Frontier Research Institute for Interdisciplinary Sciences
Tohoku University

A research team at Tohoku University has published a new study highlighting recent advances in multifunctional fiber technologies for neurochemical sensing and modulation in the brain. The study was led by Yuanyuan Guo, Associate Professor at the Frontier Research Institute for Interdisciplinary Sciences (FRIS) and the Graduate School of Biomedical Engineering at Tohoku University, who heads the Biofibertronics research group. The research was carried out in collaboration with a graduate researcher, Adrijana Savevska, from the University of Maribor. Adrijana Savevska joined the team through the Erasmus+ Programme traineeship and contributed to the review and analysis of emerging fiber-based electrochemical neural interfaces.   The article reviews recent progress in integrating electrochemical sensing and modulation with thermally drawn multimaterial fibers, flexible bioelectronic platforms that combine optical, electrical, and chemical functions in a single device. Such technologies hold promises for advancing neuroscience research and for future biomedical tools that can monitor biochemical signals in living tissues.   This work also demonstrates the important role of international student exchange in advancing interdisciplinary research. By hosting visiting students and young researchers, the Biofibertronics group at Tohoku University continues to foster global collaboration and train the next generation of scientists working at the intersection of materials science, bioelectronics, and neuroscience.   The work is published in Bioelectrochemistry on December 29, 2025, and was conducted through international collaboration and student exchange.   Figure：Conceptual illustration of thermally drawn multifunctional fibers integrated with electrochemical sensing for neurochemical monitoring and modulation   Publication Details: Title: Critical perspectives on thermally-drawn multimaterial and multifunctional fiber-based neural interface for neurochemical sensing and modulation Authors: Adrijana Savevska , Yuanyuan Guo Journal: Bioelectrochemistry DOI: 10.1016/j.bioelechem.2025.109208 URL: https://pubmed.ncbi.nlm.nih.gov/41576484/

We are pleased to announce that the International Symposium on Social Robots and Ethical Design (iSRED), chaired by Associate Professor Weng (Cross-Appointment, Kyushu University Institute for Advanced Study), is now accepting submissions.   Starting in 2024, the annual IAS-FRIS Symposium on Social Robots and Ethical Design, a collaboration between the Institute for Advanced Study, Kyushu University and the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, will be held with the participation of strategic partners such as the Research Center for Digital Humanities at National Taiwan University, the Centre for Law and Technology (LawTech) at the University of Hong Kong, and the Graduate School of Data Science at Seoul National University. We believe that this symposium should extend beyond its locations in Fukuoka and Sendai and focus on closer exchanges with other universities in East Asia. After careful consideration, we have decided to change the name of the conference to the International Symposium on Social Robots and Ethical Design (iSRED) and to change from an invitation-only conference to a CFP open call for papers conference.   Schedule Full Paper Submission: March 13 - July 31, 2026.  Workshop Proposal Submission: March 13 - July 31, 2026. Notification of Acceptance: August 31, 2026. Early Bird Registration: Starts August 31, 2026.   iSRED 2026 Symposium  Date: November 10–11, 2026 Location: Inamori Hall, Inamori Foundation Memorial Hall, Ito Campus, Kyushu University (hybrid event) Call for Paper The iSRED Annual Theme: Leveraging Design Thinking for the Implementation of Responsible Robotics Please visit the iSRED 2026 website for submission instructions. https://www.isred-ethical.design/   Details（PDF）  

Quantum computers work by applying quantum operations, such as quantum gates, to delicate quantum states. Ideally, quantum computers can solve complex equations at staggeringly fast speeds that vastly outpace regular computers. In real hardware, the operations of quantum computers often deviate from the ideal behavior because of device imperfections and unwanted noise from the environment. To build reliable quantum machines, researchers need a way to accurately determine what a quantum device is actually doing.   Quantum process tomography (QPT) is a standard method for this. However, traditional QPT becomes very costly as the system grows, because the number of required measurements and calculations increases rapidly with the number of qubits.   To address this challenge, a research team from Tohoku University, the Nara Institute of Science and Technology (NAIST), and the University of Information Technology (Vietnam National University, Ho Chi Minh City) has introduced a new framework called compilation-based quantum process tomography (CQPT).    