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Research Article
Fragmentation of Global Science and the Role of BRICS: A Bibliometric Analysis of Scientific Publications on Semiconductors
expand article infoLilia Valitova, Marina Sheresheva, Dmitry Oskin§
‡ Lomonosov Moscow State University, Moscow, Russia
§ Moscow Analytical Center, Moscow, Russia
Open Access

Abstract

This paper examines the fragmentation of global science and the changing role of the BRICS countries in international research collaboration under geopolitical pressure. Using bibliometric analysis of more than 688,000 semiconductor-related publications indexed in the Web of Science Core Collection (1965–2025), the study traces how the imposition of sanctions since 2022 has transformed global co-authorship networks. The findings demonstrate a structural shift from a previously integrated international scientific system toward a constellation of regional clusters. China has consolidated its position as the central node of the global publication network, assuming integrative functions once held by the United States and the European Union. India has increased its connectivity, strengthening ties within BRICS and with the Global South. Russia’s role has markedly declined following the suspension of collaboration with Western institutions, accompanied by a drop in joint publications. At the same time, Saudi Arabia and Egypt have emerged as new peripheral hubs, reflecting a reallocation of scientific collaboration toward countries not affected by sanction regimes. Network-metric analysis (degree, betweenness, closeness, and eigenvector centrality) confirms the polarization of the international research system. Sanctions have weakened traditional nodes while fostering new centers of influence within BRICS and the Global South. The paper concludes that sanctions have accelerated the regionalization of global science, transforming the semiconductor research landscape from a unified global network into multiple interconnected regional systems, each with its own core and sphere of influence.

Keywords

international scientific collaboration, global science fragmentation, joint publishing, semiconductors, bibliometric analysis, network studies.

JEL: O32, F02, C88.

1. Introduction

International scientific cooperation is one of the key drivers in the contemporary science and technology development. Since the late twentieth century, a growing number of joint publications and international projects have contributed to faster accumulation of knowledge, formation of global research networks and increased citation impact of scientific results (Wagner & Leydesdorff, 2005). This trend is particularly significant in high-tech industries, where achieving results requires concentration of financial resources, equipment and expertise from several countries simultaneously. Research in the field of semiconductors gives a vivid example of this interdependence: key technological chains are spread across various world regions, and international collaborations provide access to critical knowledge and infrastructure (OECD, 2025). The United States and Europe continue to lead in architectural design and software development, Taiwan and Korea specialize in contract manufacturing, and China dominates the rapidly expanding sector of mass production and testing. Under these circumstances, the disruption of international relations threatens both scientific advancement and economic stability.

Since 2022, amidst escalating geopolitical tensions and imposition of sanctions on Russia and some of its partners, international scientific landscape underwent significant changes. Major universities in the United States and Europe have announced that they are suspending cooperation with Russian organizations. Many grant programs, including Horizon Europe, have been stopped for Russian researchers and access to international research infrastructure has been restricted (Plackett, 2022). All this affected not only Russia but also the BRICS countries and, more broadly, the “Global South” (Gueye et al., 2022; McManus et al., 2024; Saba & Pretorius, 2024).

Bibliometric data confirm the decline in publication activity and the sharp drop in joint works between Russia and its Western partners in the period 2022-2023 (Zhang et al., 2024). At the same time, there have been increases in joint publications within BRICS and intensified collaborations with universities and research centers in the Middle East, Africa, and Southeast Asia (Sokolov et al., 2025). This indicates the emergence of new patterns of interaction in global science, which can be described as polarization of the global scientific space. While in the 2000s and 2010s, science developed as an integrated and interconnected network, the 2020s have seen the growing importance of regional clusters and the weakening of global links. Sanctions and political barriers have not only limited BRICS cooperation with Western research centers but also stimulated the rise of peripheral nodes of scientific collaboration, such as Saudi Arabia and Egypt.

The aim of this paper is to reveal, based on bibliometric analysis of publications related to semiconductors, how sanctions have transformed the structure of international scientific cooperation. The research questions are as follows: is there a reduction in the connectivity of the global network and a constraining of traditional interaction channels? And, at the same time is there a stimulation of the development of new regional centers, leading to a gradual transformation of the global architecture of science?

The paper is structured as follows: Section 2 provides a review of relevant literature. Section 3 describes the hypotheses and chosen methodology. Section 4 presents the main findings of the study, including the visualization of networked collaboration in semiconductor research. Section 5 discusses the results compared to the hypotheses formulated in Section 3. The paper concludes with a discussion of the limitations of the study and suggestions for future research paths.

2. Literature review

2.1. BRICS countries as a new rising power in contemporary scientific world

Today, one can talk about the rise of network structures that make it possible to create a win-win situation for their participants. An example of this is the BRICS intergovernmental organization comprising Brazil, Russia, India, China, South Africa, Iran, Egypt, Ethiopia, Saudi Arabia and the United Arab Emirates (Merino & Tianjiao, 2025). Though extremely different, the BRICS members play a highly important role in their respective regions. Some view them as leaders in economic development, innovation and knowledge transfer among developing countries (Dube, 2024, p.8).

China is leading this race for the world technological supremacy (Knox, 2020; Savage, 2020; Deligöz, 2025; Elbassoussy, 2025). According to HSE University research, in 2023 the list of highly cited scientists included 6,835 researchers from 64 countries. Of these, 2,542 were affiliated with organizations located in the US, 1,350 in China, 562 in the UK, 333 in Germany and 298 in Australia. The composition of the “top five” has not changed in the past ten years, but the “flows” of highly cited research have noticeably shifted. In 2014, every second highly cited researcher came from the US. In 2023, this share decreased to 37.2%, while China showed almost a fivefold increase, from 4.6% in 2008 to 19.8% (Kutsenko et al., 2024). It is now obvious that China’s approach challenges America’s traditional advantages in macro-level drivers of technological competition, such as its technology talent pipeline, R&D ecosystem and national policies (Allison et al., 2021). More and more developing countries are taking serious steps to design and introduce new technologies without directly competing with the powerful economy of the United States. Thus, India and Russia have set ambitious goals for the next decade (Surana et al., 2020; Danilin, 2021). Africa, Latin America and the Caribbean (Abisuga-Oyekunle et al., 2020; Bazarkina & Pashentsev, 2020; Mazzucato, 2023), and Middle East countries like Saudi Arabia and Iran are all striving to make technological progress (Al-Saidi & Haghirian, 2020; Zorri, 2023).

If we analyze the Hirsch index ranking of countries in the important field of artificial intelligence (AI), we can see that China and the United States are at the top of the list in almost all aspects of AI research. In terms of critical AI technology, India looks quite promising. It is worth noting that Iran, a new member of BRICS, is also making significant strides.

2.2. Restrictions on joint research and exemptions for open publications

Collaborative research in high-technology fields faces serious constraints related to export-control regimes and the protection of intellectual property. In the United States, two main regulatory frameworks are in force: The International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR). They restrict the transfer of technologies, equipment, and data that may have military or “dual-use” applications (22 CFR §120.34; EAR §734.3(b)(3)) (University of Pittsburgh, 2023). Similar regimes have been established in the EU and a number of Asian countries through rules governing dual-use goods and technologies.

Research and development in this sphere typically involve technology transfer, access to laboratory equipment, and the exchange of “sensitive” data — all of which often fall under national security laws and international sanctions regimes (Plackett, 2022; Zhang et al., 2024). Consequently, joint applied research and experimental design activities are frequently prohibited or tightly regulated (Deligöz, 2025; Matulionyte & Lee, 2025).

At the same time, one may treat publications in scientific journals as part of the open science concept (Norori et al., 2021; Bertram et al., 2023). Exemptions for publications are explicitly embedded within export-control regimes: according to EAR §734.7 and the ITAR Public Domain Exclusion (22 CFR §120.34), published materials and results of fundamental research available to the public do not fall under export control. In parallel, the Fundamental Research Exclusion (National Science Foundation, 1985) stipulates that fundamental research intended for publication should not be restricted by national-security considerations.

So, research papers in open, peer-reviewed journals that do not contain classified or proprietary information are not considered breaches of secrecy. This explains the seeming paradox: international publications on semiconductors and other high technologies continue to appear, while actual joint R&D and cross-border technology exchange remains prohibited.

2.3. Global changes in joint publication activity

After the imposition of sanctions against Russia and its partners, the number of joint scientific publications with Western partners declined sharply (Mallapaty et al., 2022; Polozhikhina & Korovnikova, 2024). This was partly due to the suspension of access to international grant programs and funding. For instance, in March 2022 the European Commission halted the participation of Russian organizations in the Horizon Europe program and froze payments under existing contracts. At the same time, the members of the BRICS group work together to promote trade and economic development and have an active program of scientific cooperation (Mallapaty et al., 2022; Wang & Long, 2024).

These developments demonstrate that sanctions have a significant impact on global science, altering publication patterns, reshaping network connections, and promoting the emergence of new regional hubs (Matkovskaya, 2024; Milani & Pham, 2025; Zhang et al., 2025). However, empirical assessments of this effect have so far been mostly fragmentary, focusing on individual countries or institutions. A more comprehensive understanding requires a systematic analysis of international publishing flows, which can reveal not only the general decline in collaborative activity, but also the transformation of the very structure of scientific networks.

