Zinc rose to 3,118.55 USD/T on March 27, 2026, up 1.01% from the previous day. Over the past month, Zinc's price has fallen 6.13%, but it is still 9.21% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Zinc - values, historical data, forecasts and news - updated on March of 2026.

Description:

A simple yet challenging project, to forecast the IMF commodity price of Zinc, based on monthly totals zinc price recorded from 1980 to 2016. Can you overcome these obstacles & Forecast its future prices?

This data frame contains the following columns:

• Month : The month of observation
• Price : Average Prices of zinc in that particular month

Acknowledgement

This dataset is referred from Kaggle.

Objectives:

• Understand the Dataset & cleanup (if required).
• Perform the necessary checks like stationarity & DF on the Dataset.
• Build a forcasting model to forecast zinc prices.

Monthly Zinc prices measured in USD per metric tonne (mt).

Global Zinc Prices - Historical chart and current data through 2026.

This dataset contains historical price data for seven essential metals traded on the Multi Commodity Exchange (MCX) India: Gold, Silver, Lead, Zinc, Copper, Nickel, and Aluminum. The data is meticulously collected to support prediction models, trend analysis, and statistical exploration of metal price movements.

The dataset includes: - Daily price data for 7 metals - Open price, high/low values, and closing prices - Data across multiple periods, useful for preliminary exploration, model training, and analysis

Description for each column in the dataset: 1. Date: The date on which the market data was recorded (format: DD-MM-YYYY). 2. Price: The closing price of Copper on the given date, reflecting the last traded price of the day. 3. Open: The opening price of Copper at the start of trading on the given date. 4. High: The highest price Copper reached during the trading day. 5. Low: The lowest price Copper traded at during the day. 6. Vol. (Volume): The total volume of Copper traded on the given day, typically in thousands (K). 7. Change %: The percentage change in the closing price from the previous trading day.

Knoema provides access to the World Bank Commodity Price data through an online database tool. World Bank Commodity Prices are available through Knoema on an annual/monthly basis. Data are updated continuously.

Website: https://knoema.com/WBCPD2015Oct/world-bank-commodity-price-data-pink-sheet-monthly-update

The zinc ingot prices in the United States for Q3 2024 reached 3450 USD/MT in September. The region saw notable fluctuations in zinc ingot prices throughout the quarter, primarily influenced by the limited availability of zinc ingots and ongoing supply chain challenges. These factors, coupled with consistent demand from critical sectors, have kept prices on an upward trajectory, emphasizing the market's sensitivity to supply-demand dynamics.

Explore IMARC’s newly published report, titled “Zinc Ingot Prices, Trend, Chart, Demand, Market Analysis, News, Historical and Forecast Data Report 2024 Edition,” offers an in-depth analysis of zinc ingot pricing, covering an analysis of global and regional market trends and the critical factors driving these price movements.

Average Rural Consumer Price: Zinc Plate: West Sumatera data was reported at 85,832.000 IDR/m in Dec 2018. This stayed constant from the previous number of 85,832.000 IDR/m for Nov 2018. Average Rural Consumer Price: Zinc Plate: West Sumatera data is updated monthly, averaging 59,499.000 IDR/m from Jan 2008 (Median) to Dec 2018, with 132 observations. The data reached an all-time high of 85,832.000 IDR/m in Dec 2018 and a record low of 42,406.000 IDR/m in Feb 2008. Average Rural Consumer Price: Zinc Plate: West Sumatera data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Prices – Table ID.PE073: Average Rural Consumer Price: By Province: Housing Product: Zinc Plate.

