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Research article · 2025 · Full text

International Journal of Advanced Chemistry Research

X-ray fluorescence spectroscopy for non-destructive analysis of archaeological artifacts

Lorenzo GalliRiccardo ContiPaolo GalliStefano Leone

Volume 7(11) · Pages 179–182 · DOI: 10.33545/26646781.2025.v7.i11c.464 ↗

Research areasCultural Heritage Materials AnalysisMetallurgy and Cultural ArtifactsX-ray Spectroscopy and Fluorescence Analysis

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Abstract

Author-written

A scratch on a 2,400-year-old bronze coin might seem trivial, but to a museum conservator it represents an irreversible loss of information which is precisely why non-destructive elemental analysis has become indispensable in archaeometry. This research applied portable X-ray fluorescence (pXRF) spectroscopy to characterise thirty-five archaeological artifacts (fifteen bronze coins, twelve bronze tools, and eight glazed pottery fragments) from Roman and pre-Roman Mediterranean contexts. Measurements were performed in air using a handheld Bruker Tracer 5g spectrometer with optimised beam parameters. Bronze coins showed Cu contents of 82.1–89.4 wt% with Sn at 6.3–12.1 wt% and Pb increasing from the Archaic (0.8%) to Roman (5.4%) period. Pottery glazes were dominated by Pb (42.7 wt%) and Sb (44.2 wt%). Accuracy was validated against certified reference materials (NIST SRM 1107 and BCR-691), yielding recoveries of 96.3–103.8% for major elements. Principal component analysis separated the three artifact categories into distinct clusters, and the Sn/Pb ratio proved a useful chronological marker for bronze coinage. These results confirm pXRF as a rapid, reliable, and truly non-destructive tool for archaeological provenance and dating research.

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • Chemical fingerprints in archaeological artifacts are valuable because they can reveal the object's origin, manufacture date, and associated trade networks. View evidence ↗

      Why it matters

      Chemical fingerprints in archaeological artifacts are valuable because they can reveal the object's origin, manufacture date, and associated trade networks.

      In the paper's own words

      “Archaeological artifacts carry chemical fingerprints that can reveal their origin, date of manufacture, and the trade networks through which they travelled”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Traditional elemental analysis methods are often unsuitable for unique or protected artifacts because they require the removal of material samples. View evidence ↗

      Why it matters

      Traditional elemental analysis methods are often unsuitable for unique or protected artifacts because they require the removal of material samples.

      In the paper's own words

      “traditional methods wet-chemical assays, atomic absorption, ICP-MS require sample removal, which is unacceptable for unique or legally protected objects”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • X-ray fluorescence (XRF) spectroscopy provides a solution by allowing the determination of surface elements without needing physical contact or causing material loss. View evidence ↗

      Why it matters

      X-ray fluorescence (XRF) spectroscopy provides a solution by allowing the determination of surface elements without needing physical contact or causing material loss.

      In the paper's own words

      “XRF spectroscopy solved this problem by enabling surface elemental determination without physical contact or material loss.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. The question

    • The study aimed to establish elemental profiles for artifacts, validate the accuracy of portable XRF (pXRF), and determine if compositional data could distinguish between artifact types and historical periods. View evidence ↗

      The question

      The study aimed to establish elemental profiles for artifacts, validate the accuracy of portable XRF (pXRF), and determine if compositional data could distinguish between artifact types and historical periods.

      In the paper's own words

      “The objectives were to establish elemental profiles, validate pXRF accuracy against certified reference materials, and test whether compositional data can distinguish artifact types and chronological periods through multivariate statistics”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  3. What they did

    • Elemental measurements were conducted using a Bruker Tracer 5g handheld XRF spectrometer equipped with a Rh anode and an SDD detector. View evidence ↗

      What they did

      Elemental measurements were conducted using a Bruker Tracer 5g handheld XRF spectrometer equipped with a Rh anode and an SDD detector.

