AI FOR ELECTROCHEMISTRY EST. 2026
QCALC · COREONLINE
AGENTS5 / 5 · RELAY
MLIP STACKMACE · DPA-4
ENGINESCP2K · ABACUS
VALIDATED33 SYSTEMS
DELIVERY5–10 D *
0x51 43 41 4C 43 · SIM RELAY ACTIVE · RSI LEDGER SYNC · FLYWHEEL ROTATING · NODE HANGZHOU CN · UPTIME 00:00:00 · NO DRIFT DETECTED ·
AI FOR ELECTROCHEMISTRY · QCALC

The AI Atomic-Simulation Foundation for Electrochemistry One data-flywheel base · Two native engines

We are building the “AlphaFold” of electrochemistry — compressing the discovery of battery, catalysis and clean-energy materials from years down to days.

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q-dft open source Multiple academic papers Patents & copyrights pending Used daily by real customers
SYSTEM ONLINE · ALL MODULES NOMINAL
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Why Qcalc

R&D acceleration validated by institutions

Not a concept demo — a productivity tool used daily by real institutional customers.

5–10 days
End-to-end deliveryFinal timeline upon consultation · industry outsourcing typically 6–12 months
33 systems
DFT-free electronic-structure engine
validated material systems
100 +
Q-nergy 3D modeling panels
slab builder · Wulff · Brillouin zone
3+2
Invention patents + software copyrights
filed under the company
Product Matrix

One base · Two engines · A closed automation loop

From an AI research workbench to automated hardware — every delivery flows data back, making the base stronger every day.

Commercial

Q-nergy AI RESEARCH WORKBENCH

Autonomous AI research workbench · flagship

Hypothesis-to-report closed loop, 24/7: five-agent pipeline plus RSI recursive self-improvement; 12-tab Research Hub, 100+ 3D modeling panels, bilingual UI, Docker / desktop deployment — a real product used daily by institutions.

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Open Source

q-dft AI DFT AGENT

Five-agent relay · open source on GitHub

Surface scientist → MLIP optimization → DFT engineering → analysis → report; three standard workflows.

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In Development

Q-electron

Electrochemistry foundation framework
Contact for details →
Platform

DeepDFT

Computing service platform
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Digital Twin

Q-Batt INVERSE DESIGN

Battery inverse design · four linked views

Molecule · crystal · Pareto · 16-channel FlowBench twin.

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Hardware

FLOWCELL-BUS AUTOMATED LAB

Automated electrochemistry · integrated hardware

11 module classes on one bus — AI agents drive lab hardware directly.

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Live Workbench

Q-nergy · the live workbench

Every five-agent session is visible in real time: tabs advance with execution stages, logs stream line by line, and the chart draws itself — fully transparent from system design to academic report.

  • ▸ 12-tab Research Hub · 100+ modeling panels
  • ▸ RSI recursive self-improvement · experience auto-archived
  • ▸ Bilingual UI · Docker / desktop deployment
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Q-NERGY · RESEARCH HUBLIVE SESSION
  • Overview
  • Pipeline
  • ML Lab
  • Report
  • RSI Ledger
Research Hub ML Lab Evaluation

Q-nergy live session illustration · agent relay executing automatically

Why Qcalc

Why Qcalc?

Efficiency First

Delivery measured in days versus 6–12 months for traditional outsourcing — an order-of-magnitude compression of R&D iteration cycles.

Self-Sustaining

Computing services generate cash flow that funds foundation research — a technology route that doesn’t depend on external transfusions.

Flywheel Effect

Every delivery automatically deposits structural and result data — customers fund the production of our foundation-model training set.

Untapped Blue Ocean

AI for Science is moving from Nobel prizes to industry — and electrochemistry is the largest untapped territory on the AI4S map.

DELIVER交付 DATA数据 MODEL模型 GROW增长 FME Electrochemistry Foundation Model

DATA FLYWHEEL · EVERY DELIVERY MAKES THE BASE STRONGER

Core Technology

A three-layer stack, one DFT-free road

Multiscale Agent Engine

Open-source MLIPs (MACE / DPA-4) for high-throughput pre-screening, refined by mainstream engines such as CP2K / ABACUS — agents orchestrate cluster compute.

Multi-Agent Automation

Five-agent relay pipeline with RSI recursive self-improvement: experience auto-archived, dual-ledger audited — the system gets sharper with use.

DFT-Free Frontier

Electronic structure without the traditional DFT workflow — validated on 33 systems, paving the way to the electrochemistry foundation model.

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Applications

Core scenarios for clean energy

Batteries & Storage

Electrolyte formulation screening, interfacial film (SEI/CEI) mechanisms, electrode material modification.

CO₂ Electroreduction

High-entropy-alloy catalyst screening, adsorption scaling relations, batch volcano plots.

Hydrogen & Water Splitting

HER / OER catalyst design, constant-potential interface simulation, overpotential analysis.

Functional Materials

Fast band-structure / DOS prediction for semiconductors, insulators and alloys, with inverse design.

Trusted by Institutions

Working alongside leading institutions

(Selected partners)

复旦大学FUDAN UNIVERSITY
浙江大学长三角智慧绿洲ZJU YANGTZE DELTA
北京林业大学BEIJING FORESTRY UNIVERSITY
浙江师范大学ZHEJIANG NORMAL UNIVERSITY
山西大学SHANXI UNIVERSITY
上海第二工业大学SHANGHAI SECOND POLYTECHNIC
北京理工大学BEIJING INSTITUTE OF TECHNOLOGY
华南理工大学SOUTH CHINA UNIVERSITY OF TECHNOLOGY
上海市重大传染病和生物安全研究院SHANGHAI INSTITUTE OF INFECTIOUS DISEASES
Get Started

Ready to accelerate your electrochemical R&D?

Tell us your material system and goal — we return an assessment and computing plan within 48 hours.

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