{"paper":{"title":"Lie Generator Networks Extract EIS-Grade Battery Diagnostics from Pulse Relaxation Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Lie Generator Networks recover the same electrochemical time constants from 60-second pulse relaxation as from full EIS spectra.","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Rehan Kapadia, Shafayeth Jamil","submitted_at":"2026-05-14T19:22:48Z","abstract_excerpt":"Electrochemical impedance spectroscopy (EIS) is the most informative diagnostic for lithium-ion batteries: its frequency-resolved spectra decompose cell behavior into distinct electrochemical processes, revealing mechanism-specific degradation invisible to voltage and resistance measurements. Yet EIS requires dedicated hardware and minutes-long acquisitions incompatible with field deployment. Here we show that Lie Generator Networks (LGN), a structure-preserving identification framework, extract electrochemical time constants from 60 seconds of post-pulse voltage relaxation, data that battery "},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"LGN tracks degradation with near-perfect rank correlation (|ρ_s| = 0.999), enables cross-validated reconstruction of full Nyquist spectra at 2% median error across 227 cells, predicts which capacity-matched cells fail first from three early diagnostics, and recovers Arrhenius activation energies with zero physics priors.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The post-pulse voltage relaxation can be accurately represented as the output of a linear time-invariant system whose generator matrix directly encodes the same electrochemical time constants that appear in frequency-domain EIS measurements.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Lie Generator Networks learn the generator matrix of post-pulse relaxation dynamics to recover EIS-grade time constants and Nyquist spectra from 60-second data across multiple battery datasets and chemistries.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Lie Generator Networks recover the same electrochemical time constants from 60-second pulse relaxation as from full EIS spectra.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"77355b19e7d09a027583eabf7bb4c5b2d5965a54d5a04b0f9464299c11009773"},"source":{"id":"2605.15351","kind":"arxiv","version":1},"verdict":{"id":"5d27c6ed-7410-49bf-8f80-3fdbb2ac4c4a","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T15:36:31.083255Z","strongest_claim":"LGN tracks degradation with near-perfect rank correlation (|ρ_s| = 0.999), enables cross-validated reconstruction of full Nyquist spectra at 2% median error across 227 cells, predicts which capacity-matched cells fail first from three early diagnostics, and recovers Arrhenius activation energies with zero physics priors.","one_line_summary":"Lie Generator Networks learn the generator matrix of post-pulse relaxation dynamics to recover EIS-grade time constants and Nyquist spectra from 60-second data across multiple battery datasets and chemistries.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The post-pulse voltage relaxation can be accurately represented as the output of a linear time-invariant system whose generator matrix directly encodes the same electrochemical time constants that appear in frequency-domain EIS measurements.","pith_extraction_headline":"Lie Generator Networks recover the same electrochemical time constants from 60-second pulse relaxation as from full EIS spectra."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.15351/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T16:01:18.102850Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T15:53:47.778153Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T14:21:54.202572Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T13:33:22.749128Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"171b066119cf1a25fa513eee8e4e8c0fa519361d472cc5e6b406073fd33fce3e"},"references":{"count":18,"sample":[{"doi":"","year":2025,"title":"Global EV Outlook 2025,","work_id":"2cc830c6-b1f3-4f2b-b46b-4ca7cc282c02","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1016/j.xcrp.2021.100537","year":2021,"title":"End-of-life or second-life options for retired electric vehicle batteries,","work_id":"ff36424f-a716-49cd-8f81-5e6335a645a8","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1016/j.jpowsour.2024.235827","year":2025,"title":"Driving the future: A comprehensive review of automotive battery management system technologies, and future trends,","work_id":"278aa72e-9bca-4ea2-bc85-f9289ec1873b","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1002/0471716243","year":2005,"title":"E. Barsoukov and J. R. Macdonald, Eds., Impedance Spectroscopy. Wiley, 2005. doi: 10.1002/0471716243","work_id":"2acfb973-5057-4440-ab06-a3920f88a5b9","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1016/j.electacta.2015.03.123","year":2015,"title":"Analysis of Electrochemical Impedance Spectroscopy Data Using the Distribution of Relaxation Times: A Bayesian and Hierarchical Bayesian Approach,","work_id":"b4f2ee59-e8d6-4093-ab9f-fa28a3b4e5bc","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":18,"snapshot_sha256":"8d416e36eb1cb3bb4d6ebbb3685587fccc1b4b7996c7822423e6b55239954561","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}