      In the paper's own words

      “Measurements were performed with a Bruker Tracer 5g handheld XRF spectrometer (Rh anode, SDD detector, spot size 8 mm).”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • Analysis parameters differed by material: bronze artifacts were measured at 40 kV / 35 µA for 120 seconds with a Ti/Al filter, while pottery glazes were measured at 15 kV / 55 µA for 90 seconds without a filter. View evidence ↗

      What they did

      Analysis parameters differed by material: bronze artifacts were measured at 40 kV / 35 µA for 120 seconds with a Ti/Al filter, while pottery glazes were measured at 15 kV / 55 µA for 90 seconds without a filter.

      In the paper's own words

      “Bronze artifacts were analysed at 40 kV / 35 µA with a Ti/Al primary beam filter and 120 s live time. Pottery glazes used 15 kV / 55 µA without filter and 90 s.”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • Principal Component Analysis (PCA) was performed using PAST 4.03 software on centered log-ratio transformed data to manage compositional closure. View evidence ↗

      What they did

      Principal Component Analysis (PCA) was performed using PAST 4.03 software on centered log-ratio transformed data to manage compositional closure.

      In the paper's own words

      “PCA was performed using PAST 4.03 software on centred log-ratio transformed data to handle the compositional closure constraint.”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
  4. What they found

    • The pXRF system demonstrated high accuracy, with measured values for copper, tin, lead, and zinc agreeing with certified reference materials within 96.3–103.8%. View evidence ↗

      What they found

      The pXRF system demonstrated high accuracy, with measured values for copper, tin, lead, and zinc agreeing with certified reference materials within 96.3–103.8%.

      In the paper's own words

      “Measured values for Cu, Sn, Pb, and Zn agreed with certified values within 96.3–103.8%.”

      Page 2

      Found in: Performance evaluation

      Read it in the full textOpen PDF at page 2 ↗
    • While both bronze coins and tools had a copper-tin base, coins had a higher average lead content (3.2%) compared to tools (1.6%). View evidence ↗

      What they found

      While both bronze coins and tools had a copper-tin base, coins had a higher average lead content (3.2%) compared to tools (1.6%).

      In the paper's own words

      “Bronze coins and tools shared a Cu-Sn base but differed in Pb content coins averaged 3.2% Pb versus 1.6% for tools”

      Page 2

      Found in: Results

      Read it in the full textOpen PDF at page 2 ↗
    • Pottery glazes exhibited a distinct elemental profile dominated by lead (42.7 wt%) and antimony (44.2 wt%). View evidence ↗

      What they found

      Pottery glazes exhibited a distinct elemental profile dominated by lead (42.7 wt%) and antimony (44.2 wt%).

      In the paper's own words

      “Pottery glazes showed a completely different profile dominated by Pb and Sb.”

      Page 2

      “Pottery glazes were dominated by Pb (42.7 wt%) and Sb (44.2 wt%).”

      Page 1

      Found in: Results

      Read it in the full textOpen PDF at page 2 ↗
    • The tin-to-lead (Sn/Pb) ratio decreased from 9.0 in the Archaic period to 1.5 in the Roman period, serving as a useful marker for dating. View evidence ↗

      What they found

      The tin-to-lead (Sn/Pb) ratio decreased from 9.0 in the Archaic period to 1.5 in the Roman period, serving as a useful marker for dating.

      In the paper's own words

      “The Sn/Pb ratio declined from 9.0 in the Archaic to 1.5 in the Roman period, providing a useful compositional chronological marker.”

      Page 2

      Found in: Results

      Read it in the full textOpen PDF at page 2 ↗
    • PCA successfully separated the three artifact categories using the first two principal components, which explained 87.4% of the total variance. View evidence ↗

      What they found

      PCA successfully separated the three artifact categories using the first two principal components, which explained 87.4% of the total variance.

      In the paper's own words

      “PCA of the full dataset separated the three artifact categories along the first two principal components (explaining 87.4% of variance)”

      Page 3

      Found in: Comprehensive interpretation

      Read it in the full textOpen PDF at page 3 ↗
  5. What it means

    • The authors conclude that pXRF is a reliable, non-destructive tool and recommend its adoption as a primary analytical method for museum conservation and archaeological fieldwork. View evidence ↗

      What it means

      The authors conclude that pXRF is a reliable, non-destructive tool and recommend its adoption as a primary analytical method for museum conservation and archaeological fieldwork.

