Aluminum fell to 2,649.55 USD/T on July 23, 2025, down 0.29% from the previous day. Over the past month, Aluminum's price has risen 2.86%, and is up 15.17% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Aluminum - values, historical data, forecasts and news - updated on July of 2025.

This dataset provides values for ALUMINUM reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Real-time aluminum futures prices from major exchanges with price changes and trends

Real-time aluminum spot prices from major Chinese markets with price changes and trends

This time I deided to pay attention on the changes in metal prices within last 30 year. The most popular and interesting in visualization metals prices were tacken: Gold, Aluminium, Silver, Uranium and Nickel Don't forget to check out my previous "Price Changes within last 30 Years" datasets: 🌽 Cerial Prices Changes Within Last 30 Years ☕Coffee, Rice and Beef Prices Changes for 30 Years

Russia Average World Price: Aluminium data was reported at 2,299.700 USD/Ton in May 2018. This records an increase from the previous number of 2,254.700 USD/Ton for Apr 2018. Russia Average World Price: Aluminium data is updated monthly, averaging 1,816.800 USD/Ton from Jun 2000 (Median) to May 2018, with 180 observations. The data reached an all-time high of 2,852.000 USD/Ton in May 2006 and a record low of 1,283.900 USD/Ton in Oct 2001. Russia Average World Price: Aluminium data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Prices – Table RU.PC002: Average World Prices, Crude Oil Export Price, Crude Oil Export Duty.

Russia Average Import Price: Aluminium Ore & Ore Concentrates data was reported at 344.000 USD/Ton in 2017. This records an increase from the previous number of 140.000 USD/Ton for 2016. Russia Average Import Price: Aluminium Ore & Ore Concentrates data is updated yearly, averaging 161.000 USD/Ton from Dec 1999 (Median) to 2017, with 19 observations. The data reached an all-time high of 438.000 USD/Ton in 2009 and a record low of 40.000 USD/Ton in 2002. Russia Average Import Price: Aluminium Ore & Ore Concentrates data remains active status in CEIC and is reported by Federal Customs Service. The data is categorized under Russia Premium Database’s Prices – Table RU.PC007: Average Import Price: Annual.

Comprehensive aluminum spot price dataset from Zhongyuan market including real-time pricing, daily changes, and percentage fluctuations for aluminum ingot trading in China's spot market

Comprehensive aluminum futures price dataset from LME exchange including real-time contract pricing, daily settlement changes, and percentage fluctuations for aluminum futures trading with detailed market analysis and trend indicators

Prices for 4 basic commodities for industry: Brent crude oil, natural gas, aluminum, and DJUSST (Iron & Steel); monthly data from Jan. 2010, a weighted sum of daily data from Yahoo Finance.

About This Dataset: Copper Prices and Market Trends

    This dataset provides **insights into copper prices**, including current rates, historical trends, and key factors affecting price fluctuations. Copper is essential in **construction**, **electronics**, and **transportation** industries. Investors, traders, and analysts use accurate copper price data to guide decisions related to **trading**, **futures**, and **commodity investments**.

    ### **Key Features of the Dataset**

    #### **Live Market Data and Updates**
    Stay updated with the latest **copper price per pound** in USD. This data is sourced from exchanges like the **London Metal Exchange (LME)** and **COMEX**. Price fluctuations result from **global supply-demand shifts**, currency changes, and geopolitical factors.

    #### **Interactive Copper Price Charts**
    Explore **dynamic charts** showcasing real-time and historical price movements. These compare copper with **gold**, **silver**, and **aluminium**, offering insights into **market trends** and inter-metal correlations.

    ### **Factors Driving Copper Prices**

    #### **1. Supply and Demand Dynamics**
    Global copper supply is driven by mining activities in regions like **Peru**, **China**, and the **United States**. Disruptions in production or policy changes can cause **supply shocks**. On the demand side, **industrial growth** in countries like **India** and **China** sustains demand for copper.

    #### **2. Economic and Industry Trends**
    Copper prices often reflect **economic trends**. The push for **renewable energy** and **electric vehicles** has boosted long-term demand. Conversely, economic downturns and **inflation** can reduce demand, lowering prices.

    #### **3. Impact of Currency and Trade Policies**
    As a globally traded commodity, copper prices are influenced by **currency fluctuations** and **tariff policies**. A strong **US dollar** typically suppresses copper prices by increasing costs for international buyers. Trade tensions can also disrupt **commodity markets**.