This paper presents a bibliometric analysis of publications related to semiconductors, one of the most research-intensive and strategically important high-tech sectors. This case is particularly illuminating: on the one hand, semiconductors are deeply embedded in global production chains; on the other, they have become central to sanctions policies, which makes them an ideal “indicator” of how political restrictions influence international scientific cooperation. The study seeks to trace the recent changes in the structure of co-authorship networks, identifying which countries and institutions lost prominence and which strengthened their positions in the global system.

3. Methodology and hypotheses

Drawing on theoretical perspectives of the impact of geopolitical factors on transnational scientific networks, we have formulated several hypotheses.

The first hypothesis posits that sanctions against Russia and related restrictions on academic cooperation have led to a decline in joint publications between the BRICS countries and leading Western scientific centers.

The second hypothesis suggests that under the sanctions pressure, polarization within scientific networks has intensified: the reduction in the BRICS linkages with the EU and the United States has been accompanied by growing collaboration among the BRICS countries and also with universities of the Global South — including the Middle East, Africa, and Southeast Asia.

The third hypothesis proposes that sanctions have facilitated the emergence of new peripheral nodes of international cooperation — such as universities in Saudi Arabia and Egypt — which previously played secondary roles but have since strengthened their presence in global publication networks.

To test these hypotheses, we conducted a bibliometric analysis of semiconductor-related publications, representing a strategically vital segment of high technology. The empirical base comprised data from the Web of Science Core Collection covering the period 1965–2025. Approximately 688 thousand publications containing the keyword semiconductor were identified. Two time periods were chosen for analysis: 2000–2021, characterized by relatively stable international cooperation, and 2022–2025, corresponding to the period of extensive sanctions.

The research methodology included constructing international co-authorship networks between countries and organizations using the VOSviewer software and the Python/NetworkX library for graph analysis.

VOSviewer constructs bibliometric networks based on a similarity matrix that reflect the strength of connections between elements such as authors, institutions, countries, or keywords. It processes data imported from Web of Science and computes link strength for each pair of elements according to the chosen analysis type — co-authorship, co-occurrence, co-citation, or bibliographic coupling. To ensure comparability, the software applies the association strength normalization, which compensates for differences in publication volume across nodes and produces a weighted network where vertices represent analytical objects and edges capture the intensity of their interactions. Node placement on the map is determined by the VOS algorithm, a modified multidimensional scaling technique that minimizes distances between strongly connected elements and increases distances between weakly connected ones, producing a stable and interpretable spatial layout. The software then applies modularity-based clustering (a variant of the Louvain algorithm) to identify groups of closely related elements. The visualization simultaneously conveys link strength via distances and edge thickness, and node relevance via size and colour, allowing users to analyze the structure of a research domain and identify its main participants (van Eck & Waltman, 2018).

The essential network-analysis metrics were calculated to assess the position of countries and institutions:

  • Degree centrality, reflecting the number of connections a node has;
  • Betweenness centrality, indicating a country’s or organization’s role in connecting clusters;
  • Closeness centrality, characterizing accessibility to other participants in the network; and
  • Eigenvector centrality, showing the overall influence within the global system.

Network clustering was also performed to identify the main research centers and evaluate their evolution over time.

The comparative approach enabled us to juxtapose network structures across the two time intervals and assess changes in link distribution. Special attention was given to the share of the BRICS joint publications with the United States and the EU, the dynamics of Chinese, Russian, and Indian institutions, and the rise of peripheral actors that had previously occupied marginal positions in global science.

We acknowledge the limitations of this approach: bibliometric data capture only a segment of research represented in international peer-reviewed journals and omit local studies, technical reports, and projects under embargo. Nevertheless, the use of the Web of Science database provides the most reliable and comparable dataset for analyzing the transformation of global scientific networks under sanctions pressure.

4. Results

4.1. Connections between countries and organizations with regard to co-authored research papers on semiconductors.

Based on affiliation and country data available in Web of Science, Figure 1 presents a network visualization of the connections between countries based on co-authored publications in the field of semiconductors. It shows the 100,000 most-cited joint publications from 2000 to 2025.

Figure 1. 

Joint scientific publications by researchers from different countries on the topic “semiconductors” — Network Visualization.

The size of each node reflects the number of joint papers written by authors from a given country (or organization) in collaboration with authors from another affiliation. It should be noted that in a network-based approach, the most significant participants are not necessarily the ones who are the most prolific or highly cited. They are those with the largest number of collaborative connections, i.e. with greater network influence, rather than purely academic productivity.

The VOSviewer clustering algorithm identifies 107 countries participating in scientific research, which are grouped into 10 clusters (Table 1).

Table 1.

Clusters of countries based on the collaborative activity of their affiliated researchers on the topic “semiconductors”

Cluster No. List of countries
1 Algeria, Azerbaijan, Bahrain, Bangladesh, Cameroon, Egypt, Ethiopia, Ghana, India, Indonesia, Iran, Iraq, Jordan, Kenya, Kuwait, Libya, Malaysia, Moldova, Morocco, Nigeria, Oman, Pakistan, Palestine, Philippines, Qatar, Romania, Saudi Arabia, Senegal, South Africa, Taiwan, Tajikistan, Tanzania, Thailand, Tunisia, Turkey, United Arab Emirates, Vietnam, Wales, Yemen, Zimbabwe
2 Austria, Belgium, Croatia, Czech Republic, Denmark, Estonia, Finland, Germany, Hungary, Israel, Italy, Latvia, Lebanon, Lithuania, Netherlands, Poland, Serbia, Slovakia, Slovenia, Sweden, Switzerland, Ukraine
3 Argentina, Armenia, Belarus, Brazil, Brunei, Chile, Colombia, Cuba, Ecuador, Iceland, Kazakhstan, Mexico, Norway, Peru, Portugal, Russia, Spain, Uruguay, Uzbekistan, Venezuela
4 Australia, Costa Rica, Japan, New Zealand, China, Singapore, Sri Lanka, United States
5 Canada, Côte d’Ivoire, France
6 Cyprus, Georgia, Greece, Ireland, Northern Ireland, Scotland
7 Bulgaria, Macedonia, North Macedonia
8 Nepal, South Korea
9 United Kingdom
10 Luxembourg

The first cluster is centered around India and Saudi Arabia; the second cluster around Germany, Italy, and Switzerland; the third cluster around Spain, Russia, and Brazil; the fourth cluster around China, the United States, and Japan. The fifth cluster is led by France, while the remaining clusters do not exhibit clearly defined central nodes.

In a similar manner, it is possible to analyze the connections between scientific organizations (in fact, these data serve as the primary source for the country-level information). According to the VOSviewer clustering algorithm, there are seven clusters of institutional collaboration within the scientific domain (Table 2).

Table 2.

Clusters of scientific organizations based on the collaborative activity of their affiliated researchers

Cluster No. Number of organizations Major research centers
1 398 University of Cambridge; Russian Academy of Sciences; Centre National de la Recherche Scientifique (CNRS), France; École Polytechnique Fédérale de Lausanne (EPFL), Switzerland; University of Oxford; Dresden University of Technology; National Research Council of Italy (CNR)
2 199 Chinese Academy of Sciences; University of the Chinese Academy of Sciences; Peking University; Tsinghua University; Nanyang Technological University; Nanjing University; Zhejiang University
3 167 University of California, Berkeley; Massachusetts Institute of Technology; Stanford University; University of California, Santa Barbara; National Renewable Energy Laboratory (NREL); Georgia Institute of Technology
4 96 Seoul National University; Yonsei University; Korea University; Sungkyunkwan University; Northwestern University (USA)
5 60 King Abdulaziz University (Saudi Arabia); King Saud University; Universiti Sains Malaysia (USM)
6 56 University of Tokyo; Tohoku University; Tokyo Institute of Technology; Osaka University; National Institute of Advanced Industrial Science and Technology (AIST); Kyoto University
7 23 Academia Sinica; Chang Gung University; Chung Yuan Christian University; Feng Chia University; Industrial Technology Research Institute (ITRI); Institute of Materials Research and Engineering; Institute of Microelectronics; King Abdullah University of Science and Technology (KAUST); National Central University; National Cheng Kung University; National Chiao Tung University; National Chung Hsing University; National Nano Device Laboratories; National Sun Yat-sen University; National Synchrotron Radiation Research Center; National Taipei University of Technology; National Taiwan Normal University; National Taiwan University; National Taiwan University of Science and Technology; National Tsing Hua University; Tamkang University; Yuan Ze University

Figure 2 shows a visualization of the connections between researchers from different institutes and universities, illustrating the clusters of organizations that most frequently collaborate with one another.

Figure 2. 