      In the paper's own words

      “These findings support the broader adoption of pXRF as a first-line analytical tool in museum conservation, archaeological fieldwork, and cultural heritage management.”

      Page 3

      Found in: Conclusion

      Read it in the full textOpen PDF at page 3 ↗
    • A limitation of pXRF is that surface corrosion (patina) can artificially inflate the measured concentrations of tin and lead by 1–3 wt% compared to the bulk material. View evidence ↗

      What it means

      A limitation of pXRF is that surface corrosion (patina) can artificially inflate the measured concentrations of tin and lead by 1–3 wt% compared to the bulk material.

      In the paper's own words

      “The enrichment of Sn and Pb in patina layers can inflate their apparent concentrations by 1–3 wt% relative to the bulk”

      Page 3

      Found in: Discussion

      Read it in the full textOpen PDF at page 3 ↗
    • The authors state that future research should utilize larger sample sets with known provenance to create a comprehensive compositional database for the central Mediterranean. View evidence ↗

      What it means

      The authors state that future research should utilize larger sample sets with known provenance to create a comprehensive compositional database for the central Mediterranean.

      In the paper's own words

      “Future work should extend this approach to a larger sample set with known provenance to build a comprehensive compositional database for the central Mediterranean”

      Page 3

      Found in: Discussion

      Read it in the full textOpen PDF at page 3 ↗

Visual summary

1 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

Replotted from source data
Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Sn (wt%) and Pb (wt%): Archaic (700–480 BC) vs Classical (480–323 BC) vs Hellenistic (323–31 BC) vs Roman (31 BC–476 AD)
Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Sn (wt%) and Pb (wt%): Archaic (700–480 BC) vs Classical (480–323 BC) vs Hellenistic (323–31 BC) vs Roman (31 BC–476 AD)

Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
Mean Elemental Composition (wt%) of Three Artifact CategoriesTable 1Page 2Sn and Pb Content in Bronze Coins by Historical PeriodTable 2Page 2Elemental composition profiles of three artifact categories measured by pxrf (logarithmic scale).Figure 1Page 2Mean sn and pb concentrations in bronze coins by historical period, with error bars showing ± 1 sd.Figure 2Page 3
FULL TEXT Original article · reflowed for reading

Introduction

Archaeological artifacts carry chemical fingerprints that can reveal their origin, date of manufacture, and the trade networks through which they travelled [1] . Elemental analysis of metals, ceramics, and glass has been practised since the nineteenth century, but traditional methods wet-chemical assays, atomic absorption, ICP-MS require sample removal, which is unacceptable for unique or legally protected objects [2] . XRF spectroscopy solved this problem by enabling surface elemental determination without physical contact or material loss. The development of portable, handheld XRF instruments over the past two decades has brought the laboratory to the museum storeroom and the excavation trench [3] . Modern pXRF units achieve detection limits below 10 ppm for mid-Z elements and provide quantitative results in 60-120 seconds per measurement point [4] . Yet questions about accuracy persist, particularly for corroded surfaces, heterogeneous samples, and light elements (Z < 12) that are poorly excited in air [5] . This research examined thirty-five artifacts spanning four historical periods (Archaic through Roman) and two material classes (copper alloys and lead-antimony pottery glazes). The objectives were to establish elemental profiles, validate pXRF accuracy against certified reference materials, and test whether compositional data can distinguish artifact types and chronological periods through multivariate statistics [6] .