    ### **Applications and Benefits**

    This dataset supports **commodity investors**, **traders**, and **industry professionals**:

    - **Investors** forecast price trends and manage **investment risks**. 
    - **Analysts** perform **market research** using price data to assess **copper futures**. 
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    - [**Copper Buffalo Rounds**](https://www.moneymetals.com/copper-buffalo-round-1-avdp-oz-999-pure-copper/297)

    ### **Copper Price Comparisons with Other Metals**

    Copper prices often correlate with those of **industrial** and **precious metals**:

    - **Gold** and **silver** are sensitive to **inflation** and currency shifts. 
    - **Iron ore** and **aluminium** reflect changes in **global demand** within construction and manufacturing sectors.

    These correlations help traders develop **hedging strategies** and **investment models**.

    ### **Data Variables and Availability**

    Key metrics include:

    - **Copper Price Per Pound:** The current market price in USD. 
    - **Copper Futures Price:** Data from **COMEX** futures contracts. 
    - **Historical Price Trends:** Long-term movements, updated regularly. 

    Data is available in **CSV** and **JSON** formats, enabling integration with analytical tools and platforms.

    ### **Conclusion**

    Copper price data is crucial for **monitoring global commodity markets**. From **mining** to **investment strategies**, copper impacts industries worldwide. Reliable data supports **risk management**, **planning**, and **economic forecasting**.

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Graph and download economic data for Global price of Aluminum (PALUMUSDQ) from Q1 1990 to Q2 2025 about aluminum, World, and price.

Comprehensive aluminum spot price dataset from Nanhai market including real-time pricing, daily changes, and percentage fluctuations for aluminum ingot trading in China's spot market

Metal Industry Indicators (MII) is a monthly newsletter that analyzes and forecasts the economic health of five metal-processing industries: primary metals, steel, copper, primary and secondary aluminum, and aluminum mill products. The MII presents composite leading and coincident indexes of a set of indicators that historically have proven to lead or coincide with the major business cycle changes in these industries. The indexes were developed in cooperation with the Center for International Business Cycle Research at Columbia University. Each month, these indexes are analyzed along with any economy-wide occurrences that would affect the metals industries. Stone, Clay, Glass, and Concrete Products Industry Indicators (IMII) is a monthly newsletter that analyzes and forecasts the economic health of four industrial-mineral-processing industries: stone, clay, glass, and concrete products. The IMII presents composite leading and coincident indexes of a set of indicators that historically have proven to lead or coincide with the major business cycle changes in these industries. The indexes were developed cooperation with the Center for International Business Cycle Research at Columbia University. Each month, these indexes are analyzed along with any economy-wide occurrences that would affect the industrial minerals industries.

Comprehensive aluminum futures price dataset from SHFE exchange including real-time contract pricing, daily settlement changes, and percentage fluctuations for aluminum futures trading with detailed market analysis and trend indicators

LME Index rose to 4,269.90 Index Points on July 22, 2025, up 0.51% from the previous day. Over the past month, LME Index's price has risen 2.72%, and is up 9.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. LME Index - values, historical data, forecasts and news - updated on July of 2025.

This dataset contains raw mechanical data (strain, stress and strain rate curves and initial temperatures) for compression experiments performed on aluminum alloy 6061-T6 using the NIST pulse-heated Kolsky Bar at strain rates between 2400 1/s and 2700 1/s and initial temperatures from 23 °C to 527 °C and heating times ranging between 0.2 s and 3.5 s. At this time, the thermal history of the specimen during heating is not included in the dataset but this information may be included in a future update. The pulse-heated Kolsky bar method is described in reference [1]. Additional information regarding the temperature measurement methods specific to aluminum are found in reference [2] as well as a supplementary included in this data publication [3]. This dataset includes measurements of right-circular cylindrical samples measuring 6 mm diameter by 3 mm thick, fabricated by conventional machining. The effect of the surface condition on the thermographic temperature measurements and the temperature uncertainty calculations are described in reference [3], which is included in this dataset as metadata. [1] Mates, S.P., et al., A Pulse-Heated Kolsky Bar Technique for Measuring the Flow Stress of Metals at High Loading and Heating Rates. Experimental Mechanics, 2008. 48(6): p. 799-807. https://dx.doi.org/10.1007/s11340-008-9137-1 [2] Lopez-Hawa, H., et al., On the Mechanical Response of Aluminum Alloy 6061-T6 under Extreme Strains and Strain Rates, and Rapid Heating. Manufacturing Letters, 2022. 33: p. 292-301. https://dx.doi.org/10.1016/j.mfglet.2022.07.036 [3] Aluminum_insitu_calibration.docx (included in this dataset)

Daily updated dataset showing Hindalco aluminium price movements including upgrade, down, and stable statuses with historical tracking in HTML table format.

