Science Explorer Interactive view Map
Topic · Fluid Flow and Transfer Processes

Thermodynamic properties of mixtures

Thermodynamic properties of mixtures is a research topic within Fluid Flow and Transfer Processes. Science Explorer counts 30k research works in it since 1950. 12.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the thermodynamic properties, such as density, viscosity, surface tension, and excess molar volumes, of various liquid mixtures including binary and aqueous solutions. The research also explores the interactions and hydrogen bonding in these mixtures.

  • Density
  • Viscosity
  • Surface Tension
  • Binary Mixtures
  • Thermodynamic Properties
  • Excess Molar Volumes
  • Refractive Indices
  • Speed of Sound
  • Hydrogen Bonding
  • Aqueous Solutions
Research works
30k
fractional, since 1950
In the world top 10%
3.6k
per year above
Top-10% rate
12.0%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-35%
the tick is no change

Which countries lead Thermodynamic properties of mixtures research?

By volume, India and China publish the most (336 and 219 works in 2022–2025).

By volume, 2022–2025

  1. 1 India 336 works
  2. 2 China 219 works
  3. 3 United States 124 works
  4. 4 Russia 117 works
  5. 5 Iran 86 works
  6. 6 Germany 84 works
  7. 7 Japan 52 works
  8. 8 France 51 works
  9. 9 Spain 38 works
  10. 10 Brazil 37 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.

India: 29.4%China: 19.1%United States: 10.8%Russia: 10.2%6 others listed: 30.4%29%largest
India336 · 29.4%China219 · 19.1%United States124 · 10.8%Russia117 · 10.2%6 others listed348 · 30.4%

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

Which institutions lead Thermodynamic properties of mixtures research?

By volume in 2022–2025, Xi'an Jiaotong University publishes the most Thermodynamic properties of mixtures research, followed by Institute of Solution Chemistry and Lovely Professional University.

By volume, 2022–2025

  1. 1 Xi'an Jiaotong UniversityChina 18 works
  2. 2 Institute of Solution ChemistryRussia 17 works
  3. 3 Lovely Professional UniversityIndia 16 works
  4. 4 Technical University of DenmarkDenmark 16 works
  5. 5 Siksha O Anusandhan UniversityIndia 13 works
  6. 6 Malayer UniversityIran 13 works
  7. 7 Swami Ramanand Teerth Marathwada UniversityIndia 12 works
  8. 8 China University of Petroleum, East ChinaChina 11 works
  9. 9 University of JammuIndia 10 works
  10. 10 St Petersburg UniversityRussia 9 works

Who are the leading researchers in Thermodynamic properties of mixtures?

The most-cited researchers publishing on Thermodynamic properties of mixtures include H. Eugene Stanley, William L. Jorgensen and Paul J. Flory.

  1. 1 H. Eugene Stanley United States 5.5k citations
  2. 2 William L. Jorgensen United States 4.5k citations
  3. 3 Paul J. Flory United States 3.7k citations
  4. 4 Harold A. Scheraga United States 3.3k citations
  5. 5 Abdullah M. Asiri Saudi Arabia 3.2k citations

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

Where is Thermodynamic properties of mixtures research done?

The largest centres of Thermodynamic properties of mixtures research in 2022–2025 are Moscow (Russia), Beijing (China), Xi'an (China) and Qingdao (China).

Largest cities, 2022–2025

  1. 1 Moscow Russia 35 works
  2. 2 Beijing China 33 works
  3. 3 Xi'an China 24 works
  4. 4 Qingdao China 23 works
  5. 5 Paris France 23 works
  6. 6 Bhubaneswar India 21 works
  7. 7 Ivanovo Russia 20 works
  8. 8 Tianjin China 19 works
  9. 9 Nanded India 16 works
  10. 10 Phagwāra India 16 works
See Thermodynamic properties of mixtures on the map

Where is the best place to study Thermodynamic properties of mixtures?

Among universities, judged by research, Technical University of Denmark, Lovely Professional University and Malayer 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%10%20%mean 8.12%fractional works in this node (log) →share in the world top 10% →Technical University of Denmark: 16, 18.6%Lovely Professional University: 16, 14.2%Malayer University: 13, 7.8%Siksha O Anusandhan University: 13, 12.9%University of Jammu: 10, 3.2%Xi'an Jiaotong University: 18, 0.0%China University of Petroleum, East China: 11, 3.1%University of Tabriz: 9, 7.1%Swami Ramanand Teerth Marathwada University: 12, 4.9%Hebei University of Technology: 9, 9.4%Technical University…Lovely Professional …Siksha O Anusandhan …Malayer 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 Technical University of DenmarkDenmark 83.518.6%19.8×16 +6.6%
2 Lovely Professional UniversityIndia 74.714.2%20.9×16 —
3 Malayer UniversityIran 66.87.8%317.3×13 +333.3%
4 Siksha O Anusandhan UniversityIndia 65.412.9%42.0×13 +36.2%
5 University of JammuIndia 52.23.2%89.6×10 +216.7%
6 Xi'an Jiaotong UniversityChina 51.80.0%7.1×18 +223.4%
7 China University of Petroleum, East ChinaChina 49.63.1%14.3×11 +140.7%
8 University of TabrizIran 49.67.1%25.1×9 +31.2%
9 Swami Ramanand Teerth Marathwada UniversityIndia 48.84.9%398.2×12 -8.7%
10 Hebei University of TechnologyChina 47.49.4%14.3×9 +13.9%

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 Thermodynamic properties of mixtures research growing?

Output in 2018–2022 was 35% lower than in 2013–2017, peaking in 2008.

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.