Theoretical background

XRF operates on a straightforward physical principle: when a primary X-ray beam strikes a sample, inner-shell electrons are ejected, and the resulting vacancy is filled by an electron from a higher shell, emitting a characteristic fluorescent X-ray whose energy identifies the element and whose intensity is proportional to its concentration [7] . The fundamental parameters (FP) approach relates measured intensities to concentrations through a system of equations that account for matrix absorption and enhancement effects. In pXRF, the source is typically a miniaturised Rh-anode X-ray tube operating at 15-50 kV, and the detector is a silicon drift detector (SDD) with energy resolution of 135-145 eV at Mn Kα [4] . For archaeological bronzes, the main analytical challenge is surface corrosion (patina), which enriches certain elements (Sn, Pb) relative to the bulk and can bias quantification if not accounted for [8] .

Material and Methods

Material and Methods

Material

This research was conducted from January 2024 to November 2024 at the Department of Chemical Analysis and Quality Control, Collegio Romano di Scienze Chimiche, Rome, Italy, with complementary analyses at the Department of Chemistry, Università del Mediterraneo, Naples, Italy. Thirty-five artifacts were made available by the Museo Nazionale Romano under a research loan agreement (protocol MNR-2024-0013, dated 8 January 2024): fifteen bronze coins (Archaic to Roman, 6th century BC to 3rd century AD), twelve bronze hand tools (Classical to Hellenistic), and eight glazed pottery fragments (Roman period). Certified reference materials NIST SRM 1107 (naval brass) and BCR-691 (a set of five copper alloy standards) were used for accuracy verification.

Methods

Measurements were performed with a Bruker Tracer 5g handheld XRF spectrometer (Rh anode, SDD detector, spot size 8 mm). Bronze artifacts were analysed at 40 kV / 35 µA with a Ti/Al primary beam filter and 120 s live time. Pottery glazes used 15 kV / 55 µA without filter and 90 s. Three points per artifact were measured on cleaned surfaces (patina gently removed mechanically where permitted by the conservator). Quantification used the Bruker Artax FP calibration for copper alloys and an empirical calibration for glazes built from in-house standards. Data quality was ensured by measuring one CRM every ten samples. PCA was performed using PAST 4.03 software on centred logratio transformed data to handle the compositional closure constraint. All elemental concentrations are reported in weight percent on a moisture-free basis [9] .

Performance evaluation

Accuracy was assessed by repeated analysis (n = 10) of NIST SRM 1107 and three BCR-691 standards. Measured values for Cu, Sn, Pb, and Zn agreed with certified values within 96.3-103.8%. Precision (RSD, n = 10) was 0.4-1.7% for major elements (>1 wt%) and 3.8-8.2% for minor elements (<1 wt%). Detection limits, computed as 3σ of blank measurements, were 18 ppm for Cu, 12 ppm for Sn, 8 ppm for Pb, and 24 ppm for Fe under the bronze protocol [10] .

Results

Bronze coins and tools shared a Cu-Sn base but differed in Pb content coins averaged 3.2% Pb versus 1.6% for tools (Table 1), likely reflecting the intentional addition of lead to improve casting fluidity in coinage. Pottery glazes showed a completely different profile dominated by Pb and Sb. Table 2 reveals a progressive increase in Pb content from the Archaic to the Roman period, while Sn peaked during the Hellenistic era. The Sn/Pb ratio declined from 9.0 in the Archaic to 1.5 in the Roman period, providing a useful compositional chronological marker. The log-scale profiles in Figure 1 clearly separate the bronze and ceramic groups, with pottery glazes showing dramatically different Cu/Pb/Sb ratios . Figure 2 visualises the chronological trend in alloy composition. The crossover pattern rising Pb, fluctuating Sn is consistent with the known shift toward cheaper leaded bronzes as the Roman economy expanded and demand for coinage grew [11] .

Figure 2. Mean sn and pb concentrations in bronze coins by historical period, with error bars showing ± 1 sd.
Mean sn and pb concentrations in bronze coins by historical period, with error bars showing ± 1 sd.↗ Enlarge
Figure 2
Mean sn and pb concentrations in bronze coins by historical period, with error bars showing ± 1 sd.

Mean sn and pb concentrations in bronze coins by historical period, with error bars showing ± 1 sd.

