Archaeology / Ceramic Thin-Section Petrography
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LABORATORY 08 · ARCHAEOLOGY

Ceramic Thin-Section Petrography lab report

A worked ceramic thin-section petrography lab report with sample observation tables, regression plots, calculations, and error analysis.

WORKED EXAMPLE · BENCHMARK OBSERVATIONS

A complete example archaeology laboratory report.

Simulated demonstration data.

This report illustrates formal archaeological data reduction, instrument calibration tares, and parameter estimation. Replace its observations with your own experimental telemetry when preparing an archaeology laboratory report submission.

Student: __________________Student ID: __________________Course: __________________Date: __________________Partner: __________________Instructor: __________________

1. Title and aim

Ceramic Petrography: Thin-Section Optical Mineralogy & Temper Volume. Identify mineral inclusions, paste matrix fabric, and volcanic/sand temper volumetric percentage in archaeological sherds using point-counting polarized microscopy.

2. Abstract

Laboratory evaluation of Ceramic Petrography: Thin-Section Optical Mineralogy & Temper Volume was conducted across six calibrated setpoints under standard laboratory conditions. Measured empirical telemetry was reduced and linearized, yielding an ordinary least-squares correlation coefficient R² = 1.000000. The experimental parameter Petrographic Modal Temper Factor was estimated as 0.7500 %/(grain/100), comparing against the standard reference benchmark of 0.7500 %/(grain/100) with a relative percentage deviation of 0.0000%.

3. Apparatus and fixed settings

4. Theory and graph choice

Identify mineral inclusions, paste matrix fabric, and volcanic/sand temper volumetric percentage in archaeological sherds using point-counting polarized microscopy.

V_v = 0.7500 · N

Plotting Point-counted mineral inclusions N (grains/100) on the horizontal abscissa against Temper volumetric area fraction V_v (%) on the vertical ordinate demonstrates the linear governing response predicted by Ceramic Thin-Section Petrography archaeometric formulations.

5. Method

  1. Inspect all optical, electrical, and radiometric sensors. Verify instrument calibration against certified reference materials and perform electronic zero tare.
  2. Clean, dry, or prepare the archaeological sample according to standardized micro-analytical protocols to eliminate modern surface contamination.
  3. Mount the specimen securely within the sensor housing or establish spatial grid coordinates. Verify alignment of the point-counted inclusions with primary excavation datum.
  4. Increment the point-counted inclusions systematically across the designated domain (8.0 to 38.0 grains/100), permitting full signal equilibration at each measurement station.
  5. Record the primary dependent variable (Temper Volumetric Area Fraction V_v) alongside auxiliary environmental monitors. Validate signal stability and confirm low noise thresholds.
  6. Cycle the sensor through a verification standard to confirm zero baseline drift, de-energize primary drives, and export all digital telemetry observations to the persistent laboratory database.

6. Observations and calculation table

All archaeological observations use strictly controlled 64-bit IEEE 754 precision buffers under conditioned equilibrium. Residuals are computed relative to the ordinary least-squares regression line.

Table 1. Six simulated observations; x and y represent transformed archaeological metrics.
No.Point-Counted Mineral Inclusions Count N (grains/100)Temper Volumetric Area Fraction V_v (%)Point-counted mineral inclusions N (grains/100)Temper volumetric area fraction V_v (%)Fitted yResidual
18.06.08.00006.00006.00000.0000
214.010.514.000010.500010.50000.0000
320.015.020.000015.000015.00000.0000
426.019.526.000019.500019.50000.0000
532.024.032.000024.000024.00000.0000
638.028.538.000028.500028.50000.0000

Download the sample observations (CSV) ↓

7. Worked calculation for one observation

x = 8.0000; y = 6.0000; fitted_y = 0.7500 · x + 0.0000 = 6.0000

8. Graph, gradient and final calculation

6.504.8813.109.8219.7014.7826.3019.7332.9024.6839.5029.62Point-counted mineral inclusions N (grains/100)Temper volumetric area fraction V_v (%)

Circular markers represent empirical observations. The solid line represents the ordinary least-squares linear fit.

x̄ = 23.0000; ȳ = 17.2500
Σ(x − x̄)² = 630.0000
Σ(x − x̄)(y − ȳ) = 472.5000
m = Σ(x − x̄)(y − ȳ) / Σ(x − x̄)² = 0.75000000
b = ȳ − mx̄ = 0.00000000
Petrographic Modal Temper Factor = 0.75000 %/(grain/100)

9. Uncertainty and comparison

Percentage difference = |estimate − theoretical value| / |theoretical value| × 100 = 0.0000%.

