Frontier Research Institute for Interdisciplinary Sciences
Tohoku University

To successfully meet the United Nations' Sustainable Development Goals (SDGs), we need significant breakthroughs in clean and efficient energy technologies. Central to this effort is the development of next-generation energy storage systems that can contribute towards our global goal of carbon neutrality. Among many possible candidates, high-energy-density batteries have drawn particular attention, as they are expected to power future electric vehicles, grid-scale renewable energy storage, and other sustainable applications.   Lithium-oxygen (Li-O2) batteries stand out due to their exceptionally high theoretical energy density, which far exceeds that of conventional lithium-ion batteries. Despite this potential, their practical application has been limited by poor cycle life and rapid degradation. Understanding the root causes of this instability is a critical step toward realizing a sustainable and innovative energy future.   In a recent study, a Tohoku University research team led by Dr. Wei Yu (FRIS) Professor Hirotomo Nishihara (AIMR/IMRAM), and first author Zhaohan Shen (JSPS Fellow (DC1)) - with researchers from Gunma University, Kyushu Synchrotron Light Research Center, Manchester Metropolitan University (UK), and the University of Cambridge (UK) - addressed this long-standing challenge by synthesizing a high-purity (> 99%) 13C-labeled graphene mesosponge (13C-GMS).   "Graphene mesosponge is a hollow-structured material with sponge-like properties, such as high flexibility," explains Nishihara, "It has a unique structure that makes it useful for many different applications. In this case, we customized it to learn more about why batteries fail,"   This novel material, with high surface area and few edge sites, serves as a stable scaffold for loading polymorphic ruthenium (Ru) catalysts. By integrating quantitative characterization techniques and theoretical simulations, the team was able to clearly distinguish whether battery failure originates from carbon cathode degradation or electrolyte decomposition.   Synthesis process of GMS and 13C-GMS. ©Zhaohan Shen et al.   The results show that while reducing charge potential helps to suppress carbon cathode degradation, different Ru crystal phases induce varying degrees of electrolyte decomposition.   "Our findings allow us to point out the 'weakest link' in batteries - either the cathode or the electrolyte - which lets us know exactly what we need to improve to make Li-O2 batteries a more practical option," explains Yu.   Schematic illustration of the critical impact of Ru catalysts in Li-O2 batteries. ©Zhaohan Shen et al.   This breakthrough not only resolves a key controversy regarding the role of solid-state catalysts in Li-O2 batteries but also contributes to the global pursuit of sustainable energy storage solutions. By revealing the hidden mechanisms behind battery failure, the research provides new design principles for next-generation batteries that can support SDGs and accelerate innovation in clean energy systems.   The findings were published in Applied Catalysis B: Environment and Energy on September 29, 2025.     Publication Details: Title: High-Purity 13C-labeled Mesoporous Carbon Electrodes Decouple Degradation Pathways in Li-O2 Batteries with Polymorphic Ru Catalysts Authors: Zhaohan Shen, Wei Yu, Alex Aziz, Takeharu Yoshii, Yoshikiyo Hatakeyama, Eiichi Kobayashi, Thomas Kress, Xinyu Liu, Alexander C. Forse, Hirotomo Nishihara Journal: Applied Catalysis B: Environment and Energy DOI: 10.1016/j.apcatb.2025.126030   Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/unmasking_the_culprits_of_battery_failure_with_a_graphene_mesosponge.html