The increasing use of electronic devices raises concerns about resource availability and end-of-life management, particularly regarding conductors for interconnects and sensing elements. While gold and silver are the leading materials for interconnects, they pose challenges related to scarcity, cost, and toxicity. Zinc offers a promising alternative due to its good electrical conductivity, non-toxicity, abundance, and affordability. However, challenges in achieving high conductivity and waste generation from processing techniques like screen-printing remain. To address this, a zinc ink optimizes for 3D printing is proposed, using active zinc particles in a shellac matrix. The methods, including chemical and photonic sintering, achieve conductivities of up to 8.74•10⁴ S m⁻¹ on paper substrates, with stable performance over a range of 30%–70% relative humidity at 15, 20, 25, and 30 °C respectively. Potential applications in high-conductivity transducers for humidity sensing and metal-air batteries are demonstrated, achieving a maximum power output of 3.5 mW and an open-circuit voltage of 1.25 V. The integration of digital material assembly of zinc, reliable high-performance operation, and non-toxicity pave the way for innovative advancements in sustainable electronics, including applications in environmental sensing, e-textiles, and healthcare.

Dataset:

Aqueous organic redox flow batteries offer great promise for long-duration stationary energy storage but are often hindered by high costs associated with synthetic redox-active materials and expensive ion-exchange membranes. Polymer-based redox species allow the use of cheaper microporous membranes, yet synthetic redox polymers remain costly to produce. In this study, a cost-effective zinc/lignosulfonate hybrid redox flow battery (RFB) is presented, employing commercial sodium lignosulfonate (NaLS) as a biopolymer catholyte, Zn foil as a low-cost and abundant anode, and a cost-effective size-exclusion cellulose membrane as the separator. The sluggish electrochemical behavior of the NaLS is enhanced by using carbon-impregnated felt electrodes. Using 10 mM NaLS (20 kDa), the system achieves an average discharge voltage of 0.98 V and an initial capacity of 1.41 Ah L−1 (9.4 mAh g−1), outperforming previous lignin-based RFBs. Increasing NaLS concentration to 30 mM boosts capacity to 3.52 Ah L−1, although the cycling stability in 1 M ZnSO4 remains moderate. However, increasing the ZnSO4 concentration to 3 M further improves cyclability, with capacity retention rising to 72% over 28 days, compared to 66% over 17 days for 1 M ZnSO4. This work represents the first demonstration of commercial lignosulfonate as a catholyte in Zn-hybrid RFBs, showcasing its potential as a sustainable active material with a remarkably low electrolyte cost of 26 € kWh−1.

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

This Data consists of some world statistics published by the World Bank since 1961

Variables:

1) Agriculture and Rural development - 42 indicators published on this website. https://data.worldbank.org/topic/agriculture-and-rural-development

2) Access to electricity (% of the population) - Access to electricity is the percentage of the population with access to electricity. Electrification data are collected from industry, national surveys, and international sources.

3) CPIA gender equality rating (1=low to 6=high) - Gender equality assesses the extent to which the country has installed institutions and programs to enforce laws and policies that promote equal access for men and women in education, health, the economy, and protection under law.

4) Mineral rents (% of GDP) - Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.

5) GDP per capita (current US$) - GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.

6) Literacy rate, adult total (% of people ages 15 and above)- Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.

7) Net migration - Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.

8) Birth rate, crude (per 1,000 people) - Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.

9) Death rate, crude (per 1,000 people) - Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.

10) Mortality rate, infant (per 1,000 live births) - Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

11) Population, total - Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.

Acknowledgements

These datasets are publicly available for anyone to use under the following terms provided by the Dataset Source https://www.worldbank.org/en/about/legal/terms-of-use-for-datasets

Banner photo by https://population.un.org/wpp/Maps/

Inspiration

Subsaharan Africa and east Asia record high population total, actually Subsaharan Africa population bypassed Europe and central Asia population by 2010, has this been influenced by crop and food production, large arable land, high crude birth rates(influx), low mortality rates(exits from the population) or Net migration.

Summary

Dataset of imaging data related to the publication Raudenska, M., Kratochvilova, M., Vicar, T., Gumulec, J., Balvan, J., Polanska, H. Pribyl, J. & Masarik, M.:Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation. Scientific Reports 2019, 9, 1660

This dataset includes image data of atomic force microcopy (Young modulus) and confocal microscopy(staining of F-actin and β-tubulin) of prostate cell lines PNT1A, 22Rv1, and PC-3.