Joint publications by researchers from different scientific organizations on the topic “semiconductors”, 2000–2025, Network Visualization

The highest number of connections (joint scientific publications on the topic “semiconductors”) is observed for researchers affiliated with the Chinese Academy of Sciences and the French Centre National de la Recherche Scientifique (CNRS), followed by the U. S. Department of Energy, the University of California system, the Swiss Federal Institutes of Technology (ETH Domain), and the Russian Academy of Sciences. The same research organizations are also ranked at the top on the betweenness centrality metric.

At the country level, the highest values of degree centrality (total number of connections) are found for the United States, China, Germany, South Korea, and France.

The countries with the highest betweenness centrality values, which indicate their role as intermediaries connecting different parts of the network, are the United States, China, the United Kingdom, France, Italy, India, South Korea, and Turkey.

4.2. Joint scientific publications on semiconductors by authors from the BRICS Countries

The purpose of this study was to assess the current state of semiconductor research and examine how collaborative activities have evolved in recent years, primarily following the imposition of sanctions on certain BRICS countries, Iran and Russia in particular. We analyzed the patterns of collaboration among BRICS researchers over different time frames to determine if any significant changes had occurred.

Let us consider the institutional linkages among the BRICS countries for the period 2000–2021.

The most influential organization in this network, in terms of the total number of joint scientific publications, is the Chinese Academy of Sciences. During the specified period, they recorded 1,979 publications co-authored with researchers from other institutions (see Table A2, Appendix 1).

The Chinese Academy is followed by the Russian Academy of Sciences (1,555 publications) and the Centre National de la Recherche Scientifique (France) (1,077 articles).

Lower positions in the ranking, in descending order, are held by the Indian Institute of Technology system (India), the U. S. Department of Energy (DOE), the University of California System (USA), the Institute of Semiconductors, Chinese Academy of Sciences, the University of the Chinese Academy of Sciences (CAS), the Egyptian Knowledge Bank (EKB), and the Helmholtz Association (Germany).

In total, the number of joint publications authored by researchers from BRICS during the analyzed period amounts to 156,030, involving 108 participating countries within the scientific collaboration network.

The largest number of co-authored papers with authors from the BRICS countries belongs to China, followed by India, Russia, the United States, Germany, Iran, Brazil, Japan, the United Kingdom, and Egypt (see Table 3).

Table 3.

Number of joint publications with authors from the BRICS countries for the period 2000–2021 (based on the 100,000 most cited articles)

Country Number of joint publications … as a share of the total number of articles, % Citations
People’s R China 63885 41% 2674361
India 16169 10% 458442
Russia 10994 7% 235671
USA 8245 5% 578157
Germany 3808 2% 193891
Iran 3726 2% 102996
Brazil 3394 2% 87280
Japan 2534 2% 137755
England 2262 1% 119046
Egypt 2156 1% 53317
South Korea 1916 1% 86588
Singapore 1806 1% 106239
Australia 1763 1% 99840
Saudi Arabia 1737 1% 93466
France 1696 1% 60118
Canada 1191 1% 56425
Sweden 957 1% 43499
Taiwan 951 1% 37167
Italy 904 1% 37346
Spain 860 1% 36750
South Africa 803 1% 23268
Pakistan 607 0% 16612
Belgium 577 0% 27024
Poland 517 0% 19985
Netherlands 515 0% 23163
Switzerland 481 0% 26589
Finland 457 0% 11260
Ukraine 414 0% 8310
Malaysia 391 0% 11165
U Arab Emirates 387 0% 10561
Denmark 360 0% 15700
Turkey 343 0% 11538
Scotland 326 0% 15047
Czech Republic 283 0% 10333
Israel 275 0% 10986
Ireland 270 0% 14531
Portugal 262 0% 10634
Austria 250 0% 13939
Belarus 247 0% 5313
Vietnam 230 0% 6519
Mexico 196 0% 5886
Wales 192 0% 6182
Greece 154 0% 8116
Norway 146 0% 3904
Algeria 142 0% 3654
Iraq 116 0% 3141
Chile 108 0% 3168
Qatar 102 0% 2885
Thailand 96 0% 4290
Hungary 92 0% 2530
Tunisia 88 0% 1654
Romania 83 0% 3183
Nigeria 82 0% 1785
Colombia 77 0% 2056
Ethiopia 76 0% 1451
Iceland 75 0% 3210
New Zealand 70 0% 6974
Argentina 68 0% 2339
Estonia 58 0% 1261
Lithuania 57 0% 1112
Slovakia 57 0% 1120
Morocco 52 0% 1078
Bangladesh 49 0% 1165
Cuba 48 0% 761
Kazakhstan 46 0% 808
Uzbekistan 43 0% 868
North Ireland 43 0% 5154
Jordan 42 0% 999
Slovenia 40 0% 1253
Bulgaria 40 0% 1082
Moldova 40 0% 770
Yemen 39 0% 990
Lebanon 36 0% 644
Turkey 35 0% 258
Serbia 35 0% 502
Oman 33 0% 1191
Azerbaijan 32 0% 937
Latvia 28 0% 655
Indonesia 27 0% 466
Kuwait 26 0% 1298
Palestine 24 0% 495
Sudan 23 0% 189
Croatia 21 0% 482
Armenia 21 0% 312
Luxembourg 18 0% 303
Venezuela 18 0% 301
Uruguay 18 0% 303
Cameroon 17 0% 595
Bahrain 17 0% 450
Peru 17 0% 276
Botswana 14 0% 218
Zimbabwe 14 0% 260
Kenya 12 0% 168
Ghana 12 0% 641
Sri Lanka 11 0% 764
Georgia 11 0% 296
Libya 11 0% 307
Cyprus 10 0% 449
Senegal 9 0% 350
Philippines 7 0% 88
Ecuador 6 0% 50
Brunei 6 0% 97
Nepal 6 0% 228
Zambia 6 0% 105
Tanzania 6 0% 207
Namibia 6 0% 138
North Korea 6 0% 80
Mauritius 5 0% 45

Below is a visualization of the connections between researchers from various institutes and universities, illustrating the clusters of organizations that most frequently collaborate with one another (Figure 3).

Figure 3. 

Joint scientific publications by researchers from the BRICS countries on the topic “semiconductors”, 2000–2021.

According to the VOSviewer clustering algorithm, ten clusters of scientific collaboration were identified among the BRICS countries for the period 2000–2021.

The first and largest is a powerful Chinese cluster, whose gravitational field also included the United States, Australia, New Zealand, and North Korea.

The second cluster comprises India, Iran, Egypt, Saudi Arabia, and South Africa, along with numerous countries from the Middle East and North Africa.

The third cluster can be described as the “Russia–Germany–Italy–Eastern Europe–former USSR countries” cluster.

The fourth represents a “Japan–South Korea” cluster.

The fifth cluster is centered in Brazil, encompassing South American countries, Cuba, and Portugal.

There is also a distinct “Taiwan” cluster, along with several smaller ones.

4.3. Joint publication activity of researchers from BRICS countries after 2022

The Web of Science database contains 41,629 articles published by researchers from the BRICS countries since 2022, most of which are multi-author papers.

The most highly cited publication in this dataset is the joint article by Chinese researchers, titled “Inactive (PbI₂)₂RbCl stabilizes perovskite films for efficient solar cells” (Science, Vol. 377, Issue 6605, pp. 531–534, doi: 10.1126/science.abp8873).

During the 2022–2025 period, scientists from 95 countries co-authored publications with researchers from the BRICS nations. The list of the most active co-authoring countries has generally remained stable (see Table 4 and Table 3 for comparison with data for 2000–2021). However, in terms of joint publication activity, participation of the Western countries has declined noticeably.

Table 4.

Number of joint publications with authors from the BRICS countries for the period 2022–2025 (based on the 100,000 most cited articles)