Detecting dark matter - the mysterious substance that holds galaxies together - is one of the greatest unsolved problems in physics. Although it cannot be seen or touched directly, scientists believe dark matter leaves weak signals that could be captured by highly sensitive quantum devices.   In a new study, researchers at Tohoku University propose a way to boost the sensitivity of quantum sensors by connecting them in carefully designed network structures. These quantum sensors use the rules of quantum physics to detect extremely small signals, making them far more sensitive than ordinary sensors. Using these, accurately detecting the faint clues left behind from dark matter could finally become possible.   The study focuses on superconducting qubits, which are tiny electric circuits cooled to very low temperatures. These qubits are normally used as building blocks of quantum computers, but here they act as powerful quantum sensors. Just as a team working together can achieve more than a single person, linking many of these superconducting qubits in an optimized network allows them to detect weak dark matter signals much more effectively than any single sensor could on its own.   (Top left) Composition of the universe, showing that dark matter accounts for about 27%. (Top right) Proposed quantum sensor network, where superconducting qubits are connected in different graph structures. (Bottom) Estimation results demonstrating agreement with the true value, along with a comparison against quantum bounds. ©Tohoku University   The team tested different network patterns, such as ring, line, star, and fully connected graphs, using systems of four and nine qubits. They then applied variational quantum metrology (a method similar to training a machine-learning model) to optimize how the quantum states were prepared and measured. To refine the results, Bayesian estimation was used to filter out noise, much like sharpening a blurry image.   The findings were striking: optimized networks consistently outperformed traditional methods, even when realistic noise was introduced. This shows the approach can work on today's quantum devices.   "Our goal was to figure out how to organize and fine-tune quantum sensors so they can detect dark matter more reliably," said Dr. Le Bin Ho, lead author of the study. "The network structure plays a key role in enhancing sensitivity, and we've shown it can be done using relatively simple circuits."   Beyond dark matter, these quantum sensor networks could advance technologies such as quantum radar, gravitational wave detection, and ultra-precise timekeeping. Furthermore, they may one day improve GPS accuracy, enhance brain imaging with MRI, or help detect hidden underground structures.   "This research shows that carefully designed quantum networks can push the boundaries of what is possible in precision measurement," Dr. Ho added. "It opens the door to using quantum sensors not just in laboratories, but in real-world tools that require extreme sensitivity."   Looking ahead, the team plans to extend this approach to larger networks and explore ways to make the sensors more resistant to noise.   The findings were published in Physical Review D on October 1, 2025.   Publication Details: Title: Optimized quantum sensor networks for ultralight dark matter detection Authors: Adriel I. Santoso, Le Bin Ho Journal: Physical Review D DOI: https://doi.org/10.1103/rv43-54zq   Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/quantum_networks_bring_new_precision_to_dark_matter_searches.html  

Hybrid Event   The symposium aims to discuss the use of AI ethics standardization in the governance of social robots, specifically examining the challenges to regulating AI-enabled technologies due to an inability to keep up with the rapid legislative process. Incidentally, in addition to examining the regulation of social robots, we also explore regulatory frameworks that rely on non-binding, flexible AI ethics standards to ensure stakeholders can manage the risks of ethical, legal, and societal impacts (ELSI) from the perspective of ethical design. Registration https://x.gd/wC4m5 Deadline 2025/11/03   Date 2025/11/05-2025/11/07 Time 09:30a.m. /05:00p.m.   Venue Seminar Room, FRIS, Tohoku University     Website: https://2025.roboethics.design// LinkedIn: https://www.linkedin.com/events/ias-frissymposiumonsocialrobots7379026824103649280/   Contact WENG Yueh Hsuan 　 @

Prof. Hideaki Fujiwara (Specially Appointed Associate Professor) at the Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, has published a study analyzing the scholarly impact of research papers based on early observations with the Subaru Telescope. The Subaru Telescope is an 8.2-meter optical-infrared telescope atop Maunakea, Hawaii, and operated by the National Astronomical Observatory of Japan as one of the country’s leading astronomical research facilities.   This study evaluated astronomy papers published between 1996 and 2007 using bibliometric methods based on citation indicators. The analysis revealed that, although Subaru-based papers accounted for less than 10% of Japan’s total astronomy output, they achieved notably high citation performance, far exceeding the world average. The results highlight the scientific value of the Subaru Telescope and demonstrate the academic return of Japan’s large-scale research facilities in quantitative terms.   This research was published in the academic journal Publications of the Astronomical Society of Japan on September 17, 2025. Publication Details: Title: A bibliometric analysis of the scholarly impact of early Subaru Telescope-based publications Author: Hideaki Fujiwara Journal: Publications of the Astronomical Society of Japan DOI: 10.1093/pasj/psaf100 URL: https://academic.oup.com/pasj/advance-article/doi/10.1093/pasj/psaf100/8256513  