For n = 6 observations, Σresidual² = 0.0000; s² = Σresidual²/(n − 2). Gradient standard error = √[s²/Σ(x − x̄)²] = 0.0000. Intercept standard error = √[s²(1/n + x̄²/Σ(x − x̄)²)] = 0.0000.

Propagating the fit parameters yields a fit standard error of 0.0000 %/(grain/100), with an ideal coefficient of determination R² = 1.000000.

Instrumental and regression uncertainty for Ceramic Thin-Section Petrography is constrained within 0.02% of certified calibration reference materials.

10. Result and discussion

Petrographic Modal Temper Factor = 0.7500 %/(grain/100)
Theoretical reference value: 0.7500 %/(grain/100)

Experimental observations across all six trials demonstrate rigorous agreement with governing analytical models. OLS linear regression yielded slope m = 0.750000 and intercept b = 0.000000, validating the governing equation V_v = 0.7500 · N with R² = 1.000000.

11. Precautions and limitations

Archaeometric interpretations assume verified conservation standards and absence of modern contamination. Diagenetic weathering models apply within verified geological limits.

12. Conclusion

The experimental determination of Ceramic Petrography: Thin-Section Optical Mineralogy & Temper Volume confirmed the analytical model within an experimental uncertainty of 0.0000%. Standardized calibration protocols ensure high laboratory repeatability.

In-Depth Technical Supplement & Archaeological Science Derivation

1. Title and Objective

Ceramic Petrography: Thin-Section Optical Mineralogy & Temper Volume. Identify mineral inclusions, paste matrix fabric, and volcanic/sand temper volumetric percentage in archaeological sherds using point-counting polarized microscopy. This formal laboratory report documents experimental data acquisition, mathematical model calibration, regression analysis, error propagation, and physical parameter extraction for ceramic thin-section petrography.

2. Abstract

An experimental investigation of ceramic thin-section petrography was conducted using precision archaeometric instrumentation across six systematic setpoints of point-counted inclusions ranging from 8.0 to 38.0 grains/100. All archaeological specimens were prepared, cleaned, and conditioned under controlled laboratory environments prior to evaluation. Measured temper volumetric area fraction v_v data were logged using calibrated digital transducers, multi-channel telemetry systems, and optical sensors. Ordinary least-squares regression yielded an empirical calibration line of V_v = 0.7500 · N with a coefficient of determination R² = 1.000000. The derived experimental parameter Petrographic Modal Temper Factor was evaluated as 0.75 %/(grain/100), demonstrating complete agreement with theoretical benchmark expectations within 0.02% experimental error.

3. Experimental Apparatus & Standard Settings

  • Ceramic Thin-Section Petrography Workstation & Field Sensor Rig: Provides rigid calibrated mounting, standardized environmental control, and precise positioning for delesse principle (v_v = a_a), birefringence, quartz/feldspar extinction & fabric groupings.
  • Calibrated Digital Archaeometric Transducer & Sensor Head: Quantifies physical, chemical, or optical responses with high baseline sensitivity and ±0.05% measurement accuracy.
  • Multi-Channel Digital Telemetry Data Logger (Class 0.2): Samples resistance, potential, magnetic flux, optical absorbance, and temperature at 1 kHz with 24-bit resolution.
  • Precision Specimen Preparation & Thin-Section Polishing Rig: Prepares microscopic petrographic sections, resin-embedded blocks, or powder samples under controlled thickness (30 μm).
  • Certified Archaeological & Geological Reference Standards Set: Provides verified isotopic, elemental, or dimensional benchmarks before establishing point-counted inclusions setpoints.
  • Grounded Shielded Instrumentation Leads & Environmental Enclosure: Eliminates stray electromagnetic interference, electrostatic charge drift, and thermal fluctuations in field laboratories.
  • Environmental Ambient Conditions: Ambient laboratory temperature 20.0 ± 0.5 °C; relative humidity 50.0 ± 2.0%; atmospheric pressure 101.325 kPa.
  • Pre-Treatment & Cleaning Protocol: Certified solvent cleaning and ultrasonic bath decontamination applied to isolate authentic endogenous signals.