Country Number of joint publications … as a share of the total number of articles, % Citations
People’s R China 29543 71% 173876
India 6110 15% 29497
Russia 2394 6% 6608
USA 2096 5% 18076
Saudi Arabia 1251 3% 10198
Iran 1232 3% 7346
Egypt 991 2% 6595
South Korea 988 2% 8423
Germany 894 2% 6678
Brazil 800 2% 2762
Japan 721 2% 6898
England 720 2% 5930
Australia 636 2% 8192
Taiwan 596 1% 4087
Singapore 534 1% 4949
Pakistan 479 1% 3461
France 404 1% 3174
Canada 399 1% 3507
U Arab Emirates 293 1% 1936
Italy 285 1% 2413
South Africa 283 1% 1563
Spain 275 1% 2556
Sweden 270 1% 2898
Malaysia 212 1% 2420
Turkey 209 1% 2367
Poland 200 0% 2036
Netherlands 164 0% 1072
Belgium 139 0% 1209
Switzerland 129 0% 1627
Scotland 129 0% 939
Denmark 120 0% 1169
Iraq 112 0% 1156
Austria 100 0% 916
Portugal 99 0% 772
Finland 99 0% 635
Algeria 94 0% 855
Czech Republic 94 0% 1023
Israel 93 0% 547
Ethiopia 93 0% 452
Tunisia 90 0% 587
Wales 88 0% 441
Ukraine 86 0% 512
Vietnam 79 0% 914
Belarus 75 0% 268
Chile 70 0% 537
Ireland 66 0% 388
Nigeria 64 0% 402
Norway 57 0% 265
Morocco 52 0% 398
Bangladesh 50 0% 487
Greece 50 0% 110
Uzbekistan 48 0% 392
Hungary 44 0% 447
Mexico 44 0% 327
Jordan 42 0% 130
Qatar 39 0% 227
Kazakhstan 38 0% 89
Palestine 30 0% 352
Lebanon 30 0% 179
Romania 29 0% 169
Sudan 28 0% 79
New Zealand 28 0% 240
Slovakia 27 0% 216
Colombia 26 0% 105
Indonesia 22 0% 115
Yemen 21 0% 125
Slovenia 20 0% 171
Kuwait 19 0% 58
Latvia 18 0% 94
Azerbaijan 16 0% 166
Cameroon 16 0% 57
Philippines 16 0% 63
Estonia 16 0% 81
Oman 15 0% 114
Nepal 15 0% 139
Armenia 14 0% 43
Bulgaria 13 0% 128
Serbia 13 0% 35
Peru 11 0% 16
North Ireland 11 0% 59
Lithuania 10 0% 164
Argentina 10 0% 31
Kenya 9 0% 20
Ecuador 8 0% 57
Croatia 8 0% 32
Luxembourg 7 0% 90
Afghanistan 7 0% 8
Ghana 7 0% 23
Brunei 6 0% 54
Myanmar 6 0% 8
Cuba 5 0% 24
Uruguay 5 0% 19

Thus, among the top ten most active co-authoring countries, the leading positions are now held by China, India, and Russia, followed by the United States, Saudi Arabia, Iran, Egypt, South Korea, Germany, and Brazil.

The top twenty also includes Pakistan, the United Arab Emirates, and South Africa.

In addition to the visualization of connections and clusters produced by VOSviewer, we calculated network metrics (two centrality measures1) for the largest nodes. Summary results for the periods before and after 2022 are presented in Tables 5 and 6 (Appendix 1). The highest values of total link strength are observed for the United States, China, Germany, South Korea, and France. High betweenness centrality is characteristic of the United States, China, the United Kingdom, France, Italy, India, South Korea, and Turkey.

The calculation of network metrics for the post-2022 scientific collaboration network shows that the Chinese Academy of Sciences, the Indian Institute of Technology System (IIT System), the University of the Chinese Academy of Sciences, the Russian Academy of Sciences, and the Egyptian Knowledge Bank (EKB) remain the institutions with the highest number of connections (see Table A1).

Other leading organizations in terms of joint publication activity include Zhejiang University, the Centre National de la Recherche Scientifique (CNRS), the Institute of Semiconductors (CAS), the University of Science and Technology of China (CAS), and the United States Department of Energy (DOE).

For the first time, two Saudi Arabian universities — King Saud University and King Khalid University — as well as the National Institute of Technology (NIT System, India) entered the top 20 institutions by total number of connections.

To better understand the changes in collaborative publication activity over the past three years, we compared the network metrics of BRICS research organizations before and after 2022.

The top three institutions that recorded the largest decline in joint publications were all Russian: the Russian Academy of Sciences, the St. Petersburg Scientific Centre of the Russian Academy of Sciences, and the Ioffe Physical Technical Institute.

Conversely, the scientometric indicators of most Chinese and Indian universities and research institutions improved.

The top ten institutions showing the strongest growth in joint publication activity include not only Chinese and Indian centers but also several universities and research hubs from Saudi Arabia and Egypt:

  • Chinese Academy of Sciences (China)
  • King Khalid University (Saudi Arabia)
  • University of the Chinese Academy of Sciences, CAS (China)
  • King Saud University (Saudi Arabia)
  • Indian Institute of Technology System (India)
  • Zhejiang University (China)
  • Egyptian Knowledge Bank (Egypt)
  • Saveetha Institute of Medical & Technical Sciences (India)
  • Princess Nourah bint Abdulrahman University (Saudi Arabia)
  • Chandigarh University (India)

It is noteworthy that these institutions not only increased their number of connections, but also improved their betweenness centrality scores, further consolidating their positions as local centers of knowledge creation and transfer.

The influence and significance of many Western — particularly American and European — research centers in terms of collaboration with the BRICS countries decreased as expected.

The level of connectivity with researchers from the United States, EU countries, Japan, and Taiwan declined sharply; these countries deteriorated in terms of network metrics, reflecting a loss of intermediary and integrative functions in the global research landscape.

Although countries’ positions in the ranked list of co-publication counts changed very little (the Spearman rank correlation coefficient is 0.94, significant at the 0.01 level), China’s role as a major node in the scientific publication network increased substantially after 2022 (see Table A2). This applies both to its share of total scientific links and to its betweenness centrality.

When the diverse dynamics of all scientific organizations are aggregated at the country level, the results show a substantial strengthening of China’s role as the largest node within the global publication network.

This applies both to its share of total network connections and to its betweenness centrality, reflecting an increased capacity to connect diverse parts of the network.

Other countries that improved their positions include Saudi Arabia, India, Sweden, Pakistan, Slovenia, Egypt, Iran, Vietnam, South Korea, Australia, Malaysia, Iraq, Lebanon, Morocco, Bangladesh, the United Arab Emirates, Palestine, Uzbekistan, and Nepal.

All of these nations intensified their collaborative scientific activity within the BRICS network and their respective regional clusters.

5. Discussion

This paper’s findings show that significant changes have also occurred in the overall network landscape.

An analysis of the interactions between the BRICS countries and the nations of East, Asia, and Africa reveals several notable trends:

  • China plays a key role in the network, maintaining active collaboration with all the other BRICS members — especially India and Russia — and sustaining a broad range of ties with countries across East, Asia, and Africa. As before 2022, China continues to strengthen its cooperation with South Korea, Japan, Indonesia, Singapore, and with South Africa and Egypt on the African continent. India is strengthening its engagement with the developing world and working closely with other countries in the BRICS group, particularly China and Russia. Its growing cooperation with Asian partners, such as Iran, South Korea, and Saudi Arabia, indicates the increasing influence of India in the region. The second network visualization shows India's even greater integration with regional and global networks.
  • Russia occupies a major position within the “green cluster,” maintaining cooperation not only with China and India but also with several European countries (notably Germany and France) and selected Eastern and Asian partners, including South Africa and Egypt. After 2022, Russia retained its core position within the green cluster, but its interactions with Asian countries have become less visible compared to China and India.
  • South Africa functions as a key node for the African continent and maintains strong collaboration with other BRICS member countries, especially China and India. It also maintains active ties with other African countries such as Nigeria and Egypt. Since 2022, these links have intensified, highlighting the growing role of South Africa in Asia–Africa scientific collaboration.
  • Brazil’s interactions with Asian countries remain less pronounced than those of the other BRICS members, suggesting that its cooperation continues to focus primarily on European and American partners.
  • A noticeable rise is observed in the influence of countries such as Indonesia, Thailand, Malaysia and the Philippines, which have become more integrated into the global scientific collaboration network. This is particularly evident through their connections with China and India.
  • Collaboration between the BRICS countries and African nations (South Africa, Egypt, Nigeria, and Ethiopia) remains substantial, with China and India playing the leading roles in these partnerships.

Overall, the bibliometric analysis confirmed the initial hypotheses and revealed substantial structural changes in international scientific collaboration following the imposition of sanctions.

First, the role of China as the central node of the global publication network has strengthened markedly. The Chinese Academy of Sciences (CAS) has become the largest institution in terms of co-authored works, maintaining active partnerships with the BRICS members and with several countries of the Global South.

Whereas CAS was already a leading center before 2022, the centrality metrics of CAS have further increased since sanctions were introduced. The number of joint publications with India, Russia, Saudi Arabia, and Egypt has risen significantly. This demonstrates that China is gradually taking on the role of an integrator in international research networks, especially in the face of the weakening of traditional Western actors. Second, the analysis indicates a sharp decline in collaboration between the BRICS countries and Western scientific centers. The share of joint publications with researchers from the United States and the European Union has decreased by nearly half, as evidenced by the drop in betweenness centrality for countries such as Germany, Japan and Britain. Where these nations once served as bridges connecting different clusters, the linking function has shifted increasingly towards China and India since 2022.

This trend reflects a structural fragmentation of the global scientific network. Instead of a single, integrated core, there are now multiple regional clusters forming.

Third, the period under review shows the rising importance of Global South countries as emerging peripheral nodes of scientific collaboration. Universities in Saudi Arabia (e.g., King Saud University, King Khalid University) and Egypt (Egyptian Knowledge Bank and other centers) are now among the top 20 global partners in joint publications with institutions from the BRICS countries. Only a few years ago, these organizations were peripheral to the network and played a limited role in semiconductor research. Their rapid ascent can be explained by the reallocation of international research efforts towards countries not subject to sanctions.

Russia occupies a special place in this analysis. The Russian Academy of Sciences, which ranked among the most prominent network participants in the 2000-2021 period, showed a substantial decline in co-authored publications after 2022 — from more than 1,500 to roughly 700. Particularly sharp was the drop in collaboration with European institutions, which previously accounted for a significant share of Russia's international linkages.