No description is available. Visit https://dataone.org/datasets/2b4cb5f363163b0330a31fa5371fbc8a for complete metadata about this dataset.

'Emission dynamics of optically driven aluminum nitride quantum emitters' dataThe dataset includes Excel files with the raw data for each figure in the manuscript. The filename of the files points towards each labelled subplot in each figure and the necessary description.Figure 1 is the characterization of two quantum emitters in AlN at room temperature. (a) is the spectrum for QE A.(b) is the photon emission correlation spectrum (PECS), normalised, without background correction for QE A.(c) is the continuous wave photoluminescence (CW-PL) saturation behaviour for QE A.(d) shows the excited state lifetime measurement for QE A.(e) is the spectrum for QE B(f) is the photon emission correlation histogram, normalised, without background correction for QE B.(g) is the CW-PL saturation behavior for QE B.(h) shows the excited state lifetime measurement for QE B.Figure 2 is photon emission correlation spectroscopy on a long-time scale.(a) includes the QE A's PECS raw data and its fitting curves with different fitting parameters of N =2,3,4,5.(b) includes the QE B's PECS raw data and its fitting curves with different fitting parameters of N =2,3,4,5.(c) is the corresponding residuals from the fits to QE A.(d) is the corresponding residuals from the fits to QE B.Figure 3 is time-resolved PL (TRPL) under double-pulse laser excitation. (a) is the TRPL of QE A under double-pulse laser excitation.(b) is the TRPL of QE B under double-pulse laser excitation. (c) is the PL revival behaviour under the second pulse excitation in (a) fitted by single exponential and double exponential equations. (d) is the PL revival behaviour under the second pulse excitation in (b) fitted by single exponential and double exponential equations.Figure 4 is power-dependent PECS from QE A and QE B. (a) is power-dependent PECS for QE A.(b) is power-dependent PECS for QE B.(c) includes amplitudes C_i and rates r_i arising from fitting the equation for QE B.(d) includes amplitudes C_i and rates r_i arising from fitting the equation for QE B.Figure 5 is power-dependent TRPL with the square excitation pulse. (a) is power-dependent TRPL with square excitation pulse for QE A.(b) is power-dependent TRPL with square excitation pulse for QE B.(c) is the normalized PL saturation behaviours of the steady state for QE A. (d) is the normalized PL saturation behaviours of the steady state for QE B. (e) includes the TRPL decay rates observed in (a).(f) includes the TRPL decay rates observed in (b).Figure 6 is the state population dynamics simulation. The results in (c-f) are plotted as a function of a12=k_{12}/k_{21}, where k_{21}= 200 MHz is a fixed parameter as the spontaneous emission decay rate.(a) is PECS simulation results for shelving Model I.(b) is TRPL simulation results for shelving Model II.(c) is the best-fit parameter r_1 with fitting parameters of N =2.(d) is the best-fit parameter C_2 with fitting parameters of N =2.(e)is the best-fit parameter r_2 with fitting parameters of N =2. (f) is the steady state PL saturation behaviour.Figure S1 includes the absorption and emission polarization plots of QE A (a) and QE B (b). Figure S2 is a single NV centre (a) in diamond power-dependent saturation PL characterization compared with QE A (b) and QE B (c).Figure S3 is the state population dynamics simulation for Model III and Model IV. The results of (c-f) are plotted as a function of k_{12}/k_{21}, where k_{21}= 200 MHz is a fixed parameter.(a) includes PECS shelving simulation results for Model III and Model IV.(b) includes TRPL simulation results for shelving Model III and Model IV (c) is the best-fit parameter r_1 with fitting parameters of N =2.(d) is the best-fit parameter r_2 with fitting parameters of N =2.(e) is the best-fit parameter C_2 with fitting parameters of N =2. (f) is the steady state PL saturation behaviour.Research results based upon these data are published at https://doi.org/10.1103/PhysRevB.110.014109