Percentage extraction is calculated by dividing the mass of Ni in the leachate by the total Ni mass in the ore and multiplying by 100. A result over 100% indicates measurement errors or contamination, as extracting more Ni than originally present is not physically possible.

It is better to use ICP, but AAS results may also be acceptable. XRF results are not acceptable. You can use the following formulae:

LE (%) = [Mass of Ni in leachate (g) / Mass of Ni in initial ore (g)] * 100

where Mass of Ni in leachate (g) =

[Ni in leachate (ppm) * Vol of leachate (L)] / 1000

and Mass of Ni in initial ore (g) =

[Ni in ore (ppm) * Mass of ore used for leaching (g)] / 10^6

you can deploy Copilot to help you.

When you're trying to calculate the nickel extraction percentage from leaching ore, you're essentially measuring how much nickel was successfully pulled from the ore into solution. To do that, you compare the amount of nickel found in the leaching solution with the amount originally present in the ore sample. Using the numbers from your experiment:

🧾 Provided Data

• Initial nickel content in ore: 1.84% (from XRF)
• Ore sample weight: 150 g
• Nickel in solution: 4791.9 ppm (from AAS)
• Volume of leaching reagent: 1500 mL or 1.5 L

🧮 Step-by-Step Breakdown

❗ Why Is the Result Over 100%?

An extraction percentage over 100% is scientifically not possible under normal conditions—it means you recovered more nickel than was originally present in the ore, which suggests something’s off. Possible explanations:

• Measurement Error: The ore’s nickel content may have been underestimated by XRF or the leachate’s nickel concentration overestimated by AAS.
• Sample Inconsistency: Your ore sample might not have been well-mixed, leading to unrepresentative analysis.
• Contamination: Nickel might have leached from tools, containers, or even reagents.
• Volume Miscalculation: The actual volume of leaching solution may have changed due to evaporation or dilution.

🔧 How to Fix or Refine Your Process

To improve accuracy:

• Use multiple analysis methods (e.g., ICP-OES or acid digestion followed by AAS to cross-verify the actual Ni content in the ore) to confirm ore nickel content.
• Calibrate instruments properly and include blanks and standards.
• Homogenize ore samples to avoid bias. Crush and homogenize ore thoroughly before sampling to avoid biased analysis.
• Use dry weight correction if the sample is moist or contains volatile components.
• Ensure precise volume measurements—consider sealed containers to prevent evaporation.
• Perform spike recovery and matrix matching in AAS to reduce interference.

In short: The math checks out, but the result signals a need for better control and verification in the experimental setup.

🧠 Advanced Tips

• For more precise quantification, consider using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) if available.
• Track the mass balance across solid and liquid phases to detect hidden losses or gains.
• Apply statistical analysis to replicate runs for error margins and reliability.

:

🧪 Improve Accuracy of Measurements

🔹 XRF for Initial Ni Content

• Calibrate the XRF instrument using certified nickel standards to avoid underestimation.
• Perform replicate measurements on multiple ore subsamples to account for inhomogeneity.
• Use complementary techniques like ICP-OES or acid digestion followed by AAS to cross-verify the actual Ni content in the ore.

🔹 AAS for Ni in Solution

• Ensure proper standard curve preparation and matrix matching to reduce signal interference.
• Dilute the leachate sample if it's too concentrated; AAS can lose accuracy at high ppm levels.
• Perform blank and spike recovery tests to check for contamination or adsorption loss.

📈 Data Validation

🔹 Check Calculation Assumptions

• Double-check unit conversions (ppm to mg/L, g to mg).
• Consider adsorption losses or precipitation in the solution—some Ni might not stay dissolved.

🔹 Run Controls

• Include negative controls (no ore) and positive controls (known Ni content) to monitor procedural integrity.
• Repeat experiments with different reagent volumes or concentrations to test robustness.

Applying statistical analysis to replicate leaching runs is a smart way to assess the reliability of your results and quantify uncertainty. Here's how you can do it step-by-step:

📈 1. Perform Replicate Runs

• Repeat your leaching experiment at least 3–5 times using identical conditions.
• Record the nickel extraction percentage from each run.

Example: Run 1: 245% Run 2: 258% Run 3: 260% Run 4: 253% Run 5: 264%

📉 2. Calculate Descriptive Statistics

:

📊 Descriptive Statistics (Inline Style)

• Mean = (Sum of extraction percentages) ÷ (Number of runs)  Example: Mean = (245 + 258 + 260 + 253 + 264) ÷ 5 = 256
• Standard Deviation (SD) = Square root of [(sum of each value minus mean, squared) ÷ (n - 1)]
• Coefficient of Variation (CV) = (Standard deviation ÷ Mean) × 100  This helps express variability relative to the mean.

🎯 Confidence Interval (CI)

• CI = Mean ± (t-value × SD ÷ square root of n)  This gives a margin around the mean where the true value likely falls.

🧪 Nickel Extraction Formulas (Inline Style)

• Mass of Ni in leachate (g) = (Ni concentration in ppm × volume in liters) ÷ 1000
• Mass of Ni in ore (g) = (Ni percentage ÷ 100) × ore weight in grams
• Extraction Efficiency (%) = (Ni in leachate ÷ Ni in ore) × 100

For a 95% confidence level, use appropriate tt-value based on degrees of freedom (n−1n - 1).

🧪 4. Perform ANOVA (if comparing methods)

If you use multiple measurement techniques (e.g., XRF vs. ICP-OES), Analysis of Variance (ANOVA) helps determine if differences in results are statistically significant.

📊 5. Visualize the Data

• Use box plots to show spread and outliers.
• Create error bars on bar charts for the mean ± SD or CI.
• Scatter plots can reveal trends and inconsistencies across conditions.

✅ Benefits

• Identifies outliers and abnormal runs
• Quantifies measurement reliability
• Strengthens conclusions in research reports or publications

• Good luck