Materials and Methods

Cells, cell culture conditions

Cells confluent up to 50–60% were washed with a FBS-free medium and treated with a fresh medium with FBS and required antineoplastic drug concentration (IC50 concentration for the particular cell line). The cells were treated with 93 µM (PC-3), 38 µM (PNT1A), and 24 µM (22Rv1) of cisplatin (Sigma-Aldrich, St. Louis, Missouri), respectively. IC50 concentrations used for treatment with docetaxel (Sigma-Aldrich, St. Louis, Missouri) were 200nM for PC-3, 70nM for PNT1A, and 150nM for 22Rv1.

Long-term zinc (II) treatment of cell cultures

Cells were cultivated in the constant presence of zinc(II) ions. Concentrations of zinc(II) sulphate in the medium were increased gradually by small changes of 25 or 50 µM. The cells were cultivated at each concentration no less than one week before harvesting and their viability was checked before adding more zinc. This process was used to select zinc resistant cells naturally and to ensure better accumulation of zinc within the cells (accumulation of zinc is usually poor during the short-term treatment of prostate cancer cells). Total time of the cultivation of cell lines in the zinc(II)-containing media exceeded one year. Resulting concentrations of zinc(II) in the media (IC50 for the particular cell line) were 50 µM for the PC-3 cell line, 150 µM for the PNT1A cell line, and 400 µM for the 22Rv1 cell line. The concentrations of zinc(II) in the media and FBS were taken into account.

Actin and tubulin staining

β-tubulin was labeled with anti- β tubulin antibody EPR1330 at a working dilution of 1/300. The secondary antibody used was Alexa Fluor® 555 donkey anti-rabbit (ab150074) at a dilution of 1/1000. Actin was labeled with Alexa Fluor™ 488 Phalloidin (A12379, Invitrogen); 1 unit per slide. For mounting Duolink® In Situ Mounting Medium with DAPI (DUO82040) was used. The cells were fixed in 3.7% paraformaldehyde and permeabilized using 0.1% Triton X-100.

Confocal microscopy

The microscopy of samples was performed at the Institute of Biophysics, Czech Academy of Sciences, Brno, Czech Republic. Leica DM RXA microscope (equipped with DMSTC motorized stage, Piezzo z-movement, MicroMax CCD camera, CSU-10 confocal unit and 488, 562, and 714 nm laser diodes with AOTF) was used for acquiring detailed cell images (100× oil immersion Plan Fluotar lens, NA 1.3). Total 50 Z slices was captured with Z step size 0.3 μm.

Atomic force microscopy

We used the bioAFM microscope JPK NanoWizard 3 (JPK, Berlin, Germany) placed on the inverted optical microscope Olympus IX‑81 (Olympus, Tokyo, Japan) equipped with the fluorescence and confocal module, thus allowing a combined experiment (AFM‑optical combined images). The maximal scanning range of the AFM microscope in X‑Y‑Z range was 100‑100‑15 µm. The typical approach/retract settings were identical with a 15 μm extend/retract length, Setpoint value of 1 nN, a pixel rate of 2048 Hz and a speed of 30 µm/s. The system operated under closed-loop control. After reaching the selected contact force, the cantilever was retracted. The retraction length of 15 μm was sufficient to overcome any adhesion between the tip and the sample and to make sure that the cantilever had been completely retracted from the sample surface. Force‑distance (FD) curve was recorded at each point of the cantilever approach/retract movement. AFM measurements were obtained at 37°C (Petri dish heater, JPK) with force measurements recorded at a pulling speed of 30 µm/s (extension time 0.5 sec).