Although Russia has maintained active cooperation with China and India and expanded contacts with Middle Eastern universities, the overall dynamics suggest a reduction in Russia’s role in the global scientific system and its gradual shift toward the periphery.

Taken together, the results confirm the polarization of global science. Sanctions have led to decreased network connectivity, weakened traditional nodes, increased participation of the Global South countries and the rise of new centers of influence based in China and India.

The global scientific system in semiconductor research appears to be entering a phase of structural transformation — from an integrated global network towards a constellation of regional clusters, each with its own core and sphere of influence.

6. Conclusions

The analysis shows that the sanctions against Russia, and their indirect effects on the BRICS countries, have become a significant factor in driving the transformation of the global science system in the area of semiconductor research.

Before 2022, global science was characterized by increasing integration into a unified network with relatively dense linkages between Western countries and emerging economies.

However, the trend has now reversed towards fragmentation and polarization.

1. First, the results support the hypothesis that there has been a decline in the number of co-authored publications between the BRICS countries and Western countries. Restrictions on access to international grants, the termination of partnerships and barriers to the exchange of equipment and data have all contributed to a reduction in scientific cooperation and a decrease in publication activity.

2. Second, under the pressure of sanctions, polarization of international scientific network intensified. Western countries have partly lost their intermediary role, while China and India increasingly assumed integral functions. This led to the emergence of new regional centers and a shift in emphasis towards the Global South.

3. Third, sanctions have stimulated the rise of new peripheral nodes.

4. Countries such as Saudi Arabia and Egypt, previously peripheral, have significantly strengthened their positions owing to the reallocation of research flows and targeted policies to develop science and innovation.

For Russia, the effects have been predominantly negative. The sharp decline in joint publications with the EU and the United States weakened its position in the global scientific network. Cooperation with China and India, which has been maintained, created a dependence on a limited number of partners and increased the risk of long-term scientific isolation.

On the whole, sanctions have not only reduced the connectivity of international science but also accelerated its structural transformation. The global scientific system is shifting from a formerly integrated network toward a regionalized architecture with distinct centers and zones of influence.

This supports the broader thesis that science is increasingly influenced by geopolitical and geoeconomic factors, with international cooperation closely linked to issues of global security and technological independence.

This study has certain limitations that suggest directions for future research. It inevitably operates within several methodological constraints, some of which arise from conscious decisions we made when developing a general approach to mapping the global scientific network.

First, our reliance on a subset of 100,000 highly cited publications puts the spotlight on established scientific powers and old papers — a familiar side-effect of citation-based selection. Expanding the dataset downward would, of course, include more recent and more diverse works, but it would also blur the comparability of periods and inject a large amount of noise. In this sense, the approach is less about capturing every single collaborative tie and more about ensuring that the structural contours of the network remain interpretable (and replicable).

Second, we did not implement extended keyword harmonization or semantic clustering, even though semiconductor research spans everything from perovskite solar cells to nanoelectronics. Such refinements could certainly reduce thematic “spillover,” but they would also shift the study from macro-mapping to field-level micro-taxonomy — a task for a different paper and, ideally, a different coffee supply.

A related limitation concerns the use of full counts for international co-authorships. Fractional counting often produces a more conservative and “fair” representation of contributions, but switching to this method mid-analysis disrupts comparability across different time periods and institutions. Since our goal was to outline a methodological pathway rather than adjudicate credit allocation in large multi-author teams, we preserved the full-counting logic as the simplest and most transparent option. Equally important is the fact that the Web of Science only captures the visible tip of global research. It leaves out local journals, industrial research and projects covered by confidentiality and export control regimes — an omission that is especially relevant for semiconductor research where classified and proprietary work takes up a large share of real effort. WoS indexing also expanded in the early 2020s, particularly for journals from the Global South, which means that part of the “rise” observed among new regional hubs may reflect adjustments in the database rather than dramatic shifts in scientific behavior.

Another limitation lies in the inherent difficulty of separating short-term geopolitical shocks from long-term structural trends. China’s ascent in the global collaboration networks began well before 2022. Although sanctions amplified the rate of reconfiguration, they were not its sole cause. Our methodological design allows us to trace transformations in co-authorship networks, but not to fully disentangle the share attributable to sanctions from other significant shifts in the system of global science. The clustering logic of VOSviewer adds its own subtleties: cluster boundaries depend on resolution parameters and threshold settings, and small adjustments may shift cluster composition at the margins. Finally, the presence of organizations with multiple or fragmented affiliations (multi-campus systems, hybrid institutes, or national labs) leads to a certain granularity that no bibliometric tool has yet fully resolved.

Taken together, these limitations do not reflect shortcomings in the approach, but rather the inherent constraints of any attempt to map a rapidly evolving, unevenly indexed, geopolitically influenced scientific landscape. Put differently, our goal was not to provide the final word on semiconductor collaboration, but to demonstrate a robust way of thinking about it — even if the global science system is moving faster than any of us (or any reviewer) might prefer.

Aknowlegement

The study is supported by the Russian Science Foundation grant № 25-18-00075, https://rscf.ru/project/25-18-00075/

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Appendix 1

Table A1.

Comparison of network metrics for organizations that have co-publications with researchers from the BRICS countries before 2022 and after 2022 (the degree metric is measured as a share of the total number of co-publications for comparability)

