 days
End-to-end deliveryFinal timeline upon consultation
6–12 mo
Typical industry outsourcing cycle (comparison)
Scenarios

Typical Application Scenarios

Battery & Storage Materials

High-throughput electrolyte screening, interfacial-film mechanisms, electrode doping modification. Connectable to the Q-Batt inverse-design workbench and 16-channel digital twin.

  • Typical delivery: formulation comparison · interfacial energy dataset · modification advice

CO₂ Electroreduction

One of our most mature scenarios: high-entropy-alloy catalyst screening, adsorption scaling relations, volcano plots with multi-engine cross-validation, reproduced on real clusters.

  • Typical delivery: volcano plot · free-energy diagram · catalyst shortlist

Hydrogen & Water Splitting

HER / OER catalyst design and overpotential analysis; computed candidates can flow directly into experimental validation on the automated electrochemistry platform.

  • Typical delivery: activity-trend figures · interface stability analysis

Fast Functional-Material Prediction

Fast band / DOS prediction for metals, semiconductors and ionic crystals via the DFT-free engine — a prior ranking for experimental synthesis.

  • Typical delivery: electronic-structure report · ranked candidates
FAQ

Frequently Asked Questions

5–10 days end-to-end; final timeline upon consultation, depending on system size and workload. Compared with the typical 6–12 months of traditional outsourcing, the platformized pipeline compresses delivery by an order of magnitude.
Project data will never appear in public materials without permission, nor be used beyond the scope of cooperation; data-usage boundaries are specified clause by clause in the cooperation agreement.
Describe your project and material system via the website form or email (services@slisa.ac.cn); we return a feasibility assessment and computing plan within 48 hours, then enter the delivery pipeline after confirmation.
Yes. q-dft is Qcalc’s open-source project hosted on GitHub (github.com/JXiao-slisa/q-dft); the community may freely audit, reproduce and extend it. For commercial support and custom extensions, please contact us.
Q-electron is currently in development. For details, reach out via the form or email — we reply within 48 hours.

Start with one project — let AI prove its speed

Assessment returned within 48 hours. Let the data speak.