Lithium rose to 70,450 CNY/T on July 23, 2025, up 1.95% from the previous day. Over the past month, Lithium's price has risen 17.61%, but it is still 17.60% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lithium - values, historical data, forecasts and news - updated on July of 2025.

In 2022, the average price of battery-grade lithium carbonate stood at ****** U.S. dollars per metric ton. This figure is by far the highest price for battery-grade lithium carbonate recorded in the period of consideration. For 2024, lithium carbonate price was estimated at ****** U.S. dollars per metric ton. Lithium is a highly reactive soft and silvery-white alkali metal. As the third element in the periodic table, it cannot be found in its pure form in nature. Lithium is the least dense of solid elements and the lightest out of all metals. Lithium and batteries One of lithium’s most well-known end uses is in lithium-ion batteries. Lithium-ion batteries are rechargeable and mostly used in portable electronics and electronic vehicles. In lithium-ion batteries, the lithium ions move from the negative electrode to positive electrode while in use, and the process is reversed while charging. These batteries are highly flammable but are also low-maintenance. They have a high energy density and a low self-discharge. Some drawbacks include the fact that they are expensive to manufacture, and that they require protection circuits to maintain the voltage safely. Lithium-ion batteries are also the single-largest end use of lithium, amounting to an ** percent share of global lithium consumption in 2024. Lithium demand forecasts Looking to the future, lithium demand is forecast to stand at *** million tons by 2025. This growth will be mainly driven by lithium-ion battery demand for electric vehicles. Demand is expected to remain the highest in China, which will consistently account for half of global lithium-ion battery demand.

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Intro

Dataset from the publication "Lithium-ion battery degradation: comprehensive cycle ageing data and analysis for commercial 21700 cells", DOI: https://doi.org/10.1016/j.jpowsour.2024.234185

Full details of the study can be found in the publication, including thorough descriptions of the experimental methods and structure. A basic desciption of the experimental procedure and data structure is included here for ease of use.

Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 4 different SoC ranges [0-30, 70-85, 85-100, 0-100]%, as well as a further [0-100]% SoC range experiment which utilised a drive-cycle discharge instead of constant-current. The same C-rates (0.3C / 1 C, for charge / discharge) were used in all tests; multiple cells were tested under each condition. These are listed in the table below.

Cells were base-cooled at set temperatures using bespoke test rigs (see our linked publications for details; the supporting information file contains detailed descriptions and photographs). Cells were subject to break-in cycles prior to beginning of life (BoL) performance tests using the ‘Reference Performance Test’ (RPT) procedures. They were then alternately subject to ageing sets and RPTs until the end of testing. Full details of each of these procedures are described in the linked publication.

The data contained in this repository is then described in the Data section below. This includes a description of the folder structure and naming conventions, file formats, and data analysis methods used for the ‘Processed Data’ which has been calculated from the raw data.

An 'experimental_metadata' .xlsx file is included to aid parsing of data. A jupyter notebook has also been included to demonstate how to access some of the data.

Data

Data are organised according to their parent ‘Experiment’, as defined above, with a folder for each. Within each Experiment folder, there are 3 subfolders: ‘Summary Data’, ‘Processed Timeseries Data’, and ‘Raw Data’.

Summary Data

This folder contains data which has been extracted by processing the raw data in the ‘Degradation Cycling’ and ‘Performance Checks’ folders. In most cases, the data you are looking for will be stored here.

It contains:

Performance Summary

A summary file for each cell which details key ageing metrics such as number of ageing cycles, charge throughput, cell capacity, resistance, and degradation mode analysis results. Each row of data corresponds to a different SoH.

Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge. See our ACS publication for more details.

Data includes:

· Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to.

· Ageing Cycles: number of ageing cycles the cell has been subject to. *this is not equivalent full cycles.

· Ageing Set Start Date/ End date: The date that each ageing set began/ ended.

· Days of degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending.

· Age set average temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps).

· Charge throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cumulative total since BoL (not including RPTs, and not including break-in cycles).

