How does SEI growth cause calendar aging in lithium-ion cells? Discover testing & modeling

SEI growth is a principal mechanism of calendar aging in graphite-based lithium-ion cells. During storage—especially under float-charging conditions such as constant exposure to approximately 3.8–3.9 V—electrolyte continues to decompose at the graphite anode. The resulting SEI thickens, consumes cyclable lithium, and increases interfacial resistance; its temperature dependence is commonly represented with an Arrhenius relationship. Researchers track these changes through capacity and resistance measurements, supported by Electrochemical Impedance Spectroscopy (EIS) and equivalent-circuit or physics-based battery models.

Calendar aging is not simply “time-related capacity loss”: it is the accumulated effect of parasitic electrode–electrolyte reactions. SEI growth gradually removes active lithium and raises impedance, while controlled storage tests and EIS help separate and quantify these effects.

Why SEI Growth Causes Calendar Aging

The SEI is protective but not perfectly inert

The SEI forms during initial charging when electrolyte components are reduced at the low-potential graphite surface. Its ideal structure is electronically insulating but sufficiently conductive to lithium ions, allowing lithiation while limiting further electrolyte decomposition.

In practice, passivation is incomplete. Small amounts of electrolyte and lithium continue to participate in side reactions, so the SEI can slowly become thicker and more resistive during storage.

Continued growth consumes cyclable lithium

Every additional reduction reaction incorporates electrolyte decomposition products into the interphase and consumes lithium that would otherwise shuttle between the electrodes. This produces loss of lithium inventory, which appears as declining discharge capacity.

The loss is largely irreversible. Even when the cell is not being cycled, the anode-side reactions can continue if the electrode potential and temperature enable them.

Growth increases impedance

A thicker or less conductive SEI adds resistance to lithium-ion transport across the graphite–electrolyte interface. The result is increased polarization, greater charge-transfer overvoltage, and reduced usable capacity under a specified load.

Thus, calendar aging has two linked outcomes:

• Capacity fade from loss of cyclable lithium.
• Power fade from increasing interfacial and transport resistance.

Why Storage Voltage and Temperature Matter

Float charging maintains a reactive state

Under float charging, the cell is continuously held at a defined voltage rather than being left at open circuit. For layered-oxide cathodes such as LiCoO₂ or LiNiₓMᵧO₂ paired with graphite, exposure to approximately 3.8–3.9 V can maintain conditions that promote ongoing parasitic reactions.

The applied cell voltage does not directly equal the graphite potential. However, it changes the electrode state of charge and the chemical driving forces at both interfaces, making voltage-controlled storage a useful accelerated-aging condition.

Temperature accelerates side reactions

SEI growth is commonly modeled with an Arrhenius dependence:

[ k(T)=k_{\mathrm{ref}} \exp\left[ -\frac{E_a}{R} \left(\frac{1}{T}-\frac{1}{T_{\mathrm{ref}}}\right) \right] ]

where (k(T)) is an aging or reaction-rate parameter, (E_a) is an apparent activation energy, (R) is the gas constant, and (T) is absolute temperature.

This relationship means that higher storage temperatures generally accelerate electrolyte decomposition and SEI growth. The fitted activation energy is an apparent parameter; it summarizes the measured aging process and may include more than one underlying reaction.

Solvent and electrode design influence the rate

Electrolyte formulation affects both the composition and growth rate of the SEI. The supplied references identify different growth tendencies for EC, EC/DMC mixtures, and pure DMC, with elevated temperature accelerating growth across these formulations.

Electrode density, stack pressure, separator contact, and cell assembly quality also matter. Non-uniform contact can create spatially different reaction rates and impedance, making an apparently simple aging experiment difficult to interpret.

How Battery Models Represent SEI Aging

Equivalent-circuit models connect measurements to mechanisms

A practical model may represent the cell using:

• Ohmic resistance, representing current collectors, electrolyte, tabs, and other fast resistive elements.
• Charge-transfer resistance and double-layer behavior, representing interfacial reaction kinetics.
• Diffusion or Warburg-type elements, representing lithium transport limitations.
• An SEI-related resistance or impedance element, representing transport through the growing interphase.

A simplified impedance expression may be written conceptually as:

[ Z(\omega)=R_{\Omega}+Z_{\mathrm{SEI}}(\omega) +Z_{\mathrm{ct}}(\omega)+Z_{\mathrm{diff}}(\omega) ]

The exact circuit should be selected from the observed spectra and validated against independent capacity and pulse-resistance data. A circuit is a useful parameterization, but its individual elements do not automatically correspond one-to-one with unique physical layers.

SEI growth can be coupled to capacity loss

A calendar-aging model often links an aging state variable—such as lost lithium inventory or SEI resistance—to time, temperature, and electrode condition. Depending on the assumed mechanism, the growth may be represented by a reaction-rate law, a diffusion-limited law, or an empirical power law.

The model is then fitted to storage data collected at several temperatures, voltages, and durations. Extrapolation should be restricted to conditions supported by the experiments because the dominant mechanism can change with state of charge, temperature, electrolyte, and electrode chemistry.

Models should distinguish resistance from lithium loss

A rise in impedance is not equivalent to a specific amount of capacity loss. SEI growth can simultaneously increase resistance and consume lithium, but other processes—including cathode degradation, lithium plating, contact changes, and loss of active material—can contribute to either measurement.

Reliable model development therefore uses multiple observables rather than fitting capacity alone. Capacity retention, impedance spectra, open-circuit behavior, and voltage-relaxation data provide complementary constraints.