The central idea of CQPT is simple. The method starts with a known input quantum state, applies a trainable process following the unknown process, and then works backwards to evaluate how well the final output returns to the original input. The “return-to-input” model is optimized to reconstruct the underlying quantum processes that make up the steps in-between the input and output. Importantly, the framework is designed so that optimization can conveniently be performed using only a single measurement outcome per input state.    The researchers developed two complementary versions of the CQPT: one based on Kraus operators, and one based on the Choi matrix. Together, these two approaches allow CQPT to handle a wide range of quantum operations and noisy processes relevant to modern quantum devices.   Figure 1: Overview of compilation-based quantum process tomography (CQPT). The left panel shows the main idea: an unknown quantum process transforms an input state into an output state, and CQPT uses a trainable “compiler” to learn the process by forcing the final state to return to the original input. The right panels illustrate two implementations of CQPT: a Kraus-based approach for unitary or near-unitary processes, and a Choi-based approach for general noisy processes. ©Le Bin Ho et al.   “Efficient and scalable methods for characterizing quantum processes are important for the future of quantum computing and quantum sensing,” Dr. Le Bin Ho said. “We need such methods to check whether quantum gates and circuits work correctly, identify hardware errors, calibrate devices, and support quantum error correction.”    Dr. Le believes that CQPT could become a practical alternative to standard quantum process tomography, especially for larger quantum systems where full tomography is no longer realistic due to high costs.    The current study demonstrates that CQPT is feasible through sound theoretical analysis and numerical simulations. The framework offers a promising way to make quantum tomography more efficient. Next steps will involve tackling the challenge of implementing it in real experiments. The researchers plan to focus on developing hardware-ready versions of the method and improving its robustness. Publication Details: Title: Advancing Quantum Process Tomography through Quantum Compilation Authors: Huynh Le Dan Linh, Vu Tuan Hai, Le Bin Ho Journal: Advanced Quantum Technologies DOI: 10.1002/qute.202500494   Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/whats_going_on_inside_quantum_computers_process_tomography.html

Prof. Hideaki Fujiwara (Specially Appointed Associate Professor) at the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, has published a paper presenting research findings that quantitatively analyze the scholarly impact of research articles published in major astronomy and astrophysics journals between 1996 and 2024, based on bibliographic database information.   In this study, annual trends in key metrics such as the number of publications and citations were analyzed using data obtained from the bibliographic databases Scopus/SciVal. The results show that, on average, citations to astronomy and astrophysics papers increase approximately 2-4 years after publication and then continue for about 10 years, suggesting a characteristic timescale of knowledge use in the field.   Scholarly impact is sometimes assessed using citation-based metrics. However, this study suggests that evaluating impact solely on the basis of short-term citation counts has limitations and requires careful interpretation.   This research was published in the academic journal Publications of the Astronomical Society of Japan on January 28, 2026. Publication Details: Title: Bibliometric benchmarking across astronomy journals: Knowledge–use cycle and PASJ in the global landscape Author: Hideaki Fujiwara Journal: Publications of the Astronomical Society of Japan DOI: 10.1093/pasj/psaf149  URL: https://academic.oup.com/pasj/advance-article/doi/10.1093/pasj/psaf149/8442979  

Tetrodotoxin (TTX) is one of the most famous natural toxins as a pufferfish toxin. This toxin is a potent and highly selective blocker of voltage-gated sodium channels. In addition to pufferfish and other diverse marine organisms, TTX is also found in terrestrial amphibians such as newts. Owing to its unique structure, its strong pharmacological activity that can cause fatal food poisoning, and its broad distribution across taxonomically diverse organisms, TTX has been studied in multiple disciplines, including organic chemistry, biology, food safety science, chemical ecology, and neuroscience. Nevertheless, its origin and biosynthetic pathway have remained unresolved. In this study, Associate Professor Yuta Kudo of the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, led