· Energy throughput: as with "charge throughput", but for energy.

· C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT.

· C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT.

· 0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition).

· Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower SoCs of each electrode, and the capacity fraction of graphite in the negative electrode.

· Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity.

· DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL.

· RMSE data: the root mean squared error of the optimisation function calculated from the residual between the measured and simulated voltage vs capacity profiles.

Ageing Sets Summary

Data from the ageing cycles, summarised on an average per cycle and an average per ageing set basis. Metrics include mean/ max/ min temperatures, voltages etc.

Processed Timeseries data

Timeseries data (voltage, current, temperature, etc.) from each subtest (pOCV, GITT, etc.) of the RPTs, all grouped by subtest-type and by cell ID.

Contains the same data as in the ‘Performance Checks’ subfolder of the 'Raw Data' folder, but has been processed to slice into relevant subtests from the RPT procedure and includes only limited variables (time, voltage, current, charge, temperature). These are all saved as .csv files. In general this data will be easier to access than the raw data, but perhaps not as rich.

Raw Data

These are the raw data from the performance checks and from the degradation cycles themselves. The data from here has already been processed by me to get values of ‘energy throughput’, ‘charge throughput’, ‘average ageing temperature’, etc., which are all saved in the ‘Summary Data’ folder as described in the relevant section above.

The data in the ‘Degradation Cycling’ folder are organised by ageing set (where an ageing set is a defined number of ageing cycles, as described in the paper). In theory, each cell should have one datafile in each ageing set subfolder. However, due to experimental issues, tests can sometimes be interrupted midway though, requiring the test to be subsequently resumed. In this case, there may be

The demand for lithium-ion batteries (Li-ionBs) has surged, with a projected market value of $116 billion by 2030. However, only 5% of spent Li-ionBs are currently recycled due to the high costs, energy consumption, and environmental risks of existing recycling methods. This study focuses on developing an efficient, eco-friendly process to recover valuable metals like lithium (Li), cobalt (Co), nickel (Ni), and manganese (Mn) from Li-ionB waste, specifically targeting NMC 532 cathodes.Key innovations include using potentiostatic electrowinning with rotating cathodes and Pt-coated Ti anodes to selectively recover high-purity Ni-Co alloys (99% pure) , avoiding traditional, energy-intensive hydrometallurgical steps. Optimized leaching achieved recovery efficiencies of ~98.9% for Li, ~97.1% for Co, ~96.9% for Ni, and ~95.7% for Mn. Subsequent multi-stage precipitation recovered Ni, Co, Mn, and Li in various forms, lithium carbonate (Li₂CO₃, 99 % pure), manganese hydroxide (Mn(OH)₂, 99 % pure), and 0.6[Ni(OH)2].0.3[Mn(OH)2].0.1Co(OH)2. The spectra and chronoamperometry of the recovered materials are presented in the presented data sets.

Nickel fell to 15,412.88 USD/T on July 24, 2025, down 1.04% from the previous day. Over the past month, Nickel's price has risen 2.24%, but it is still 2.26% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Nickel - values, historical data, forecasts and news - updated on July of 2025.

Dataset from the publication "Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes". Full experimental details can be found in the related publication in ACS Applied Energy Materials: https://doi.org/10.1021/acsaem.2c02047

Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 2 SoC ranges [0-30, 0-100]%, with multiple cells tested under each condition. Cells were base-cooled at set temperatures using bespoke test rigs (see pubilcation for details). All electrochemical data were recorded using a Biologic BCS-815 battery cycler.

Break-in cycles:

Prior to any ageing or performance checks, all cells were subject to 5 full charge-discharge cycles as part of the break-in procedure. This consisted of a 0.2C charge to 4.2 V with CV-hold till C/100, and 0.2C discharge to 2.5 V (repeated for 5 cycles). Cells were rested under open circuit conditions for 2 hours after each charge and 4 hours after each discharge. These break-in cycles were performed at 25°C for all cells.