The Young's modulus (E) was calculated by fitting the Hertzian‑Sneddon model on the FD curves measured as force maps (64x64 points) of the region containing either a single cell or multiple cells. JPK data evaluation software was used for the batch processing of measured data. The adjustment of the cantilever position above the sample was carried out under the microscope by controlling the position of the AFM‑head by motorized stage equipped with Petri dish heater (JPK) allowing precise positioning of the sample together with a constant elevated temperature of the sample for the whole period of the experiment. Soft uncoated AFM probes HYDRA-2R-100N (Applied NanoStructures, Mountain View, CA, USA), i.e. silicon nitride cantilevers with silicon tips are used for stiffness studies because they are maximally gentle to living cells (not causing mechanical stimulation). Moreover, as compared with coated cantilevers, these probes are very stable under elevated temperatures in liquids – thus allowing long-time measurements without nonspecific changes in the measured signal.

Image analysis

Fluorescence microscopy data were analyzed in ImageJ 1.52h and Python 3.7.1 as follows: cells were manually segmented using actin fluorescence channel, two regions were created for analysis: whole cell and cell periphery, lining a 4 μm thick region around cell border and including most of periphery actin cytoskeleton. In these two regions following parameters were measured for both actin and tubulin fluorescence: Integrated intensity, median intensity, and following regions were measured to describe cell morphology: Cell area, Maximum caliper (max feret diameter), roundness, and aspect ratio. Moreover, stress fibers were manually segmented in every cell and following parameters were measured: number of fibers per cell, feret angle of fiber, integrated intensity, fiber length, mean intensity. Next, a standard deviation of feret angles of individual fibers was calculated relatively to mean of feret angle using a circstd function from scipy package for Python.

Identification of files

Microscopy data

Files are separated into individual zip files. The dataset of confocal microscopy is separated based on treatments: untreated control, docetaxel-treated cells, cisplatin-treated cells, zinc-treated cells. Filenames actin_tubulin_Zstack_cisplatin.zip, actin_tubulin_Zstack_untreated_control.zip, actin_tubulin_Zstack_zinc.zip, actin_tubulin_Zstack_docetaxel.zip. Files included in these ZIP archives are named as follows: "cellline_treatment_FOV". Files are 3-layer 16bit tiff files with layer sequence as follows: F-Actin (Phalloidin)/b-tubulin/Hoechst 33342. The dataset contains 242 FOVs of three cell line types/three treatments + one control, files are Z-stacks made of 50 slices.

The dataset of atomic force microscopy (AFM) is included in one ZIP archive "AFM_YoungModulus_SetpointHeight.zip", which includes data on Young modulus and Setpoint Height of cell lines 22Rv1, PNT1A and PC-3 and treatments zinc, docetaxel, cisplatin (+control), i.e. identical like for confocal microscopy. The file naming is as follows: "AFM_cellline_treatment_FOV_Youngmodulus.tif" for Young modulus and "AFM_cellline_treatment_FOV_setpointheight.tif" for setpoint height. The data are filtered 32-bit tiff images, where the pixel value correspond to cell stiffness (young modulus) in Pa or setpoint height in m.

Confocal microscopy analysis files

Following files are csv tables including image analysis of actin/tubulin staining captured by confocal microscope:

Cytoskeleton_fluo_analysis_Cell_Cell_periphery_morphology.csv: table includes analyzed data for actin and tubulin staining in following cellular regions: cell, cell periphery. Standard ImageJ parameters regarding intensity and morphology included.

Cytoskeleton_fluo_analysis_Fibers.csv: table includes results of manual segmentation and consequent analysis of actin stres fibers in the cells. Apart from standard ImageJ parameters, also number of stress fibers per cell and standard deviation of fiber angle relative to the cell mean angle (for details see methods) are included.

This repository contains data relevant to India's annual natural resource (coal, oil, natural gas, minerals and forests) rents from 1971 to 2021 curated and estimated using several World Bank datasets. To understand how I estimated all values in the dataset, you can look at this spreadsheet.

You can also find all datasets on Github.