an international collaborative project with Shugo Horie (undergraduate student) and Professor Mari Yotsu-Yamashita of the Graduate School of Agricultural Science, Tohoku University, and Associate Professor Charles Hanifin of Utah State University. Kudo and co-workers discovered five new tetrodotoxin analogues from toxic newts and elucidated their chemical structures. By identifying these analogues that differ in oxidation state and stereochemical configuration, Kudo and co-workers were able to propose a biosynthetic pathway for terrestrial tetrodotoxin. Furthermore, the inhibitory activities of these newly identified analogues against voltage-gated sodium channels were evaluated, providing new insights into their structure–activity relationships. The findings have been published online on February 4, 2026, in the Journal of Natural Products, a peer-reviewed journal of the American Chemical Society (ACS). The article is available as open access through Tohoku University’s APC support program.     Publication Details: Title: Identification of Deoxy- and epi-Tetrodotoxin Analogues from the Newt Cynops ensicauda popei Suggests Stepwise Oxidation in Terrestrial Tetrodotoxin Biosynthesis  Authors: Shugo Horie, Charles T. Hanifin, Yuko Cho, Keiichi Konoki, Mari Yotsu-Yamashita, and Yuta Kudo* (*corresponding author) Journal: Journal of Natural Products DOI: 10.1021/acs.jnatprod.5c01546 URL: https://doi.org/10.1021/acs.jnatprod.5c01546     Figure: Identification of novel tetrodotoxin analogues (2-6) enabled the proposal of a late-stage biosynthetic pathway  

Developing new materials can involve a dizzying amount of trial and error for different configurations and elements. It is no wonder that artificial intelligence (AI) has seen a surge of popularity in energy materials research for its potential to streamline this time-consuming process. However, fully autonomous workflows that connect high-precision experimental knowledge to the discovery of credible new energy-related materials remain at an early stage.   A team of researchers at the WPI-Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, created the Descriptive Interpretation of Visual Expression (DIVE) multi-agent workflow to streamline the material researching process. The system extracts information from images in a database of over 30,000 entries from >4,000 scientific publications to propose new materials within minutes.   The findings were published in Chemical Science on February 3, 2026. Profs. Linda Zhang and Yusuke Hashimoto of the Frontier Research Institute for Interdisciplinary Sciences (FRIS) join the research team.    Figure 1: Comparison between DIVE's multi-agent workflow and conventional methods, and the distribution of collected publications in the hydrogen storage materials database. ©Hao Li et al. DIVE systematically organizes the information it pulls from existing literature regarding solid-state hydrogen storage materials. Its accuracy and coverage of data extraction was 10-15% better than commercial models, and over 30% better compared to open-source models. DIVE is easy to use, as input resembles a regular conversation. Simply provide DIVE with what criteria you are looking for, and it will draw from its database to propose suitable materials. It also demonstrates the ability to propose entirely novel materials that haven't been reported in the literature before.   "DIVE can convert literature-embedded scientific knowledge into actionable innovation, offering a scalable pathway for accelerated discovery across chemistry and materials science," says Distinguished Professor Hao Li (WPI-AIMR).   This research is significant because it builds a reliable, end-to-end pipeline that converts key experimental results otherwise hidden in paper figures into high-quality, machine-readable data, enabling faster and more accurate scientific synthesis and discovery. It reports clear performance gains over common extraction approaches and produces a large, curated hydrogen-storage database (DigHyd) built from thousands of papers, which can be directly queried and used to guide new material design. The Digital Hydrogen Platform (DigHyd: www.dighyd.org) is the first digital platform for hydrogen storage materials design, and also the largest experimental and computational solid-state hydrogen storage database reported to date.   "The reason we want to know so much about hydrogen storage materials is because they are a key bottleneck for making hydrogen-based clean energy practical, safer, and more affordable," explains Li. "Our proposed workflow with DIVE has the potential of accelerating evidence-based discovery, which means shorter turnaround times from when research is published to when it actually gets implemented in real-world technologies that help the environment." Figure 2: New materials design workflow powered by the AI agent platform 'DigHyd.' ©Hao Li et al. Publication Details: Title: "DIVE" into Hydrogen Storage Materials Discovery with AI Agents Authors: Di Zhang, Xue Jia, Hung Ba Tran, Seong Hoon Jang, Linda Zhang, Ryuhei Sato, Yusuke Hashimoto, Toyoto Sato, Kiyoe Konno, Shin-ichi Orimo, Hao Li Journal: Chemical Science DOI: 10.1039/d5sc09921h Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/dive_into_hydrogen_storage_materials_discovery_with_ai_agents.html WPI-Advanced Institute for Materials Research (WPI-AIMR) https://www.wpi-aimr.tohoku.ac.jp/en/achievements/press/2026/20260204_002126.html Institute of Fluid Science https://www.ifs.tohoku.ac.jp/eng/news/2205/  