Ageing Conditions:

Ageing Conditions


    Expt
    SoC Range
    C-rate
    Temperature
    # of cells
    Cell IDs




    1
    0-30%
    0.3C / 1D
    10°C
    3
    A, B, J


    1
    0-30%
    0.3C / 1D
    25°C
    3
    D, E, F


    1
    0-30%
    0.3C / 1D
    40°C
    3
    K, L, M


    5
    0-100%
    0.3C / 1D
    10°C
    3
    A, B, C


    5
    0-100%
    0.3C / 1D
    25°C
    2
    D, E


    5
    0-100%
    0.3C / 1D
    40°C
    3
    F, G, H

For cells aged in the 0-30% SoC range, each ageing set consisted of 256 cycles over the 0-30% SoC range (discharge to 2.5 V, charge by passing 1500 mA h (== 0.3*nominal capacity)). C-rates were 0.3C for charge, and 1C for discharge.

For cells aged in the 0-100% SoC range, each ageing set consisted of 78 cycles over the full SoC range (discharge to 2.5 V, charge to 4.2 V with CV hold till C/100). C-rates were 0.3C for charge, and 1C for discharge.

Reference Performance Tests (RPTs):

All cells were characterised at beginning of life (BoL) and after each ageing set using a reference performance test (RPT). The RPT was always performed at 25°C. Two different RPT procedures were used: a longer procedure which was performed after each even-numbered ageing set, and a shorter procedure which was used after each odd-numbered ageing set. Both procedures are detailed below. A CC-CV charge at 0.3C to 4.2 V, 4.2 V till C/100 was performed between each step of the procedures.

Long RPT procedure:

C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).

C/2 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).

GITT discharge at 0.5C; 25 pulses with each pulse passing 200 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).

GITT discharge at 0.5C; 5 pulses with each pulse passing 1000 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).

Short RPT procedure:

C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).

Hybrid CC-pulse test with average current of C/2. A baseline DC current of C/2 was applied with an HPPC-type profile superimposed on top. This was done for discharge and charge (with voltage limits of 2.5 V and 4.2 V).

Hybrid CC-pulse test with average current of 1C. A baseline DC current of 1C was applied with an HPPC-type profile superimposed on top. This was done for discharge only (with a voltage limit of 2.5 V).

Extracted Data - Main

One csv file exists for each cell being tested, summarising the important data extracted from the ageing cycles and the RPTs. This includes:

Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to.

Ageing Cycles: number of ageing cycles the cell has been subject to. *this is not equivalent full cycles.

Ageing Set Start Date/ End date: The date that each ageing set began/ ended.

Days of Degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending.

Age Set Average Temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps) using a K-type thermocouple. Units: °C.

Charge Throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cummulative total since BoL (not including RPTs). Units: Ah.

Energy Throughput: as with "charge throughput", but for energy. Units: Wh.

C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT. Units: mAh.

C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT. Units: mAh.

0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition). Units: Ohms.

Extracted Data - Degradation Modes:

Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge.

The results of this analysis are saved in the DMA folder, with 4 csv files for each cell, which contain data for all RPTs. The 4 files contain:

Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower lithitation fractions of each electrode and the capacity fraction of graphite in the negative electrode.

Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity.

DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL.

RMSE data: the root-mean-square error of the optimisation function calculated from the residual between the measured and calculated voltage vs capacity profiles.

Timeseries data from RPTs:

Timeseries datafiles from the Biologic battery cycler which have been exported to csv and sliced for each step of each RPT procedure to help with future use of the data. Files contain [time, voltage, current, charge, temperature] data.

Jupyter Notebook:

A jupyter notebook has been included to aid futher use of this data. The notebook shows how to load the data into pandas DataFrame objects and provides a couple of example plots to view the datasets.

Notes:

A faulty electrical connection to cell A of Expt 5 (i.e. one of the cells being aged at 0-100% SoC at 10°C) during RPT4 led to erroneous results for that performance check (as evidenced in the 0.1s resistance value). The faulty electrical connection was fixed prior to subsequent cycling but the RPT was not repeated. We have kept the data collected during this RPT as part of the dataset, so caution should be used when using this specific portion.