Advances in spintronics have led to the practical use of magnetoresistive random-access memory (MRAM), a non-volatile memory technology that supports energy-efficient semiconductor integrated circuits. Recently, antiferromagnets−magnetic materials with no net magnetization−have attracted growing attention as promising complements to conventional ferromagnets. While their properties have been extensively studied, clear demonstrations of their technological advantages have remained elusive.   Now, researchers from Tohoku University, the National Institute for Materials Science (NIMS), and the Japan Atomic Energy Agency (JAEA) have provided the first compelling evidence of the unique benefits of antiferromagnets. Their study shows that antiferromagnets enable high-speed, high-efficiency memory operations in the gigahertz range, outperforming their ferromagnetic counterparts. The findings were published in the journal Science on August 21, 2025.   (a) Schematic illustration of memory device consisting of chiral antiferromagnet Mn3Sn / nonmagnetic metal heterostructure (b) A scanning electron microscope image of the fabricated device with Mn3Sn nanodot and nonmagnetic metal channel. ©Yutaro Takeuchi et al.   The team used the chiral antiferromagnet Mn₃Sn, whose spins form a non-collinear arrangement, as the medium for writing digital information. They fabricated a nanoscale Mn₃Sn dot device and successfully induced coherent rotation of its antiferromagnetic texture using electric currents. This enabled fast, high-fidelity control of spin ordering.   The system achieved efficient switching with 0.1-nanosecond current pulses--faster than any ferromagnetic device--while requiring no external magnetic field. Remarkably, the device demonstrated 1,000 error-free switching cycles, a level of reliability not possible in ferromagnets.   "Achieving 1,000 switchings out of 1,000 trials with a 0.1-nanosecond current pulse at zero magnetic field has been unreachable for ferromagnets--but turns out not to be the case for antiferromagnets," said Yutaro Takeuchi, the paper's lead author.   (a) Switching probability versus current density and pulse width. (b) Illustration of switching (switching-back) dynamics through coherent spin rotation of chiral antiferromagnet (c) Demonstration of the 1,000/1,000 switching. (d) Pulse width dependence of normalized switching current in chiral antiferromagnet, conventional ferromagnets and ferrimagnets. ©Yutaro Takeuchi et al.   "This antiferromagnetic advantage stems from a qualitative difference in their switching dynamics," explained Yuta Yamane, who led the theoretical modeling. "In conventional ferromagnets, magnetization undergoes three-dimensional precessional motion. In contrast, antiferromagnetic switching is completed through two-dimensional rotation of the chiral spin structure with an effective inertial mass--a key factor not seen in ferromagnets."   Shunsuke Fukami, the project supervisor, emphasized the breakthrough: "Researchers had shown in recent years that antiferromagnets can do what ferromagnets can do. Our work, for the first time, shows that antiferromagnets can do what ferromagnets cannot do."   These results mark a significant step toward next-generation semiconductor device technology powered by antiferromagnets. By unlocking ultrafast and energy-efficient switching without external fields, the research opens up new pathways for spintronics-based memory and logic devices, advancing the pursuit of high-performance, low-power electronics.   Publication Details: Title: Electrical coherent driving of chiral antiferromagnet Authors: Yutaro Takeuchi, Yuma Sato, Yuta Yamane, Ju-Young Yoon, Yukinori Kanno, Tomohiro Uchimura, K. Vihanga De Zoysa, Jiahao Han, Shun Kanai, Jun'ichi Ieda, Hideo Ohno, and Shunsuke Fukami Journal: Science DOI: 10.1126/science.ado1611   Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/antiferromagnets_outperform_ferromagnets_in_ultrafast_energyefficient_memory_operations.html  