An international research team has discovered a supermassive black hole growing rapidly while radiating bright X-rays and radio waves. This combination of features contradicts the current models of black hole growth, requiring astronomers to look for a new explanation.   Supermassive black holes, millions to billions of times the mass of the Sun, sit in the centers of most galaxies. They grow by pulling in surrounding gas. As gas spirals inward, it can power a compact region of hot plasma known as a corona which emits X-rays. Some supermassive black holes also form a jet of outflowing material that emits strongly at radio wavelengths.   But if gas falls towards a supermassive black hole too quickly, radiation from the gas starts to push back on the material flowing behind it, causing the flow to slow down. This sets a self-regulating “Eddington Limit,” a speed limit on how fast gas can flow in. Like most speed limits, the Eddington Limit is broken sometimes, enabling rapid mass build-up over short cosmic timescales.     Figure: Artist’s impression of a supermassive black hole system. Infalling gas forms a bright corona near the black hole. In some systems, a jet is launched. (Credit: NASA/JPL-Caltech)   To test whether such extreme growth occurs in the early Universe, a team led by scientists at Waseda University and Tohoku University, including Prof. Kohei Ichikawa of FRIS, used the Subaru Telescope to measure the motion of gas around a supermassive black hole that existed when the Universe was less than 1.5 billion years old and found that it is accreting gas at 13 times the Eddington Limit. More surprisingly, the object also emits bright X-rays and radio waves. In the current models, super-Eddington accretion should change the gas flow and suppress X-ray and radio wave production. This unexpected combination hints at physical mechanisms not yet fully captured by current models of extreme accretion.   The team thinks the object is in a short-lived transitional stage. A sudden burst of inflowing gas may have pushed the system into a super-Eddington state, while a bright X-ray corona and a strong radio-wave emitting jet remained simultaneously energized for a limited time before the system settles toward a more typical regime.   This discovery offers a rare glimpse of time-variable black hole growth in the early Universe—an important step toward understanding the rapid growth of massive black holes. Publication Details: Title:Discovery of an X-ray Luminous Radio-Loud Quasar at z = 3.4: A Possible Transitional Super-Eddington Phase Authors: Sakiko Obuchi et al. Journal: The Astrophysical Journal DOI: 10.3847/1538-4357/ae1d6d URL: https://doi.org/10.3847/1538-4357/ae1d6d Press Release: National Astronomical Observatory of Japan https://www.nao.ac.jp/en/news/science/2026/20260122-subaru.html

Prof. Yueh-Hsuan Weng (associate Professor )at the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University (Cross-appointed with the Inamori Frontier Program, Institute for Advanced Study, Kyushu University) has published a co-authored book titled 'Generative AI, Contracts, Law and Design', in which he was in charge of the chapter titled 'Proactive Privacy Communication Design for Emotional Robots'.   This book explores how generative AI and design are reshaping the law, legal communication, and contracting—moving beyond automation toward collaboration and meaningful outcomes. Combining theory and practice, it addresses challenges such as privacy, communication, financial well-being, responsible AI use, and the language of contracts. This edited book breaks new ground in exploring how generative AI and design are acting as catalysts for change in law, legal communication, and contracting. Together, they are transforming the way we think and act—moving beyond automation toward collaboration, actionability, and achieving goals. Bringing together theoretical insights and practical experiments, the book features contributions from scholars and practitioners working at the intersection of law, business, technology, and design.    Publisher: Springer Singapore Book Name: Springer PLBI Series: Generative AI, Contracts, Law and Design Date Published: November 2025 Format: Hardback ISBN： 978-981-95-2057-2  https://link.springer.com/chapter/10.1007/978-981-95-2058-9_7  