Before 2022 After 2022 Before 2022 After 2022
degree. % degree. % betweenness centrality betweenness centrality Δ [degree. %] Δ [betweenness centrality]
Chinese Academy of Sciences (China) 0.79% 1.05% 0.008 0.009 0.3% 0.14%
Russian Academy of Sciences (Russia) 0.62% 0.49% 0.005 0.004 -0.1% -0.08%
Centre National de la Recherche Scientifique (CNRS) (France) 0.43% 0.44% 0.002 0.002 0.0% 0.02%
Indian Institute of Technology System (IIT System) (India) 0.42% 0.58% 0.003 0.004 0.2% 0.12%
United States Department of Energy (DOE) (USA) 0.41% 0.35% 0.001 0.001 -0.1% -0.05%
University of California System (USA) 0.38% 0.30% 0.001 0.001 -0.1% -0.04%
Institute of Semiconductors. CAS (China) 0.36% 0.40% 0.001 0.001 0.0% -0.02%
University of Chinese Academy of Sciences. CAS (China) 0.36% 0.53% 0.001 0.001 0.2% 0.05%
Egyptian Knowledge Bank (EKB) (Egypt) 0.34% 0.49% 0.003 0.003 0.1% 0.09%
Helmholtz Association (Germany) 0.32% 0.23% 0.001 0.000 -0.1% -0.03%
Tsinghua University (China) 0.30% 0.34% 0.001 0.001 0.0% 0.01%
Peking University (China) 0.30% 0.32% 0.001 0.001 0.0% -0.01%
Zhejiang University (China) 0.29% 0.44% 0.001 0.001 0.2% 0.07%
University of Science & Technology of China. CAS (China) 0.29% 0.36% 0.000 0.001 0.1% 0.02%
St. Petersburg Scientific Centre of the Russian Academy of Sciences (Russia) 0.28% 0.16% 0.000 0.000 -0.1% -0.03%
Ioffe Physical Technical Institute (Russia) 0.27% 0.16% 0.000 0.000 -0.1% -0.02%
Max Planck Society (Germany) 0.27% 0.18% 0.001 0.000 -0.1% -0.03%
Nanjing University (China) 0.26% 0.30% 0.001 0.001 0.0% 0.00%
Swiss Federal Institutes of Technology Domain (Швейцария) 0.26% 0.19% 0.000 0.000 -0.1% -0.03%
Rzhanov Institute of Semiconductor Physics. Siberian Branch. Russian Academy of Sciences (Russia) 0.26% 0.17% 0.001 0.000 -0.1% -0.02%
Nanyang Technological University (Singapore) 0.26% 0.24% 0.001 0.000 0.0% -0.01%
Fudan University (China) 0.24% 0.30% 0.000 0.001 0.1% 0.02%
Council of Scientific & Industrial Research (CSIR) — India (India) 0.24% 0.21% 0.001 0.001 0.0% -0.05%
Jilin University (China) 0.24% 0.25% 0.001 0.001 0.0% 0.00%
Shanghai Jiao Tong University (China) 0.24% 0.25% 0.000 0.000 0.0% -0.01%
Xi’an Jiaotong University (China) 0.23% 0.30% 0.000 0.001 0.1% 0.03%
University of Electronic Science & Technology of China (China) 0.23% 0.30% 0.000 0.001 0.1% 0.04%
Consiglio Nazionale delle Ricerche (CNR) (Италия) 0.23% 0.17% 0.000 0.000 -0.1% 0.00%
Institute of Physics. CAS (China) 0.23% 0.20% 0.000 0.000 0.0% -0.01%
National University of Singapore (Singapore) 0.22% 0.21% 0.001 0.000 0.0% -0.01%
City University of Hong Kong (Hong Kong) 0.22% 0.25% 0.000 0.000 0.0% -0.02%
Huazhong University of Science & Technology (China) 0.22% 0.27% 0.001 0.001 0.1% 0.00%
Lomonosov Moscow State University (Russia) 0.22% 0.16% 0.000 0.000 -0.1% 0.00%
Shenzhen University (China) 0.22% 0.32% 0.000 0.001 0.1% 0.03%
Tianjin University (China) 0.22% 0.24% 0.000 0.000 0.0% 0.01%
Xiamen University (China) 0.21% 0.21% 0.000 0.000 0.0% -0.01%
National Institute of Technology (NIT System) (India) 0.21% 0.31% 0.002 0.002 0.1% 0.03%
Soochow University — China (China) 0.21% 0.24% 0.000 0.000 0.0% -0.01%
University of Texas System (USA) 0.21% 0.15% 0.000 0.000 -0.1% 0.01%
University of Cambridge (United Kingdom) 0.21% 0.16% 0.000 0.000 0.0% -0.01%
National Academy of Sciences Ukraine (Ukraine) 0.20% 0.10% 0.000 0.000 -0.1% -0.02%
Lawrence Berkeley National Laboratory (USA) 0.20% 0.16% 0.000 0.000 0.0% -0.01%
Universite Paris Saclay (France) 0.20% 0.13% 0.000 0.000 -0.1% -0.02%
Shandong University (China) 0.20% 0.26% 0.000 0.000 0.1% 0.01%
University System of Georgia (USA) 0.20% 0.12% 0.000 0.000 -0.1% -0.01%
Indian Institute of Science (IISC) — Bangalore (India) 0.19% 0.18% 0.001 0.000 0.0% -0.02%
University of California Berkeley (USA) 0.19% 0.14% 0.000 0.000 -0.1% -0.01%
Consejo Superior de Investigaciones Cientificas (CSIC) (Spain) 0.19% 0.14% 0.000 0.000 -0.1% -0.02%
State University System of Florida (USA) 0.19% 0.17% 0.000 0.000 0.0% -0.01%
Harbin Institute of Technology (China) 0.19% 0.27% 0.000 0.000 0.1% 0.01%
Sun Yat Sen University (China) 0.18% 0.24% 0.000 0.000 0.1% 0.01%
Department of Science & Technology (India) 0.18% 0.15% 0.001 0.000 0.0% -0.03%
Saint Petersburg State University (Russia) 0.18% 0.12% 0.000 0.000 -0.1% -0.01%
Southern University of Science & Technology (China) 0.18% 0.28% 0.000 0.000 0.1% 0.03%
Novosibirsk State University (Russia) 0.18% 0.12% 0.000 0.000 -0.1% -0.01%
University System of Ohio (USA) 0.18% 0.13% 0.000 0.000 -0.1% 0.00%
ITMO University (Russia) 0.18% 0.12% 0.000 0.000 -0.1% -0.01%
National Institute for Materials Science (Japan) 0.18% 0.24% 0.000 0.000 0.1% 0.01%
Wuhan University (China) 0.17% 0.21% 0.000 0.000 0.0% 0.00%
Chinese Academy of Engineering Physics (China) 0.17% 0.14% 0.000 0.000 0.0% -0.01%
Georgia Institute of Technology (USA) 0.17% 0.11% 0.000 0.000 -0.1% -0.01%
Hong Kong University of Science & Technology (Hong Kong) 0.17% 0.16% 0.000 0.000 0.0% -0.01%
Dalian University of Technology (China) 0.17% 0.16% 0.000 0.000 0.0% 0.00%
King Saud University (Saudi Arabia) 0.17% 0.34% 0.001 0.002 0.2% 0.12%
University of London (United Kingdom) 0.17% 0.15% 0.000 0.000 0.0% -0.01%
Southeast University — China (China) 0.17% 0.23% 0.000 0.000 0.1% 0.02%
Beihang University (China) 0.17% 0.19% 0.000 0.000 0.0% 0.00%
Beijing Institute of Technology (China) 0.17% 0.24% 0.000 0.000 0.1% 0.01%
Massachusetts Institute of Technology (MIT) (USA) 0.16% 0.14% 0.000 0.000 0.0% 0.00%
University of Tokyo (Japan) 0.16% 0.16% 0.000 0.000 0.0% 0.00%
Universidade Estadual de Campinas (Бразилия) 0.16% 0.07% 0.001 0.000 -0.1% -0.03%
CEA (France) 0.16% 0.09% 0.000 0.000 -0.1% 0.00%
Technische Universitat Dresden (Germany) 0.16% 0.14% 0.000 0.000 0.0% 0.00%
Universidade de Sao Paulo (Бразилия) 0.16% 0.08% 0.001 0.000 -0.1% -0.01%
Nankai University (China) 0.16% 0.19% 0.000 0.000 0.0% 0.02%
University of Science & Technology Beijing (China) 0.16% 0.17% 0.000 0.000 0.0% 0.01%
Stanford University (USA) 0.16% 0.15% 0.000 0.000 0.0% 0.00%
South China University of Technology (China) 0.15% 0.22% 0.000 0.000 0.1% 0.02%
State University of New York (SUNY) System (USA) 0.15% 0.12% 0.000 0.000 0.0% -0.01%
Universite Paris Cite (France) 0.15% 0.14% 0.000 0.000 0.0% -0.01%
Communaute Universite Grenoble Alpes (France) 0.15% 0.06% 0.000 0.000 -0.1% -0.01%
Ecole Polytechnique Federale de Lausanne (Швейцария) 0.15% 0.12% 0.000 0.000 0.0% -0.01%
Polish Academy of Sciences (Poland) 0.15% 0.10% 0.000 0.000 -0.1% 0.00%
Shanghai University (China) 0.15% 0.22% 0.000 0.000 0.1% 0.02%
Universite Grenoble Alpes (UGA) (France) 0.15% 0.05% 0.000 0.000 -0.1% -0.01%
Pennsylvania Commonwealth System of Higher Education (PCSHE) (USA) 0.15% 0.13% 0.000 0.000 0.0% 0.00%
Institute of Chemistry. CAS (China) 0.15% 0.17% 0.000 0.000 0.0% 0.00%
University of Texas Austin (USA) 0.15% 0.08% 0.000 0.000 -0.1% 0.00%
Northwestern Polytechnical University (China) 0.14% 0.24% 0.000 0.000 0.1% 0.03%
Zhengzhou University (China) 0.14% 0.22% 0.000 0.000 0.1% 0.02%
Wuhan University of Technology (China) 0.14% 0.14% 0.000 0.000 0.0% 0.00%
CNRS — Institute of Physics (INP) (France) 0.14% 0.09% 0.000 0.000 -0.1% -0.01%
Hong Kong Polytechnic University (Hong Kong) 0.14% 0.18% 0.000 0.000 0.0% 0.00%
Argonne National Laboratory (USA) 0.14% 0.12% 0.000 0.000 0.0% 0.00%
Xidian University (China) 0.14% 0.19% 0.000 0.000 0.0% 0.02%
King Abdulaziz University (Saudi Arabia) 0.14% 0.16% 0.000 0.000 0.0% -0.01%
Helmholtz-Zentrum fuer Materialien und Energie GmbH (HZB) (Germany) 0.14% 0.06% 0.000 0.000 -0.1% -0.01%
Hunan University (China) 0.14% 0.23% 0.000 0.000 0.1% 0.01%
National Taiwan University (Taiwan) 0.14% 0.09% 0.000 0.000 0.0% -0.01%
Tongji University (China) 0.14% 0.10% 0.000 0.000 0.0% -0.01%
CNRS — Institute of Chemistry (INC) (France) 0.14% 0.14% 0.000 0.000 0.0% 0.00%
Omsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences (Russia) 0.14% 0.12% 0.000 0.000 0.0% 0.00%
Imperial College London (United Kingdom) 0.14% 0.14% 0.000 0.000 0.0% 0.01%
National Research Centre — Kurchatov Institute (Russia) 0.14% 0.06% 0.000 0.000 -0.1% -0.01%
King Abdullah University of Science & Technology (Saudi Arabia) 0.14% 0.16% 0.000 0.000 0.0% 0.01%
Moscow Institute of Physics & Technology (Russia) 0.14% 0.11% 0.000 0.000 0.0% 0.00%
Oak Ridge National Laboratory (USA) 0.14% 0.09% 0.000 0.000 0.0% 0.00%
Ministry of Education & Science of Ukraine (Ukraine) 0.14% 0.09% 0.000 0.000 0.0% -0.01%
Northwestern University (USA) 0.14% 0.12% 0.000 0.000 0.0% 0.00%
Royal Institute of Technology (Sweden) 0.13% 0.08% 0.000 0.000 -0.1% -0.01%
Chongqing University (China) 0.13% 0.19% 0.000 0.000 0.1% 0.02%
National University of Science & Technology (MISIS) (Russia) 0.13% 0.12% 0.000 0.000 0.0% 0.00%
Chinese University of Hong Kong (Hong Kong) 0.13% 0.11% 0.000 0.000 0.0% -0.01%
Tohoku University (Japan) 0.13% 0.09% 0.000 0.000 0.0% -0.01%
Lashkaryov Institute of Semiconductor Physics (Ukraine) 0.13% 0.04% 0.000 0.000 -0.1% -0.02%
Fuzhou University (China) 0.13% 0.16% 0.000 0.000 0.0% 0.00%
United States Department of Defense (USA) 0.13% 0.05% 0.000 0.000 -0.1% -0.01%
Agency for Science Technology & Research (A*STAR) (Singapore) 0.13% 0.12% 0.000 0.000 0.0% 0.00%
Nanjing University of Science & Technology (China) 0.13% 0.20% 0.000 0.000 0.1% 0.02%
University of Hong Kong (Hong Kong) 0.13% 0.16% 0.000 0.000 0.0% 0.00%
National Center for Nanoscience & Technology. CAS (China) 0.13% 0.11% 0.000 0.000 0.0% 0.00%
Indian Institute of Technology (IIT) — Bombay (India) 0.13% 0.08% 0.000 0.000 0.0% -0.01%
Dongguk University (S.Korea) 0.13% 0.12% 0.000 0.000 0.0% 0.00%
Central South University (China) 0.13% 0.18% 0.000 0.000 0.1% 0.02%
Hefei Institutes of Physical Science. CAS (China) 0.13% 0.12% 0.000 0.000 0.0% 0.00%
Sichuan University (China) 0.13% 0.18% 0.000 0.000 0.1% 0.01%
University of New South Wales Sydney (Australia) 0.13% 0.13% 0.000 0.000 0.0% 0.00%
National Yang Ming Chiao Tung University (Taiwan) 0.13% 0.16% 0.000 0.000 0.0% 0.02%
University College London (United Kingdom) 0.12% 0.10% 0.000 0.000 0.0% 0.00%
University of California Los Angeles (USA) 0.12% 0.08% 0.000 0.000 0.0% 0.00%
Uppsala University (Sweden) 0.12% 0.10% 0.000 0.000 0.0% 0.00%
Tomsk State University (Russia) 0.12% 0.09% 0.000 0.000 0.0% -0.01%
East China Normal University (China) 0.12% 0.15% 0.000 0.000 0.0% 0.00%
Shanghai Institute of Ceramics. CAS (China) 0.12% 0.10% 0.000 0.000 0.0% 0.00%
Russian Academy of Science Lebedev Physical Institute (Russia) 0.12% 0.08% 0.000 0.000 0.0% 0.00%
Sungkyunkwan University (SKKU) (S.Korea) 0.12% 0.15% 0.000 0.000 0.0% 0.01%
Sorbonne Universite (France) 0.12% 0.09% 0.000 0.000 0.0% 0.00%
Linkoping University (Sweden) 0.12% 0.12% 0.000 0.000 0.0% 0.01%
Beijing Computational Science Research Center (CSRC) (China) 0.12% 0.08% 0.000 0.000 0.0% 0.00%
Beijing University of Technology (China) 0.12% 0.14% 0.000 0.000 0.0% 0.00%
National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) (Russia) 0.12% 0.09% 0.000 0.000 0.0% 0.00%
Research Center Julich (Germany) 0.12% 0.07% 0.000 0.000 -0.1% 0.00%
University of Oxford (United Kingdom) 0.12% 0.15% 0.000 0.000 0.0% 0.00%
Rice University (USA) 0.12% 0.07% 0.000 0.000 0.0% -0.01%
Lanzhou University (China) 0.12% 0.15% 0.000 0.000 0.0% 0.01%
University of California Santa Barbara (USA) 0.12% 0.09% 0.000 0.000 0.0% 0.00%
Shanghai Institute of Microsystem & Information Technology. CAS (China) 0.11% 0.12% 0.000 0.000 0.0% 0.00%
University of Michigan System (USA) 0.11% 0.10% 0.000 0.000 0.0% 0.00%
University of Michigan (USA) 0.11% 0.10% 0.000 0.000 0.0% 0.00%
National Institute of Advanced Industrial Science & Technology (AIST) (Japan) 0.11% 0.06% 0.000 0.000 0.0% -0.01%
Columbia University (USA) 0.11% 0.07% 0.000 0.000 0.0% 0.00%
Brookhaven National Laboratory (USA) 0.11% 0.06% 0.000 0.000 -0.1% 0.00%
Nanjing Tech University (China) 0.11% 0.15% 0.000 0.000 0.0% 0.01%
Texas A&M University System (USA) 0.11% 0.07% 0.000 0.000 0.0% 0.00%
Jiangsu University (China) 0.11% 0.16% 0.000 0.000 0.0% 0.01%
National Academy of Sciences of Belarus (NASB) (Беларусь) 0.11% 0.07% 0.000 0.000 0.0% 0.00%
Pennsylvania State University (USA) 0.11% 0.10% 0.000 0.000 0.0% 0.00%
CNRS — Institute for Engineering & Systems Sciences (INSIS) (France) 0.11% 0.08% 0.000 0.000 0.0% 0.00%
Istituto Nazionale di Fisica Nucleare (INFN) (Италия) 0.11% 0.06% 0.000 0.000 -0.1% -0.01%
University of St Andrews (United Kingdom) 0.11% 0.04% 0.000 0.000 -0.1% -0.01%
Purdue University System (USA) 0.11% 0.10% 0.000 0.000 0.0% 0.00%
Indian Institute of Technology (IIT) — Delhi (India) 0.11% 0.12% 0.000 0.000 0.0% 0.00%
Aalto University (Finland) 0.11% 0.07% 0.000 0.000 0.0% -0.01%
Purdue University (USA) 0.11% 0.10% 0.000 0.000 0.0% 0.00%
University of Wurzburg (Germany) 0.11% 0.06% 0.000 0.000 -0.1% 0.00%
Arizona State University (USA) 0.11% 0.09% 0.000 0.000 0.0% 0.00%
Islamic Azad University (Iran) 0.11% 0.11% 0.000 0.000 0.0% 0.00%
University of Toronto (Canada) 0.11% 0.08% 0.000 0.000 0.0% -0.01%
Karlsruhe Institute of Technology (Germany) 0.11% 0.08% 0.000 0.000 0.0% 0.00%
University of Illinois System (USA) 0.11% 0.06% 0.000 0.000 0.0% 0.00%
Institute of High Energy Physics. CAS (China) 0.11% 0.12% 0.000 0.000 0.0% 0.00%
ETH Zurich (Швейцария) 0.11% 0.08% 0.000 0.000 0.0% 0.00%
Fujian Institute of Research on the Structure of Matter. CAS (China) 0.11% 0.12% 0.000 0.000 0.0% 0.00%
Arizona State University-Tempe (USA) 0.11% 0.09% 0.000 0.000 0.0% 0.00%
North Carolina State University (USA) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Prokhorov General Physics Institute of the Russian Academy of Sciences (Russia) 0.10% 0.06% 0.000 0.000 0.0% 0.00%
South China Normal University (China) 0.10% 0.17% 0.000 0.000 0.1% 0.01%
RIKEN (Japan) 0.10% 0.08% 0.000 0.000 0.0% -0.01%
Australian National University (Australia) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Czech Academy of Sciences (Czech Republic) 0.10% 0.07% 0.000 0.000 0.0% -0.01%
Dalian Institute of Chemical Physics. CAS (China) 0.10% 0.12% 0.000 0.000 0.0% 0.00%
Texas A&M University College Station (USA) 0.10% 0.06% 0.000 0.000 0.0% -0.01%
Institute of Physics — Polish Academy of Sciences (Poland) 0.10% 0.02% 0.000 0.000 -0.1% -0.01%
Changchun Institute of Optics. Fine Mechanics & Physics. CAS (China) 0.10% 0.09% 0.000 0.000 0.0% 0.00%
Pennsylvania State University — University Park (USA) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Los Alamos National Laboratory (USA) 0.10% 0.06% 0.000 0.000 0.0% 0.00%
University of Manchester (United Kingdom) 0.10% 0.09% 0.000 0.000 0.0% 0.00%
Bhabha Atomic Research Center (BARC) (India) 0.10% 0.07% 0.000 0.000 0.0% -0.01%
Seoul National University (SNU) (S.Korea) 0.10% 0.12% 0.000 0.000 0.0% 0.00%
University of Basque Country (Spain) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Harvard University (USA) 0.10% 0.07% 0.000 0.000 0.0% 0.00%
Shanghai Institute of Technical Physics. CAS (China) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Institute for Basic Science — Korea (IBS) (S.Korea) 0.10% 0.07% 0.000 0.000 0.0% 0.00%
Japan Science & Technology Agency (JST) (Japan) 0.10% 0.02% 0.000 0.000 -0.1% -0.01%
Pohang University of Science & Technology (POSTECH) (S.Korea) 0.10% 0.10% 0.000 0.000 0.0% 0.00%
King Khalid University (Saudi Arabia) 0.10% 0.32% 0.000 0.001 0.2% 0.12%
Technical University of Munich (Germany) 0.10% 0.10% 0.000 0.000 0.0% 0.00%
Princeton University (USA) 0.10% 0.08% 0.000 0.000 0.0% 0.00%
Interuniversity Microelectronics Centre (IMEC) (Belgium) 0.10% 0.06% 0.000 0.000 0.0% -0.01%
Ural Federal University (Russia) 0.10% 0.14% 0.000 0.000 0.0% 0.03%
Table A2.