Open full-size image ↗
Original paper figureSource PDF · page 3 ↗
Figure 1. Elemental composition profiles of three artifact categories measured by pxrf (logarithmic scale).
Elemental composition profiles of three artifact categories measured by pxrf (logarithmic scale).↗ Enlarge
Figure 1
Elemental composition profiles of three artifact categories measured by pxrf (logarithmic scale).

Elemental composition profiles of three artifact categories measured by pxrf (logarithmic scale).

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗
Table 2. Sn and Pb Content in Bronze Coins by Historical Period
PeriodNSn (wt%)Pb (wt%)
Archaic (700–480 BC)37.2 ± 1.10.8 ± 0.3
Classical (480–323 BC)49.4 ± 0.92.1 ± 0.5
Hellenistic (323–31 BC)410.8 ± 1.33.7 ± 0.8
Roman (31 BC–476 AD)48.1 ± 1.05.4 ± 1.2

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Sn and Pb Content in Bronze Coins by Historical Period↗ Enlarge
Table 2
Sn and Pb Content in Bronze Coins by Historical Period

Sn and Pb Content in Bronze Coins by Historical Period

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Original paper tableSource PDF · page 2 ↗
Table 1. Mean Elemental Composition (wt%) of Three Artifact Categories
Category (n)CuSnPbFeOther
Bronze coins (15)84.3 ± 2.49.7 ± 1.83.2 ± 1.41.4 ± 0.31.4
Bronze tools (12)88.1 ± 1.97.8 ± 1.31.6 ± 0.71.2 ± 0.41.3
Pottery glaze (8)2.4 ± 0.60.8 ± 0.342.7 ± 3.88.3 ± 1.745.8

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Mean Elemental Composition (wt%) of Three Artifact Categories↗ Enlarge
Table 1
Mean Elemental Composition (wt%) of Three Artifact Categories

Mean Elemental Composition (wt%) of Three Artifact Categories

Open full-size image ↗
Original paper tableSource PDF · page 2 ↗

Comprehensive interpretation

PCA of the full dataset separated the three artifact categories along the first two principal components (explaining 87.4% of variance), confirming that pXRF data contain sufficient information for material classification. The temporal trend in Sn/Pb ratio among coins adds a chronological dimension that complements stylistic dating methods.

Discussion

The elemental profiles obtained here are consistent with published analyses of Mediterranean bronzes. Craddock [11] documented the gradual increase in lead content from the Archaic through Roman periods, interpreting it as an economic response to tin scarcity and the desire for improved castability. Our data extend that observation with quantitative pXRF measurements validated against certified reference materials. Surface corrosion remains a concern for pXRF accuracy. The enrichment of Sn and Pb in patina layers can inflate their apparent concentrations by 1-3 wt% relative to the bulk [8] . We mitigated this by analysing mechanically cleaned spots, but for artifacts where cleaning isn't permitted, depth-profiling approaches or correction algorithms are needed. The pottery glaze results demonstrate pXRF's ability to handle a different matrix entirely the Pb-Sb-rich antimonate yellow glaze identified here matches the "giallo antico" type known from Roman Imperial workshops [12] . Future work should extend this approach to a larger sample set with known provenance to build a comprehensive compositional database for the central Mediterranean, and should incorporate lead isotope ratio analysis (by MC-ICP-MS on micro-samples where permitted) for ore-source attribution [13] .

Conclusion

Portable XRF spectroscopy was applied to thirty-five archaeological artifacts from Roman and pre-Roman Mediterranean contexts, delivering quantitative elemental data without material loss. Bronze coins and tools were distinguished by their Pb content, and a chronological trend in the Sn/Pb ratio was identified across four historical periods. Pottery glazes showed a lead-antimonate composition consistent with known Roman manufacturing traditions. Accuracy against NIST and BCR certified reference materials was 96.3-103.8% for major elements, confirming that pXRF provides reliable data for archaeometric interpretation. PCA cleanly separated the three artifact categories, demonstrating the multivariate potential of the dataset. These findings support the broader adoption of pXRF as a first-line analytical tool in museum conservation, archaeological fieldwork, and cultural heritage management.

References

18 in the original paper
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