Lithium-ion batteries are a key enabler for electrifying transportation and decarbonizing the electricity grid . Optimizing new battery designs is challenging due to the need to simultaneously meet many The scope of our dataset across various cycling conditions is highlighted in the inscribed spider plot in blue compared to other large, publicly available battery cycling datasets . All batteries in this dataset are cycled at 25°C. The cycling experiment structure is shown schematically with the loop surrounding the spider plot. Individual cells go through a diagnostic "checkup" cycle, followed by 100 aging cycles repeating until end of life (EOL). b) The diagnostic cycle consisting of a reset cycle, a hybrid pulse power characterization (HPPC) , and three rate performance tests (RPTs) at 0.2C, 1C, and 2C discharge currents (see SI Table for full conditions). Mechanistic SOH metrics are extracted from various parts of this diagnostic cycle data (see SI Section S.3 for further details). c) The distribution of rate-dependent capacities at beginning of life (BOL). Means and coefficients of variation are included in the plot showcasing the tight distribution at BOL. d) The distribution of rate-dependent capacities at end of life (EOL, defined by 0.2C RPT capacity reaching 80% of the nominal capacity, 4.84Ah). The broadened distribution showcases diverse aging and highlights the limitations of using a single mechanistic SOH metric such as the low-rate capacity (for further information on BOL to EOL variability see SI Section S.5) .