Datasets

1. Total natural resource rents: TOTAL_NATURAL_RESOURCE_RENTS.csv
2. Fossil-fuel (coal, oil and natural gas) rents: FOSSIL_FUEL_RENTS.csv
3. Coal rents: COAL_RENTS.csv
4. Oil rents: OIL_RENTS.csv
5. Natural gas rents: NATURAL_GAS_RENTS.csv
6. Mineral rents: MINERAL_RENTS.csv
7. Forest rents: FOREST_RENTS.csv

Definitions

Rent or Resource rent

Sale price minus costs (provided costs include a "reasonable" return on capital employed).

Mineral rents

The resource rents from mining copper, gold, iron ore, lead, nickle, silve, and zinc according to World Bank's "The Changing Wealth of Nations 2021: Managing Assets for the Future" report but resource rents from mining tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate according to the page on their website where the data has been taken from. Hence, MINERAL_RENTS.csv is the only dataset where there is some confusion; for the rest, World Bank's publications are consistent.

Sample visualizations

Some sample visualizations of the data in all datasets have been included in this notebook.

Sources

1. Total natural resource rents (as % of GDP): World Bank
2. Coal rents (as % of GDP): World Bank
3. Oil rents (as % of GDP): World Bank
4. Natural gas rents (as % of GDP): World Bank
5. Mineral rents (as % of GDP): World Bank
6. Forest rents (as % of GDP): World Bank
7. GDP (current USD): World Bank
8. Official exchange rate (INR per USD): World Bank
9. Population: World Bank
10. Inflation, consumer prices (annual %): World Bank

World Bank on the sources they used to estimate the rents in their report, "The Changing Wealth of Nations 2021: Managing Assets for the Future" (TABLE A.6 contains the revelant text):

https://github.com/vinamrsachdeva/minerals/blob/main/wb_sources.png

The effects of the current rate used during the first charging (pre-charging: so-called “formation”) on the cathodic deposition of metallic zinc (Zn) were analyzed for the high capacity (thick) zinc oxide (ZnO) electrode in rechargeable Zn-based batteries. Pre-charging at a lower current rate (1.875 mA cm−2) enabled greater electrode performances for the subsequent charge-discharge cycles. The Zn deposition profiles were investigated by conventional postmortem X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy using a scanning electron microscope, as well as in situ synchrotron XRD and ex situ synchrotron X-ray computed tomography. The results revealed significant differences in the deposition profiles of the metallic Zn depending on the current rates used during pre-charging. The higher rate (18.75 mA cm−2) resulted in an inhomogeneous deposition of Zn, whereas the lower rate yielded finer Zn particles dispersed homogeneously throughout the thick ZnO electrode. These morphological and spatial variations in the Zn deposition during pre-charging affected the subsequent cycling behavior of the thick ZnO electrode.

Lead fell to 1,894 USD/T on March 27, 2026, down 0.19% from the previous day. Over the past month, Lead's price has fallen 3.63%, and is down 6.61% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lead - values, historical data, forecasts and news - updated on March of 2026.

Zinc electrodeposition is an economical process of Zn coating compared to conventional galvanic process. The galvanizing process is used in various industrial sectors to protect ferrous alloys during the corrosion process. In buildings, the galvanizing process is widely used to coat mortar protective screens. The electrodeposition of zinc has a relatively low cost compared to other coating materials for the same purpose; however, its corrosion resistance is lower than that of most protective deposits. This study evaluated the effect of adding glycerol to the electrodeposition bath on the corrosion resistance, deposition efficiency, morphology and microstructure of the zinc electrodeposit in concentrations ranging from 0.03 to 0.82 M. The electrodeposition was performed on carbon steel AISI 1020 with a current density of 10 mA.cm-2. The electroplating solution composition was 0.10 M ZnCl2, 2.80 M KCl and 0.32 M H3BO3. Electrodeposition time was 17.56 min, 5 µm thick coating, equivalent to the mass of 7.166E-3 g of zinc on the steel surface. Evaluation of the corrosion resistance was performed by means of the electrochemical tests of Anodic Voltammetry, Potentiodynamic Polarization and Electrochemical Impedance Spectroscopy (EIS) as well as Weight Loss tests in NaCl 0.5 M in 4 (four) different period of immersion. The morphology and microstructures of electrodeposited were analyzed using the techniques of Scanning Electron Microscopy (SEM) and Spectrometry X-Ray Diffraction (XRD). The presence of glycerol in the electrodeposition bath decreased the deposition efficiency; however, it increased corrosion resistance and promoted the formation of more compact and refined electrodeposited coatings. Moreover, the results showed that the corrosion rate does not vary linearly with the addition of glycerol.