The pH, or the acidity or alkalinity of an environment, has long been known to affect how efficiently catalysts drive key electrochemical reactions. Yet despite decades of research, the atomic-scale mechanisms behind these pH effects have eluded scientists.   A new study sheds light on this mystery by decoding how electric fields, surface properties, and charge dynamics intertwine to govern catalytic performance. The findings mark a significant step toward rationally designing catalysts that perform efficiently in a range of environments, paving the way for next-generation clean energy technologies.   Details were published in the Journal of Materials Chemistry A on 26 September 2025.   Traditional models have explained pH-dependent activity mainly through the computational hydrogen electrode (CHE) model and the Nernst equation. These frameworks linked shifts in activity to changes in potential and proton concentration. However, the new research shows that the reality is far more complex, involving a web of interfacial electric fields and molecular interactions that standard models cannot fully capture.   Recent advances in both experimental and computational methods have revealed that properties such as dipole moments, polarizability, and the potential of zero charge (PZC) play a critical role. These factors determine how molecules and ions interact with catalyst surfaces, directly influencing reaction rates and selectivity.   By bringing together insights from electrochemistry, physics, and computational modeling, the research highlights how these interfacial effects manifest across a wide array of reactions, including hydrogen evolution (HER), oxygen reduction (ORR), carbon dioxide reduction (CO₂RR), and nitrate reduction (NO₃RR). These are among the most important reactions for renewable energy conversion, fuel generation, and environmental remediation.   Schematic illustrations of: (a) the methods dealing with pH for the classic CHE model and the electric field (EF) pH-dependent model; (b) surface coverage on Pt (111) revealed by the electric field model: HO* dominates under alkaline conditions, while H* prevails under acidic conditions; (c) simplified pH-dependent activity volcano. ©Hao Li et al.   "Our work shows that pH effects are not just surface-level phenomena; they are governed by the electric field environment at the interface," said Hao Li, a professor from Tohoku University's Advanced Institute for Materials Research (WPI-AIMR) who led the study. "By understanding and modeling these fields, we can predict how catalysts behave under different pH conditions and ultimately design materials that are more efficient and sustainable."   The study also introduces advanced theoretical frameworks that go beyond traditional thermodynamic descriptions. Notably, the reversible hydrogen electrode (RHE)-referenced Pourbaix diagram and the pH-dependent microkinetic volcano model provide a more accurate depiction of catalytic activity and stability across varying electrochemical conditions.   (a-c) Electric field effects on the adsorption free energies of ORR adsorbates. Determination of the PZCs in M-N-C catalysts using an explicit solvation model: (d) illustration of the PZC calculation workflow; (e) the work function (WF) of materials in ion-free water is utilized to calculate PZC; (f) PZCs of the two typical M-N-C configurations: M-pyrrole-N4 and M-pyridine-N4. (g) Calculated 1D surface Pourbaix diagram and (h) pH- and RHE-dependent 2D surface Pourbaix diagrams. ©Hao Li et al.   These new models offer scientists a powerful toolkit for predicting and optimizing catalyst behavior at the atomic scale. By integrating experimental data with computational simulations, researchers are now able to map how subtle changes in pH shift reaction pathways and determine overall efficiency. Looking ahead, the research team plans to combine molecular dynamics with machine learning potentials to simulate reaction conditions in real time. This approach could unlock even deeper insights into how catalysts evolve during operation, further accelerating the design of high-performance materials for a sustainable energy future.   (a) Scaling relations of the charge extrapolated Volmer, Heyrovsky, and Tafel transition state energies vs. H* binding energy. (b) Plot shows the adsorption energy of the intermediate HOO* plotted against the adsorption energy of the intermediate HO*. The scaling line (black line) has the equation ΔEOOH = ΔEOH + 3.2 eV. (c) EHO* vs. EO* scaling relations of M-N-C catalysts, metal, and metal oxides. (d) pH-dependent ORR volcanoes of M-N-C catalysts (left) and metal catalysts (right). (e) pH-dependent CO2RR volcanos on Sn-N-C catalysts (left) and polyatomic Sn catalysts (right). (f) 2D HER volcano considering RHE-scale surface Pourbaix (the orange triangles represent HER activity poisoned by HO*). (g) pH-dependent NO3RR volcano on pyrrolic M-N-C SACs (left) and pyridinic M-N-C SACs (right). ©Hao Li et al.   Prof. Linda Zhang from FRIS joined the research team. Publication Details: Title: Decoding pH-Dependent Electrocatalysis through Electric Field Models and Microkinetic Volcanoes  Authors: Songbo Ye, Yuhang Wang, Heng Liu, Di Zhang, Xue Jia, Linda Zhang, Yizhou Zhang, Akichika Kumatani, Hitoshi Shiku, and Hao Li Journal: Journal of Materials Chemistry A DOI: 10.1039/D5TA06105A  