4. Theory & Graphical Coordinate Selection

According to the governing principles of ceramic thin-section petrography, the physical archaeometric response follows the linear transformation:

V_v = 0.7500 · N

To evaluate the intrinsic physical parameter (Petrographic Modal Temper Factor), the experimental data are plotted with Point-counted mineral inclusions N (grains/100) on the horizontal abscissa and Temper volumetric area fraction V_v (%) on the vertical ordinate. The gradient of the resulting least-squares linear line directly yields the parameter magnitude.

5. Step-by-Step Experimental Method

  1. Apparatus Calibration & Baseline Standard Verification: Inspect all optical, electrical, and radiometric sensors. Verify instrument calibration against certified reference materials and perform electronic zero tare.
  2. Specimen Conditioning & Matrix Preparation: Clean, dry, or prepare the archaeological sample according to standardized micro-analytical protocols to eliminate modern surface contamination.
  3. Sensor Alignment & Baseline Datum Acquisition: Mount the specimen securely within the sensor housing or establish spatial grid coordinates. Verify alignment of the point-counted inclusions with primary excavation datum.
  4. Systematic Parameter Variation & Acquisition: Increment the point-counted inclusions systematically across the designated domain (8.0 to 38.0 grains/100), permitting full signal equilibration at each measurement station.
  5. Multi-Channel Telemetry Recording & Signal Integration: Record the primary dependent variable (Temper Volumetric Area Fraction V_v) alongside auxiliary environmental monitors. Validate signal stability and confirm low noise thresholds.
  6. Post-Test Verification & Digital Archive Export: Cycle the sensor through a verification standard to confirm zero baseline drift, de-energize primary drives, and export all digital telemetry observations to the persistent laboratory database.

6. Raw Experimental Observations & Data Tabulation

All experimental observations were recorded under steady-state thermal and mechanical equilibrium. The table below summarizes the recorded telemetry across the experimental domain.

Table 1. Experimental observation telemetry for Ceramic Thin-Section Petrography.
Trial # Point-Counted Mineral Inclusions Count N (grains/100) Temper Volumetric Area Fraction V_v (%) Transformed x Transformed y Residual
18.08.08.00008.0000.000
214.014.014.000014.0000.000
320.020.020.000020.0000.000
426.026.026.000026.0000.000
532.032.032.000032.0000.000
638.038.038.000038.0000.000

7. Worked Calculation for Representative Observation

For Trial 3 (Point-Counted Inclusions = 20.0 grains/100):

x_3 = 20.0 grains/100
y_3 = 0.7500 · (20.0) = 20.0 %

The calculated point aligns precisely with the least-squares regression line, demonstrating excellent instrument linearity.

8. Telemetric Graphical Representation

The scatter plot displays measured Temper Volumetric Area Fraction V_v against Point-Counted Inclusions. The empirical slope directly yields Petrographic Modal Temper Factor = 0.75 %/(grain/100) with R² = 1.000000.

9. Ordinary Least-Squares (OLS) Regression Analysis

Linear regression parameters were calculated using standard formulas:

m = \frac{N \sum xy - \sum x \sum y}{N \sum x^2 - (\sum x)^2} = 0.7500
R^2 = 1.000000

The coefficient of determination confirms an optimal linear model without systematic curvature across the test range.

10. Sources of Experimental Uncertainty & Error Propagation

Potential sources of uncertainty include sample inhomogeneity, micro-taphonomic weathering, baseline instrument drift, and ambient temperature fluctuations. Standard error of the regression slope is less than 0.0001, verifying high precision.

11. Discussion of Anthropological & Archaeological Significance

The validated empirical relationship directly reinforces core archaeological theory. By confirming Petrographic Modal Temper Factor = 0.75 %/(grain/100), researchers can reliably interpret stratigraphic chronology, sourcing patterns, and cultural behaviors from physical material evidence.

12. Conclusions & Methodological Recommendations

The experiment successfully established the quantitative validity of Ceramic Petrography: Thin-Section Optical Mineralogy & Temper Volume. For future field investigations, incorporating multi-element geostatistical mapping and high-resolution micro-CT scanning is recommended.

Simulated demonstration data.