This data set is associated with the aforementioned paper.

The data and the Jupyter notebooks (Python) to reproduce the figures in this paper can be downloaded below. To run a Jupyter notebook as a beginner, it is easiest to download and install anaconda, a Python environment that comes with many packages preinstalled and also offers Jupyter lab/notebook. It is available at https://www.anaconda.com/download.

Fig.01

Fig.01_literature_lithium_niobate_sources.csv contains a summary table of the last decades of published THz power values obtained with lithium niobate in the tilted pulse front geometry. The accompanying jupyter notebook allows to reproduce the figure that was used in the paper.

Fig.03

Each individual data frame (df), which is saved as an HDF file in the .zip file, contains a "power curve" measurement (i.e. measured THz power as a function of the applied pump power). Whenever a parameter is changed, all positions, angles, THz power and cryostat parameters are saved.

x1 is the position of the last mirror before the transmission grating (parallel to the pump beam direction before the crystal) in [mm]

x2 is the position of the first imaging lens in direction of the pump beam propagation direction before the crystal in [mm]

x3 is the position of the second imaging lens in the direction of the pump beam propagation direction before the crystal in [mm]

x4 is the position of the cryostat in the direction of the pump beam before reaching the crystal in [mm]

y0 is the position of the cryostat in the perpendicular direction of the pump beam before reaching the crystal in [mm]

α0 is the angle of the lambda/2 waveplate that allows the pump power to be varied at the crystal in [°]

α1 is the angle of the last mirror before the grating in [°]

α2 is the angle of the transmission grating in [°]

thz_power_W is the obtained power obtained from the Ophir 3A-P-THz power meter in [W]

temperature_setpoint_K is the LakeShore cryostat controller setpoint in [K]

temperature_K is the temperature read from the sensor on the cooling finger (above the crystal) in [K]

heater_output is the amount of power in [%] delivered to the resistive heating element inside the cryostat. 100% corresponds to about 50 W. Its value is controlled by an internal PID loop of the cryostat controller, which tries to stabilize temperature_K to temperature_setpoint_K

pump_power is the average laser power reaching the crystal in [W]. It was calibrated before obtaining the data set by characterizing the lambda/2 waveplate angle α0 to the value of an NIR power meter just before the cryostat.

repetition_rate is the repetition rate of the laser in [Hz]

As an example, below is one line (for one pump power) of such a data frame:

x1 x2 x3 x4 y0 α0 α1 α2 thz_power_W temperature_setpoint_K temperature_K heater_output pump_power repetition_rate

0 -12.000005 2.500039 9.100015 -5.0 -2.0 35.905660 25.68 -23.3 0.006000 80.0 79.883 4.4 20.0 40000.0

10 of such power curves were obtained at 100 kHz and 40 kHz and can be found in the respective zip-file.

Literature_Power_Efficiency.zip contains digitzed power and efficiency values from the following references:

X. Wu, D. Kong, S. Hao, et al., "Generation of 13.9-mJ Terahertz Radiation from Lithium Niobate Materials," Advanced Materials 35, 2208947 (2023).

P. L. Kramer, M. K. R. Windeler, K. Mecseki, et al., "Enabling high repetition rate nonlinear THz science with a kilowatt-class sub-100 fs laser source," Opt. Express 28, 16951 (2020).

T. Kroh, T. Rohwer, D. Zhang, et al., "Parameter sensitivities in tilted-pulse-front based terahertz setups and their implications for high-energy terahertz source design and optimization," Opt. Express, OE 30, 24186–24206 (2022).

B. Zhang, Z. Ma, J. Ma, et al., "1.4-mJ High Energy Terahertz Radiation from Lithium Niobates," Laser & Photonics Reviews 15, 2000295 (2021).

Fig.04

EOS_dfs.p is a pickle file, contain electro-optic sampling traces, which are already averaged for various pump powers at 40 kHz repetition rate.