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Photopolymerization techniques and applications

Photopolymerization techniques and applications is a research topic within Organic Chemistry. Science Explorer counts 19k research works in it since 1950. 12.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores advances, challenges, and opportunities in photoinitiated polymerization reactions, including topics such as photoinitiating systems, visible light-induced polymerization, cationic and radical mechanisms, UV-curing, and kinetics. The research covers a wide range of applications and materials, from hydrogels to composites, and emphasizes the development of new strategies and materials for efficient and controlled photopolymerization processes.

  • Photoinitiation
  • Polymerization
  • Visible Light
  • Cationic
  • Radical
  • UV-Curing
  • Photoinitiating Systems
  • Kinetics
  • Frontal Polymerization
  • Thioxanthone
Research works
19k
fractional, since 1950
In the world top 10%
2.4k
per year above
Top-10% rate
12.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+9%
the tick is no change

Which countries lead Photopolymerization techniques and applications research?

By volume, China and the United States publish the most (911 and 284 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 911 works
  2. 2 United States 284 works
  3. 3 France 124 works
  4. 4 India 110 works
  5. 5 Japan 107 works
  6. 6 Russia 94 works
  7. 7 Germany 90 works
  8. 8 South Korea 79 works
  9. 9 Türkiye 77 works
  10. 10 Poland 61 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: 47.1%United States: 14.7%France: 6.4%India: 5.7%6 others listed: 26.2%47%largest
China911 · 47.1%United States284 · 14.7%France124 · 6.4%India110 · 5.7%6 others listed507 · 26.2%

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

Which institutions lead Photopolymerization techniques and applications research?

By volume in 2022–2025, Beijing University of Chemical Technology publishes the most Photopolymerization techniques and applications research, followed by South China University of Technology and Centre National de la Recherche Scientifique.

Who are the leading researchers in Photopolymerization techniques and applications?

The most-cited researchers publishing on Photopolymerization techniques and applications include Krzysztof Matyjaszewski, Soo‐Jin Park and Abdullah M. Asiri.

  1. 1 Krzysztof Matyjaszewski United States 4.4k citations
  2. 2 Soo‐Jin Park South Korea 3.2k citations
  3. 3 Abdullah M. Asiri Saudi Arabia 3.2k citations
  4. 4 Hoi Sing Kwok Hong Kong 2.3k citations

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

Where is Photopolymerization techniques and applications research done?

The largest centres of Photopolymerization techniques and applications research in 2022–2025 are Beijing (China), Shanghai (China), Guangzhou (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Mulhouse and Wuxi.

Largest cities, 2022–2025

  1. 1 Beijing China 146 works
  2. 2 Shanghai China 69 works
  3. 3 Guangzhou China 61 works
  4. 4 Nanjing China 46 works
  5. 5 Xi'an China 43 works
  6. 6 Wuhan China 39 works
  7. 7 Moscow Russia 36 works
  8. 8 Paris France 33 works
  9. 9 Hangzhou China 33 works
  10. 10 Istanbul Türkiye 31 works

Where it is the local speciality

  1. MulhouseFR · 21.3 works145×
  2. WuxiCN · 23.6 works9.7×
← less than its size predictsmore →

Location quotient: how much more of its research is in Photopolymerization techniques and applications than the world average.

See Photopolymerization techniques and applications on the map

Where is the best place to study Photopolymerization techniques and applications?

Among universities, judged by research, Aix-Marseille Université, Jiangnan University and Université de Strasbourg 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%20%40%mean 29.77%fractional works in this node (log) →share in the world top 10% →Aix-Marseille Université: 8, 46.4%Jiangnan University: 24, 24.3%Université de Strasbourg: 8, 34.9%University of Illinois Urbana-Champaign: 12, 46.2%Université de Haute-Alsace: 15, 22.3%Nanjing Forestry University: 15, 28.9%Beijing University of Chemical Technology: 25, 15.8%Cracow University of Technology: 9, 26.8%Politecnico di Torino: 10, 37.6%South China University of Technology: 24, 14.5%Aix-Marseille Univer…University of Illino…Université de Strasb…Jiangnan University
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
1 Aix-Marseille UniversitéFrance 64.146.4%11.0×8 +4.3%
2 Jiangnan UniversityChina 61.524.3%15.5×24 -33.2%
3 Université de StrasbourgFrance 59.634.9%14.9×8
4 University of Illinois Urbana-ChampaignUnited States 58.846.2%5.4×12 +83.0%
5 Université de Haute-AlsaceFrance 57.422.3%132.1×15 -24.1%
6 Nanjing Forestry UniversityChina 56.828.9%13.1×15 -43.1%
7 Beijing University of Chemical TechnologyChina 56.615.8%23.0×25 -36.9%
8 Cracow University of TechnologyPoland 55.126.8%42.8×9 +92.4%
9 Politecnico di TorinoItaly 54.737.6%8.2×10 -0.3%
10 South China University of TechnologyChina 52.114.5%8.9×24 -71.7%

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 Photopolymerization techniques and applications research growing?

Output in 2018–2022 was 9% higher than in 2013–2017, peaking in 2025.

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.