Battery intelligence

Battery health insight from raw test data.

SciPhys brings the same research workspace logic to battery data: structured uploads, interpretable health indicators, anomaly review and trend analysis.

SOH

Summarize health indicators from cycling data.

Cycles

Track capacity, voltage, current and degradation trends.

Context

Connect battery data to sample, chemistry and test conditions.

What it does

Built around scientific evidence.

From battery tester exports to health signals

Battery instruments generate dense time-series and cycle tables. SciPhys structures these files so researchers can inspect state of health, capacity fade, efficiency and anomalous behavior.

  • Parse spreadsheet-style battery tester outputs.
  • Summarize cycle-level indicators and degradation trends.
  • Keep chemistry, cell format and test protocol metadata attached.

Designed for research and early validation

The battery module focuses on helping research teams compare materials, cells and protocols before scaling into fleet-level battery analytics.

  • Compare cells under different conditions.
  • Flag unusual cycles and suspicious measurement segments.
  • Generate concise health summaries for reports and meetings.

Part of the wider materials data platform

Battery performance can be connected to synthesis, structure and characterization data when all experiments live in the same workspace.

  • Link electrochemical behavior to XRD, Raman or microscopy evidence.
  • Search historical battery runs by chemistry, batch and protocol.
  • Build the data foundation for future prediction and optimization.

Workflow

From raw files to research decisions.

01

Import

Upload cycling files and test metadata.

02

Measure

Extract health indicators, trends and anomalies.

03

Compare

Ask questions across cells, batches and protocols.

FAQ

Questions researchers ask first.

What battery data does SciPhys target first?+

The initial battery workflow targets common spreadsheet exports from testing instruments, including cycle summaries and time-series measurement data.

Is this for lab batteries or deployed fleets?+

SciPhys currently focuses on research and validation workflows where battery data must be interpreted together with materials context.

Can battery data be compared with XRD or Raman results?+

Yes. The long-term platform direction is to connect performance data with structural, spectral and microscopy evidence in one workspace.

Continue exploring

Lab data management

Keep battery tests searchable with metadata.

Materials AI

Connect performance, structure and literature.

Platform

See the full SciPhys workflow.