How EIS Characterizes SEI-Related Aging

EIS measures the cell’s frequency-dependent response

In EIS, a small AC perturbation is applied around a selected operating point, and the resulting voltage or current response is measured across frequency. The resulting impedance spectrum changes as the cell ages.

Measurements are typically repeated at controlled states of charge, temperatures, and rest conditions. This control is essential because impedance itself depends strongly on SOC and temperature, even when no permanent aging has occurred.

Spectral features reveal resistance growth

Common qualitative interpretations include:

• The high-frequency intercept is associated primarily with ohmic resistance.
• A higher-frequency arc can reflect interfacial or SEI-related processes.
• A lower-frequency arc is often associated with charge transfer.
• A sloping low-frequency region is associated with diffusion and mass transport.

These assignments are not universal. Overlapping time constants, porous electrodes, distributed reaction sites, and instrument or fixture effects can make a single arc represent several processes.

Equivalent circuits quantify changes over time

Researchers fit EIS spectra with an equivalent circuit and track parameters such as (R_{\Omega}), SEI-related resistance, charge-transfer resistance, and diffusion coefficients or impedance terms.

An increasing SEI-related resistance during storage is consistent with interphase thickening or reduced ionic transport. The conclusion becomes stronger when it correlates with capacity loss, temperature dependence, and the expected response to SOC or voltage changes.

Testing systems enable controlled aging studies

Advanced laboratory battery test stations can combine galvanostatic cycling, constant-voltage or float storage, temperature control, and EIS. This allows researchers to measure impedance periodically or, where appropriate, continuously while maintaining defined test conditions.

A typical study compares cells stored at multiple temperatures and voltages, periodically returning them to a common reference condition for capacity and impedance measurements. The reference condition prevents changes in test temperature or SOC from being mistaken for permanent aging.

Designing a Reliable Characterization Workflow

Establish a formation baseline

The initial formation protocol strongly affects the first SEI. Formation current, voltage limits, temperature, rest periods, and electrolyte composition determine the interphase created before the calendar-aging experiment begins.

Initial coulombic efficiency, early-cycle impedance, and formation capacity provide baseline indicators of SEI quality. A poor or non-uniform initial SEI can dominate subsequent aging and obscure the mechanism being studied.

Control SOC, temperature, and mechanical conditions

EIS and capacity measurements should be made at standardized SOC, temperature, and rest duration. Otherwise, reversible changes in charge-transfer kinetics or electrolyte conductivity may be incorrectly interpreted as SEI growth.

Mechanical consistency is also important. Uniform electrode density, stack pressure, crimping, and electrical contact reduce measurement scatter and prevent assembly artifacts from appearing as electrochemical aging.

Combine EIS with destructive and non-destructive evidence

EIS is non-destructive and highly useful for tracking trends, but it does not by itself prove the chemical composition or thickness of the SEI. If detailed chemical identification is required, impedance should be complemented by methods such as post-mortem surface analysis.

For routine aging studies, the strongest evidence comes from combining:

• Capacity retention and coulombic efficiency.
• DC resistance or pulse-power measurements.
• EIS spectra at controlled SOC and temperature.
• Storage-voltage and temperature dependence.
• Post-test electrode or electrolyte analysis when mechanism confirmation is needed.

Understanding the Trade-offs

EIS parameters are not uniquely physical

Several equivalent circuits can fit the same spectrum, particularly when the SEI, charge-transfer reaction, and porous-electrode transport processes have overlapping frequency ranges. A fitted “SEI resistance” should therefore be described as SEI-associated unless independently validated.

Model selection should prioritize fit quality, parameter stability, physical plausibility, and agreement with separate measurements—not merely the lowest numerical fitting error.

Accelerated aging may change the mechanism

Higher temperature or elevated float voltage shortens test time, but excessive acceleration can introduce reactions that are not dominant under normal service conditions. For example, cathode-side degradation, gas generation, electrolyte oxidation, or lithium plating may become more important.

Acceleration is most defensible when the aging trend remains consistent across moderate conditions and the fitted model is validated against long-duration data near the intended operating range.

Resistance growth is not always caused by SEI growth

An increase in impedance can also result from cathode surface-film formation, electrolyte depletion, contact loss, separator changes, or active-material damage. Treating every impedance increase as anode SEI thickening can produce an incorrect lifetime model.

The layered-oxide/graphite systems described in the primary reference show SEI-dominated behavior under the specified float-charging conditions, but that conclusion should not be generalized to every cell chemistry or operating regime.

Applying This to a Battery Aging Study

A practical workflow is to define controlled storage conditions, measure capacity and EIS at common reference points, fit a validated circuit or aging model, and check the result against temperature and voltage dependence.

• If your primary focus is calendar-life prediction: Test multiple storage temperatures and voltages, fit an Arrhenius-based SEI-aging law, and validate it against cells held near the intended service conditions.
• If your primary focus is impedance and power fade: Track ohmic, SEI-associated, charge-transfer, and diffusion-related parameters with EIS, then confirm them with pulse-resistance measurements.
• If your primary focus is mechanism identification: Combine EIS and capacity data with controlled SOC/temperature testing and post-mortem surface analysis rather than relying on an equivalent circuit alone.
• If your primary focus is reproducible laboratory data: Standardize formation, electrode density, stack pressure, cell crimping, temperature control, and EIS measurement protocols.

The most reliable interpretation treats SEI growth as a coupled chemical, transport, and measurement problem—not as a single resistance value.

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