Indonesia Average Rural Consumer Price: Zinc Plate: DI Yogyakarta data was reported at 36,534.000 IDR/m in Dec 2018. This records an increase from the previous number of 36,218.000 IDR/m for Nov 2018. Indonesia Average Rural Consumer Price: Zinc Plate: DI Yogyakarta data is updated monthly, averaging 37,292.000 IDR/m from Jan 2008 (Median) to Dec 2018, with 132 observations. The data reached an all-time high of 40,322.000 IDR/m in Jan 2015 and a record low of 30,350.000 IDR/m in Jan 2008. Indonesia Average Rural Consumer Price: Zinc Plate: DI Yogyakarta data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Prices – Table ID.PE073: Average Rural Consumer Price: By Province: Housing Product: Zinc Plate.

This database compiles a globally representative, meta-analysis–ready collection of rice biofortification experiments, capturing comprehensive plot-level information spanning environmental, genetic, agronomic, nutritional, and economic dimensions. It integrates detailed geographic and biophysical metadata (country, GPS coordinates, climate classification, aridity index, elevation, seasonal rainfall, long-term temperature and precipitation profiles), as well as full soil physicochemical characterization including pH, texture, organic carbon, macro- and micronutrient availability (N, P, K, Zn, Fe, etc.), cation exchange capacity, bulk density, and soil fertility status. For each trial entry, the dataset documents rice genetic background (species, subspecies, ecotype, cultivar name, variety type, origin, release year), crop establishment method, management practices (irrigation regime, tillage, residue recycling, farmyard manure use, inoculation), and full experimental treatment metadata — including nutrient application rates and forms (soil or foliar), growth-stage–specific timing, input economics, and treatment replication structures. The dataset further provides standardized agronomic outcomes such as total aboveground biomass, grain yield at 14% moisture, harvest index, nutrient-use efficiency (AEN, AEZn), and economic indicators (benefit–cost ratio). Critically, it includes high-resolution grain nutritional quality data, covering zinc, iron, protein, nitrogen, phytate, starch, oil, and a wide suite of mineral micronutrients (Ca, Mg, Se, B, Mn, Cu, Mo, Cd, As, Pb, Ni), along with associated uptake values and bioavailability-relevant molar ratios (e.g., phytate:Zn, phytate:Fe).

Aqueous zinc-ion batteries have emerged as promising candidates for safe and cost-effective energy storage, yet their performance remains constrained by electrode stability and electrolyte composition. In this study, we investigate the electrochemical behavior of various electrode materials in utilizing water-in-salt dual-ion electrolytes. Our findings highlight the critical influence of substrate materials on electrochemical stability, with titanium exhibiting superior anodic stability compared to, e.g., aluminum. Furthermore, we demonstrate the feasibility of LiFePO4 as a positive electrode, revealing a redox potential of 1.17 V vs. Zn²⁺/Zn in chloride-based electrolyte, which shifts positively with increasing lithium concentration. The observed potential variation with electrolyte composition underscores the need for optimized formulations to enhance the battery performance. Additionally, while LiMnPO4 offers a higher theoretical voltage, its cycling stability remains limited, suggesting that material modifications are necessary. Finally, we highlight the overlooked impact of electrolyte impurities on battery performance, emphasizing the importance of high-purity electrolyte components. These insights contribute to the development of more stable and efficient Zn-ion batteries, paving the way for their practical deployment in energy storage applications.