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Supramolecular Chemistry and Complexes

Supramolecular Chemistry and Complexes is a research topic within Organic Chemistry. Science Explorer counts 21k research works in it since 1950. 23.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the field of supramolecular chemistry, focusing on self-assembly, molecular recognition, and the design of artificial molecular machines. It covers a wide range of topics including host-guest interactions, coordination chemistry, cucurbiturils, dynamic covalent chemistry, and the development of nanoscale devices.

  • Supramolecular Chemistry
  • Molecular Machines
  • Self-Assembly
  • Host-Guest Interactions
  • Coordination Chemistry
  • Cucurbiturils
  • Macrocycles
  • Dynamic Covalent Chemistry
  • Metal-Organic Frameworks
  • Nanomachines
Research works
21k
fractional, since 1950
In the world top 10%
4.9k
per year above
Top-10% rate
23.7%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+1%
the tick is no change

Which countries lead Supramolecular Chemistry and Complexes research?

By volume, China and Japan publish the most (1.1k and 240 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.1k works
  2. 2 Japan 240 works
  3. 3 United States 226 works
  4. 4 India 213 works
  5. 5 Germany 135 works
  6. 6 United Kingdom 124 works
  7. 7 France 122 works
  8. 8 Russia 95 works
  9. 9 Spain 82 works
  10. 10 Italy 71 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: 45.6%Japan: 10.0%United States: 9.4%India: 8.9%6 others listed: 26.1%46%largest
China1,097 · 45.6%Japan240 · 10.0%United States226 · 9.4%India213 · 8.9%6 others listed628 · 26.1%

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

Which institutions lead Supramolecular Chemistry and Complexes research?

By volume in 2022–2025, Guizhou University publishes the most Supramolecular Chemistry and Complexes research, followed by Nankai University and Chinese Academy of Sciences.

Who are the leading researchers in Supramolecular Chemistry and Complexes?

The most-cited researchers publishing on Supramolecular Chemistry and Complexes include Ben Zhong Tang, Judith A. K. Howard and Wei Huang.

  1. 1 Ben Zhong Tang Hong Kong 7k citations
  2. 2 Judith A. K. Howard United Kingdom 5.5k citations
  3. 3 Wei Huang China 5.5k citations
  4. 4 Peter G. Jones Germany 3.6k citations
  5. 5 F. Albert Cotton United States 3.5k citations
  6. 6 Jacky W. Y. Lam Hong Kong 3.4k citations
  7. 7 William A. Goddard United States 3.2k citations
  8. 8 Joseph T. Hupp United States 3.1k citations

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

Where is Supramolecular Chemistry and Complexes research done?

The largest centres of Supramolecular Chemistry and Complexes research in 2022–2025 are Beijing (China), Shanghai (China), Tokyo (Japan) and Tianjin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Kazan’ and Guiyang.

Largest cities, 2022–2025

  1. 1 Beijing China 152 works
  2. 2 Shanghai China 119 works
  3. 3 Tokyo Japan 77 works
  4. 4 Tianjin China 64 works
  5. 5 Guangzhou China 51 works
  6. 6 Hangzhou China 50 works
  7. 7 Guiyang China 46 works
  8. 8 Nanjing China 45 works
  9. 9 Paris France 43 works
  10. 10 Xi'an China 37 works

Where it is the local speciality

  1. Kazan’RU · 30.9 works16×
  2. GuiyangCN · 46.4 works13×
← less than its size predictsmore →

Location quotient: how much more of its research is in Supramolecular Chemistry and Complexes than the world average.

See Supramolecular Chemistry and Complexes on the map

Where is the best place to study Supramolecular Chemistry and Complexes?

Among universities, judged by research, TU Dortmund University, East China Normal University and Nankai 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%20%40%60%mean 35.17%fractional works in this node (log) →share in the world top 10% →TU Dortmund University: 9, 46.5%East China Normal University: 26, 40.7%Nankai University: 32, 36.7%Guizhou University: 40, 17.7%University of Groningen: 13, 27.0%University of Manchester: 11, 48.2%Fudan University: 24, 33.5%East China University of Science and Technology: 18, 22.7%University of Cambridge: 16, 47.4%Jilin University: 20, 31.3%TU Dortmund UniversityEast China Normal Un…Nankai UniversityGuizhou 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 TU Dortmund UniversityGermany 73.246.5%12.3×9 +320.0%
2 East China Normal UniversityChina 72.940.7%19.1×26 +25.1%
3 Nankai UniversityChina 69.036.7%16.9×32 -22.5%
4 Guizhou UniversityChina 61.017.7%26.9×40 +7.7%
5 University of GroningenNetherlands 60.827.0%9.7×13 +43.9%
6 University of ManchesterUnited Kingdom 60.048.2%5.1×11 +110.7%
7 Fudan UniversityChina 58.133.5%7.6×24 +6.9%
8 East China University of Science and TechnologyChina 57.722.7%12.8×18 +68.2%
9 University of CambridgeUnited Kingdom 57.647.4%5.3×16 -25.1%
10 Jilin UniversityChina 56.631.3%7.1×20 +90.9%

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 Supramolecular Chemistry and Complexes research growing?

Output in 2018–2022 was 1% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Supramolecular Chemistry and Complexes.

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.