Lithium-Ion Batteries | Material Domains

Lithium-Ion Battery Domain

The battery domain provides evaluation models for lithium-ion cell components, including cathode composition (NMC, NCA, LFP), anode blending (silicon-graphite), and electrolyte formulation. The physics models are based on electrochemical intercalation theory and empirical degradation correlations.

Physics Model

Specific capacity is calculated from stoichiometric lithium content and redox couple voltages using the Nernst equation with activity corrections for mixed transition metal oxides.
Energy density combines capacity with average discharge voltage, accounting for polarization losses from charge transfer resistance and solid-state diffusion.
Cycle life is estimated using a semi-empirical degradation model that accounts for SEI growth (proportional to sqrt(cycles)), transition metal dissolution (proportional to Ni content), and structural fatigue from lattice volume change during cycling.
Cost is computed from raw material prices (Ni, Co, Mn, Li) and processing costs scaled by calcination temperature and time.

Default Parameters

Default Objectives

Templates

bash

materia init my-nmc --template battery/nmc-cathode
materia init my-electrolyte --template battery/solid-electrolyte
materia init my-anode --template battery/anode-design

Key Trade-Offs

The battery domain exhibits several well-known trade-offs:

Ni content vs. stability: Higher nickel content (NMC811, NMC9050505) delivers higher capacity but suffers from structural instability, cation mixing, and surface degradation.
Capacity vs. cycle life: Aggressive cycling to high voltage (4.5V+) extracts more capacity but accelerates degradation.
Performance vs. cost: Cobalt provides structural stability but is expensive and supply-constrained. Minimizing cobalt while maintaining performance is a primary industry goal.

Example: NMC Cathode Optimization

yaml

name: nmc-cathode-screen
domain: battery

parameters:
  - name: ni_content
    type: continuous
    bounds: [0.50, 0.90]
  - name: mn_content
    type: continuous
    bounds: [0.05, 0.25]
  - name: co_content
    type: continuous
    bounds: [0.05, 0.25]
  - name: calcination_temp
    type: integer
    bounds: [750, 900]
  - name: coating_thickness
    type: continuous
    bounds: [0.0, 3.0]

objectives:
  - name: specific_capacity
    direction: maximize
    unit: mAh/g
  - name: capacity_retention
    direction: maximize
    unit: "%"
  - name: cobalt_cost
    direction: minimize
    unit: USD/kWh

constraints:
  - expression: ni_content + mn_content + co_content <= 1.0

optimizer:
  method: cma-es
  budget: 400
  batch_size: 20
  seed: 42

Typical Results

A well-converged NMC cathode campaign typically finds Pareto solutions spanning:

High-capacity end: NMC811-like compositions with 195+ mAh/g but ~80% retention after 500 cycles
High-stability end: NMC532-like compositions with 160 mAh/g but >95% retention
Low-cost end: Cobalt-lean compositions (Co < 0.08) with moderate capacity and stability

Programmatic Access

python

from materia.plugins.battery import BatteryDomain

domain = BatteryDomain()
result = domain.evaluate({
    "ni_content": 0.8,
    "mn_content": 0.1,
    "co_content": 0.1,
    "calcination_temp": 850,
    "coating_thickness": 2.0,
})
print(result)
# {"specific_capacity": 195.2, "capacity_retention": 82.1, "cobalt_cost": 12.4}