From November 5-7, 2025, the Symposium on Social Robots and Ethical Design, jointly organized by the Institute for Advanced Study (IAS) at Kyushu University and FRIS at Tohoku University, convened as a hybrid event in Aobayama Campus. Under the banner “Toward Design-centered Governance for Social Robots”, the symposium addressed the regulatory, ethical, design and governance challenges posed by increasingly capable AI-enabled social robots.  The symposium brought together researchers from engineering, design, ethics, law, and social sciences to provide examination on the challenges and opportunities posed by social robots. The thematic sessions covered four interconnected areas, underscoring the symposium’s central commitment to viewing social robots as socio-technical systems whose development must be informed by integrated insights from technology, behavior, and normative frameworks. In the domain of robotics design and deployment, researchers presented studies on how robots can be incorporated into real living environments. Presentations from Tohoku University demonstrated the use of living-lab and experimental settings to evaluate how individuals interact with assistive robots in everyday situations. Contributions from National Taiwan University highlighted soft robotics and adaptive locomotion mechanisms that enable robots to navigate complex human environments more effectively. Additional work explored how visual complexity and familiarity influence user comfort and attentiveness when engaging robots. Other speakers analyzed how both the physical and psychological dimensions of human–robot interaction (HRI)can be shaped through careful design choices that promote a sense of safety, empathy, and trust. The second thematic focus on HRI offered behavioral and cognitive perspectives. Scholars examined how emotional responses such as acceptance, rejection, or perceived social friction emerge in interactions with social robots. Research using game-based simulations demonstrated how robots can affect participants’ moral reasoning processes. Another presenter introduced findings about the social acceptance of anthropomorphism in dog robots. The symposium further highlighted how cultural narratives found in science fiction and digital games can illuminate public expectations, anxieties, and imaginaries surrounding future robot governance. Presentations within the policy and governance theme addressed broader societal and regulatory implications. Speakers discussed the growing role of robots in ageing societies and the need for human-centered approaches to care technologies that recognize emotional and moral dimensions of vulnerability. The presenters emphasized that recognizing overlooked needs is important. Others analyzed how systematic reviews and stakeholder consultations contribute to more inclusive robot governance frameworks. The longstanding issue of “responsibility gaps” was also examined.  The final set of presentations turned toward ethical design and governance, emphasizing the significance of non-binding ethics standards as complementary tools to formal legal regulation. Experts analyzed how socio-technical standards developed within the IEEE framework are being adopted globally, noting their increasing influence on engineering practice. Cross-cultural studies from Japan and Norway provided comparative insights into consent, privacy, and social acceptance of robots. Researchers argued for the integration of both philosophical reflection and empirical data in the development of robot ethics methodologies.  Taken together, these contributions demonstrated the inherently multidisciplinary nature of responsible robotics. The symposium underscored that engineering innovation alone cannot address the complexities of deploying social robots into public and private spaces. Instead, effective governance requires design-centred approaches that incorporate behavioural insights, ethical standards, and legal considerations from the outset. The discussions also reflected a broader shift in robotics research: from industrial automation toward socially embedded systems in homes, care settings, and everyday public environments. This shift signals that future progress in robotics must be aligned with societal needs and normative expectations. Through its diverse range of perspectives, the symposium offered a valuable foundation for continued research, collaboration, and the development of robust governance frameworks for social robots.