Comparison of network metrics for organizations that have co-publications with researchers from BRICS countries before 2022 and after 2022, by country (the degree metric is measured as a share of the total number of co-publications for comparability).

Before 2022 After 2022 Before 2022 After 2022
degree. % degree. % betweenness centrality betweenness centrality Δ [degree. %] Δ [betweenness centrality]
peoples r china 17.2% 38.5% 0.044 0.104 21.2% 6.0%
usa 22.8% 11.1% 0.063 0.080 -11.7% 1.7%
south korea 6.0% 6.0% 0.019 0.026 0.1% 0.7%
saudi arabia 1.1% 4.6% 0.014 0.099 3.5% 8.4%
india 2.3% 3.6% 0.025 0.062 1.3% 3.7%
germany 6.4% 2.8% 0.022 0.051 -3.6% 2.9%
japan 5.7% 2.7% 0.021 0.019 -2.9% -0.2%
england 3.1% 2.1% 0.039 0.013 -1.0% -2.6%
taiwan 2.3% 2.0% 0.006 0.005 -0.3% -0.1%
pakistan 0.4% 2.0% 0.012 0.036 1.5% 2.4%
australia 1.5% 1.9% 0.011 0.017 0.5% 0.6%
iran 0.8% 1.5% 0.008 0.025 0.7% 1.7%
singapore 1.7% 1.5% 0.006 0.001 -0.2% -0.5%
france 3.9% 1.4% 0.036 0.023 -2.5% -1.3%
spain 2.0% 1.1% 0.017 0.042 -0.9% 2.5%
canada 1.1% 1.0% 0.018 0.008 0.0% -0.9%
malaysia 0.3% 1.0% 0.010 0.015 0.7% 0.5%
egypt 0.4% 1.0% 0.011 0.033 0.6% 2.3%
bangladesh 0.1% 1.0% 0.000 0.001 0.9% 0.1%
iraq 0.1% 0.9% 0.001 0.004 0.9% 0.3%
algeria 0.3% 0.9% 0.010 0.001 0.6% -0.9%
russia 2.4% 0.8% 0.019 0.008 -1.6% -1.1%
vietnam 0.3% 0.8% 0.006 0.013 0.4% 0.7%
italy 3.2% 0.7% 0.028 0.014 -2.5% -1.4%
sweden 0.7% 0.7% 0.010 0.037 0.0% 2.7%
switzerland 1.4% 0.7% 0.009 0.007 -0.8% -0.3%
turkey 0.8% 0.6% 0.020 0.014 -0.2% -0.6%
netherlands 1.1% 0.6% 0.005 0.010 -0.5% 0.5%
belgium 1.0% 0.5% 0.013 0.006 -0.5% -0.7%
poland 0.7% 0.5% 0.007 0.013 -0.2% 0.6%
wales 0.3% 0.4% 0.005 0.001 0.1% -0.5%
brazil 0.6% 0.3% 0.016 0.002 -0.3% -1.4%
czech republic 0.3% 0.3% 0.004 0.016 -0.1% 1.2%
indonesia 0.1% 0.2% 0.000 0.000 0.1% 0.0%
oman 0.5% 0.2% 0.007 0.006 -0.3% -0.2%
u arab emirates 0.0% 0.2% 0.002 0.002 0.2% 0.0%
mexico 0.4% 0.2% 0.004 0.002 -0.2% -0.2%
scotland 0.4% 0.2% 0.006 0.003 -0.2% -0.2%
austria 0.6% 0.2% 0.005 0.005 -0.4% 0.0%
morocco 0.1% 0.2% 0.002 0.003 0.1% 0.2%
portugal 0.4% 0.2% 0.003 0.002 -0.2% -0.1%
denmark 0.4% 0.2% 0.003 0.008 -0.2% 0.6%
slovenia 0.1% 0.2% 0.000 0.024 0.1% 2.4%
palestine 0.0% 0.2% 0.000 0.000 0.2% 0.0%
israel 0.6% 0.2% 0.003 0.000 -0.5% -0.3%
thailand 0.2% 0.2% 0.001 0.001 0.0% 0.0%
south africa 0.1% 0.2% 0.011 0.001 0.0% -1.0%
finland 0.3% 0.1% 0.004 0.000 -0.2% -0.4%
tunisia 0.2% 0.1% 0.002 0.002 -0.1% 0.0%
ireland 0.5% 0.1% 0.002 0.002 -0.4% 0.0%
norway 0.1% 0.1% 0.001 0.000 0.0% -0.1%
nigeria 0.0% 0.1% 0.001 0.000 0.1% -0.1%
yemen 0.0% 0.1% 0.000 - 0.1%
romania 0.2% 0.1% 0.002 0.000 -0.1% -0.2%
uzbekistan 0.0% 0.1% 0.000 0.000 0.1% 0.0%
greece 0.3% 0.1% 0.008 0.001 -0.2% -0.8%
ukraine 0.4% 0.1% 0.004 0.004 -0.3% 0.0%
luxembourg 0.0% 0.1% 0.000 - 0.0%
belarus 0.1% 0.1% 0.002 0.000 -0.1% -0.2%
chile 0.1% 0.1% 0.002 0.001 0.0% -0.1%
peru 0.1% 0.1% 0.001 0.000 -0.1% 0.0%
lebanon 0.0% 0.0% 0.000 0.002 0.0% 0.2%
slovakia 0.0% 0.0% 0.001 0.000 0.0% -0.1%
new zealand 0.1% 0.0% 0.001 - -0.1%
nepal 0.0% 0.0% - - 0.0%
ethiopia 0.0% 0.0% 0.000 0.000 0.0% 0.0%
jordan 0.1% 0.0% 0.002 - 0.0%
azerbaijan 0.0% 0.0% 0.000 - 0.0%
north ireland 0.1% 0.0% 0.000 - 0.0%
colombia 0.1% 0.0% 0.001 - 0.0%
latvia 0.0% 0.0% 0.000 - 0.0%
qatar 0.0% 0.0% 0.002 - 0.0%
serbia 0.0% 0.0% 0.004 - 0.0%
bulgaria 0.0% 0.0% 0.004 - 0.0%
hungary 0.2% 0.0% 0.002 - -0.1%
kazakhstan 0.0% 0.0% 0.000 - 0.0%
estonia 0.0% 0.0% 0.000 - 0.0%
uruguay 0.0% 0.0% 0.000 - 0.0%
cyprus 0.0% 0.0% 0.001 - 0.0%
philippines 0.0% 0.0% 0.000 - 0.0%
bahrain 0.0% 0.0% 0.000 - 0.0%
croatia 0.0% 0.0% 0.000 - 0.0%
kuwait 0.0% 0.0% 0.000 - 0.0%
argentina 0.1% - 0.002 -
armenia 0.0% - 0.000 -
brunei 0.0% - 0.000 -
cameroon 0.0% - 0.000 -
costa rica 0.0% - - -
cote ivoire 0.0% - - -
cuba 0.0% - 0.000 -
ecuador 0.0% - 0.000 -
georgia 0.1% - 0.001 -
ghana 0.0% - 0.000 -
iceland 0.0% - 0.000 -
kenya 0.0% - 0.000 -
libya 0.0% - 0.000 -
lithuania 0.2% - 0.001 -
macedonia 0.0% - 0.000 -
moldova 0.1% - 0.001 -
north macedonia 0.0% - - -
senegal 0.0% - 0.000 -
sri lanka 0.0% - 0.000 -
tajikistan 0.0% - - -
tanzania 0.0% - - -
venezuela 0.0% - 0.001 -
zimbabwe 0.0% - - -

1

The characteristic of centrality makes it possible to determine how important a given node is, based on its position in the graph. We calculated two centrality metrics: 1) Degree centrality reflects how important a particular node is in terms of the number of its connections to other nodes in the network and, for a weighted graph, is calculated as follows:

cdi=jNωij

where i is the index of the node in question, wij is the weight of the edge (i, j), and N is the number of nodes in the graph.

2) Betweenness centrality. In much of the Network Science literature, the term “centrality” often refers to this specific measure. The formula for calculating betweenness centrality for node i is more complex:

cdi=2NN-1j,k,jkσjkijk,

where σjk is the number of shortest paths from node j to node k, and σ jk (i) is the number of those shortest paths that pass through node i. The summation is performed over all possible pairs of nodes (j, k). In other words, this measure shows how often node i serves as a “transit point” when moving from one node in the graph to any other. It is particularly useful for identifying bottlenecks in a network — nodes that lie on the edges or sets of edges connecting two clearly distinct clusters [https://habr.com/ru/articles/715386/].

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