How accurate is Micantis cycle life prediction?

Our AI model achieves 99.7% accuracy in predicting 1000+ cycle performance from just 100 formation cycles, backed by a money-back guarantee.

What battery chemistries does Micantis support?

Micantis supports all major battery chemistries including NMC, LFP, LTO, NCA, and emerging solid-state technologies.

Which battery cyclers are compatible with Micantis?

Micantis integrates with 50+ cycler brands including Arbin, Bitrode, Maccor, Neware, and supports custom integrations.

What lithium-ion battery chemistries does Micantis support?

Micantis supports all lithium-ion chemistries including NMC, LFP, LTO, NCA, and emerging solid-state batteries. Our AI models can be fine-tuned for specific chemistries and manufacturing processes.

Battery Analytics FAQ - Micantis | Battery Data Analytics Platform

Cycle Life Prediction

How can I predict battery cycle life without running 1000+ cycle tests?

Micantis uses AI-powered machine learning models trained on millions of battery cycles to predict cycle life from just 50-100 formation cycles with 99.7% accuracy. This reduces testing time from months to weeks while maintaining high confidence in performance predictions. Our models work with all lithium-ion chemistries including NMC, LFP, LTO, NCA, and emerging solid-state batteries.

How accurate is AI-based cycle life prediction?

Our validated models achieve 99.7% accuracy in predicting whether cells will meet cycle life specifications, backed by a money-back guarantee. Accuracy improves with more formation data, and models can be fine-tuned with your specific chemistry and manufacturing process data.

How many cycles of data do I need for accurate predictions?

Predictions require 50-100 formation or early cycles. The more data available, the higher the prediction confidence. Our models extract hundreds of features from electrochemical signatures that correlate with long-term performance.

Data Import & Cycler Support

What battery cycler formats does Micantis support?

Micantis supports automatic data import from 50+ file formats including all major cycler brands:

Cyclers: Arbin, Maccor, Neware, Bitrode, BioLogic, Basytec, Chroma, Landt, PEC, TOYO
Potentiostats: Gamry, Autolab, Hioki, Solartron, Princeton Applied Research, VersaSTAT
LIMS Integration: LabWare, STARLIMS, LabVantage, Benchling, Uncountable, LabVIEW

If we don't currently support your cycler format, we'll add support for it.

Can I import data from multiple cycler brands into one system?

Yes, Micantis is designed for multi-cycler environments. Data from different cycler brands is normalized and unified, allowing you to compare cells tested on different equipment and maintain a single source of truth for all battery test data.

Quality Control

How do I ensure incoming battery quality from suppliers?

Micantis provides automated incoming quality control (IQC) by analyzing supplier formation data, predicting cell performance before pack assembly, and generating supplier scorecards. This catches quality issues before production and prevents costly field failures and warranty claims.

What is battery formation data analytics?

Battery formation analytics involves extracting predictive features from the initial charging/discharging cycles (formation) of lithium-ion cells. Micantis analyzes formation data to predict long-term cycle life, identify defective cells early, and optimize grading decisions—all before cells leave the production line.

How can I reduce battery grading time in manufacturing?

By using AI predictions during formation, you can grade cells based on predicted final performance rather than waiting for extended cycle testing. This reduces grading time from weeks to hours while improving yield and reducing the number of cells that fail final QC.

Industry Solutions

Can Micantis help with aviation battery certification (DO-311A)?

Yes, Micantis provides aviation-specific features including DO-311A Quality Test Plan templates, thermal runaway analysis, drop test correlation, and compliance documentation. Generate 50-150 page DO-311A compliant reports in 2 days instead of 2 weeks. Full traceability from cell supplier to aircraft installation.

What about medical device battery testing requirements?

Micantis supports medical device battery qualification with IEC 62133 compliance tracking, lot traceability, and risk assessment documentation. Our platform helps meet FDA and CE marking requirements for battery-powered medical devices.

Do you support defense and military battery applications?

Yes, Micantis serves defense contractors working on UAV (unmanned aerial vehicles), UUV (unmanned underwater vehicles), and UGV (unmanned ground vehicles) battery systems. We're pursuing CMMC certification and can deploy in customer-controlled Azure tenants for enhanced security requirements.

Technical Integration

Does Micantis have an API or Python SDK?

Yes, Micantis offers a Python SDK (pip install micantis) with Jupyter notebook integration, Pandas DataFrame compatibility, and async support for high-performance analysis. REST APIs are also available for custom integrations and automation workflows.

How does Micantis compare to using Excel for battery data analysis?

Unlike Excel, Micantis provides:

Automated data import from any cycler (no manual formatting)
Professional battery-specific visualizations (dQ/dV, DCIR, capacity fade)
AI-powered cycle life predictions
Real-time test monitoring and alerts
Scales to millions of data points without performance issues

Customers report 85% reduction in analysis time compared to spreadsheet-based workflows.

Is Micantis secure and compliant?

Micantis is built on Azure enterprise infrastructure with GDPR compliance and SOC 2 Type II certification in progress. We offer multi-tenant deployment or dedicated customer tenant options for organizations with strict data isolation requirements. For defense applications, we're pursuing CMMC certification.

Frequently Asked Questions