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Topic · Archeology

Cultural Heritage Materials Analysis

Cultural Heritage Materials Analysis is a research topic within Archeology. Science Explorer counts 25k research works in it since 1950. 35.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers a wide range of analytical techniques and scientific methods used in the conservation and analysis of art, archaeological artifacts, and historical materials. The topics include spectroscopic analysis such as Raman spectroscopy, X-ray fluorescence, and hyperspectral imaging, as well as the application of proteomic analysis and synchrotron radiation in the study of pigments, glass production, and cultural heritage materials.

  • Raman Spectroscopy
  • X-Ray Fluorescence
  • Hyperspectral Imaging
  • Archaeological Science
  • Surface-Enhanced Raman Spectroscopy
  • Pigment Analysis
  • Cultural Heritage
  • Synchrotron Radiation
  • Proteomic Analysis
  • Glass Production
Research works
25k
fractional, since 1950
In the world top 10%
8.7k
per year above
Top-10% rate
35.0%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+30%
the tick is no change

Which countries lead Cultural Heritage Materials Analysis research?

By volume, China and Italy publish the most (845 and 451 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 845 works
  2. 2 Italy 451 works
  3. 3 United States 334 works
  4. 4 France 314 works
  5. 5 Spain 193 works
  6. 6 United Kingdom 191 works
  7. 7 Türkiye 157 works
  8. 8 Russia 147 works
  9. 9 Germany 142 works
  10. 10 India 125 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 29.1%Italy: 15.6%United States: 11.5%France: 10.8%6 others listed: 32.9%29%largest
China845 · 29.1%Italy451 · 15.6%United States334 · 11.5%France314 · 10.8%6 others listed956 · 32.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Cultural Heritage Materials Analysis research?

By volume in 2022–2025, Centre National de la Recherche Scientifique publishes the most Cultural Heritage Materials Analysis research, followed by Sapienza University of Rome and State Administration of Cultural Heritage.

By volume, 2022–2025

  1. 1 Centre National de la Recherche Scientifique France 44 works
  2. 2 Sapienza University of Rome Italy 29 works
  3. 3 State Administration of Cultural Heritage China 23 works
  4. 4 Cairo University Egypt 22 works
  5. 5 University of Florence Italy 21 works
  6. 6 National Research Council Italy 20 works
  7. 7 Institute of Archaeology China 19 works
  8. 8 University of Milan Italy 19 works
  9. 9 Universidad de Granada Spain 19 works
  10. 10 University of Science and Technology Beijing China 19 works

Who are the leading researchers in Cultural Heritage Materials Analysis?

The most-cited researchers publishing on Cultural Heritage Materials Analysis include Akihisa Inoue.

  1. 1 Akihisa Inoue 4.7k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Cultural Heritage Materials Analysis research done?

The largest centres of Cultural Heritage Materials Analysis research in 2022–2025 are Beijing (China), Paris (France), Rome (Italy) and London (United Kingdom).

Largest cities, 2022–2025

  1. 1 Beijing China 243 works
  2. 2 Paris France 138 works
  3. 3 Rome Italy 94 works
  4. 4 London United Kingdom 65 works
  5. 5 Xi'an China 58 works
  6. 6 Moscow Russia 51 works
  7. 7 Shanghai China 49 works
  8. 8 Giza Egypt 44 works
  9. 9 Lisbon Portugal 43 works
  10. 10 Milan Italy 43 works
See Cultural Heritage Materials Analysis on the map

Where is the best place to study Cultural Heritage Materials Analysis?

Among universities, judged by research, University of Évora, University of Pavia and Nanjing Forestry University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%25%50%75%mean 52.9%fractional works in this node (log) →share in the world top 10% →University of Évora: 15, 56.7%University of Pavia: 9, 55.2%Nanjing Forestry University: 17, 46.9%Universidade Nova de Lisboa: 16, 46.1%Ca' Foscari University of Venice: 13, 56.3%Universidad de Granada: 19, 52.6%University of Florence: 21, 48.4%Shaanxi University of Science and Technology: 9, 60.5%Sapienza University of Rome: 29, 43.7%University of Pisa: 11, 62.6%University of ÉvoraUniversity of PaviaNanjing Forestry Uni…Universidade Nova de…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1University of Évora Portugal 78.956.7%38.2×15 +168.2%
2University of Pavia Italy 68.055.2%8.0×9 +209.5%
3Nanjing Forestry University China 67.346.9%8.5×17 +163.8%
4Universidade Nova de Lisboa Portugal 67.046.1%12.8×16 +38.6%
5Ca' Foscari University of Venice Italy 66.556.3%12.6×13 +51.9%
6Universidad de Granada Spain 65.552.6%8.2×19 +40.9%
7University of Florence Italy 64.648.4%9.4×21 -8.0%
8Shaanxi University of Science and Technology China 61.360.5%8.5×9 +93.0%
9Sapienza University of Rome Italy 60.943.7%6.2×29 +66.6%
10University of Pisa Italy 60.462.6%5.7×11 +100.4%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Cultural Heritage Materials Analysis research growing?

Output in 2018–2022 was 30% higher than in 2013–2017, peaking in 2023. The fastest-growing topics are Cultural Heritage Materials Analysis.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.