Selecting the right material from countless possibilities remains a central hurdle in materials discovery. Theory-driven predictions and experiment‐based validations help us make informed selections, but their progress has long proceeded on separate tracks. A team of researchers at Tohoku University has now bridged this gap by constructing an AI‑built materials map that unifies literature‑derived experimental data with representative first‑principles computational data. This map could be a tool that leads researchers to the right material for a given situation - without wasting time getting lost along the way.   Data‑analysis workflow. Experimental and computational datasets are unified; crystal‑structure graphs, deep learning, and dimensionality reduction yield the materials map. ©Hashimoto et al. This "materials map" is a big graph with an axis for thermoelectric performance (zT) and structural similarity, with each datapoint representing a material. On this map, structurally analogous (i.e. similar) materials appear in close proximity. Because such materials are typically synthesized and evaluated using similar methods and devices, the map enables experimentalists to rapidly identify analogs of unknown high‑performance materials and to repurpose existing synthesis protocols as next steps, thereby reducing trial‑and‑error.   Led by Specially Appointed Associate Professor Yusuke Hashimoto and Professor Takaaki Tomai (FRIS) in collaboration with Assistant Professor Xue Jia and Professor Hao Li (WPI‑AIMR), the research study aimed to combine computational predictions with experiment-based data to provide the most accurate picture. The approach builds on a previously assembled integrated dataset that combines StarryData2 literature data with computed entries from the Materials Project. They used this information to train MatDeepLearn (MDL) combined with a message passing neural network (MPNN) on predictors of thermoelectric properties.   "By providing an intuitive, bird's‑eye view over many candidates, the map helps researchers to select promising targets at a glance, therefore it is expected to substantially shorten development timelines for new functional materials," remarks Hashimoto.   Developed materials map (left) and zoomed‑in view (right) showing thermoelectric performance (zT) together with structural similarity for efficient exploration. ©Hashimoto et al. Looking ahead, the team plans to extend this framework beyond thermoelectric to include magnetic and topological materials. They also plan to incorporate additional descriptors (e.g., magnetic, chemical, and topological features) toward a comprehensive, AI‑assisted materials‑design support platform.   This "materials map" allows researchers to easily spot look‑alike, potentially high‑performing materials. This can accelerate innovation, reduce development costs, and speed up the real‑world deployment of energy‑related technologies such as thermoelectric waste‑heat recovery that turns excess byproduct heat into usable energy.   The findings were published online in APL Machine Learning on July 28, 2025. Publication Details: Title: A materials map integrating experimental and computational data via graph-based machine learning for enhanced materials discovery Authors: Y. Hashimoto, X. Jia, H. Li, T. Tomai Journal: APL Machine Learning DOI: 10.1063/5.0274812   Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/ai_powered_materials_map_speeds_up_materials_discovery.html Advanced Institute for Materials Research (AIMR), Tohoku University https://www.wpi-aimr.tohoku.ac.jp/en/achievements/press/2025/20250731_002017.html  

A research team led by Linda Zhang at Tohoku University has developed a novel metal-organic framework (MOF) that enables record-breaking separation of hydrogen isotopes, achieving a D2/H2 selectivity of 32.5 at 60 K.    The findings, published in Nature Communications on July 1, 2025, represent a major advance in the quest for energy-efficient deuterium production. Figure: Illustration of isotope-selective adsorption in the MOF [Mn(ta)2]. Hydrogen (blue) and deuterium (red) molecules interact differently with the two distinct adsorption sites, inducing structural expansion that drives the separation process. (Credit: Linda Zhang) Deuterium, a stable isotope of hydrogen, is indispensable for a wide range of technologies, including nuclear fusion reactors, semiconductor processing, optical fibers, and deuterium-labeled pharmaceuticals. However, its chemical similarity to ordinary hydrogen makes isotopic separation extremely challenging. Traditional methods such as cryogenic distillation operate at -250°C and consume large amounts of energy, making them environmentally and economically costly.   The reported MOF, based on a triazolate ligand and manganese ions, demonstrates exceptional selectivity by leveraging isotopologue-specific structural dynamics. In this novel mechanism, the framework responds differently depending on whether it hosts hydrogen or deuterium. When exposed to a gas mixture containing less than 5% deuterium (natural abundance), the material successfully concentrated it to 75% in a single separation cycle, proving its practical potential.   Neutron powder diffraction experiments conducted at the Australian Nuclear Science and Technology Organisation (ANSTO) and Oak Ridge National Laboratory (ORNL) revealed the material’s two distinct adsorption sites: site 1: small pockets surrounded by triazole ligands, and site 2: larger framework channels. At low temperatures, hydrogen fills one site first before migrating to the second, while deuterium simultaneously occupies both. This unexpected behavior arises from differences in how each isotope interacts with the lattice, inducing subtle but measurable framework expansion. “This work shows how fine-tuned host–guest dynamics at the atomic level can be exploited for real-world applications,” said senior author Michael Hirscher of the Max Planck Institute (also affiliated with WPI-AIMR, Tohoku University). “It offers a pathway toward practical isotope separation systems that are both scalable and energy-efficient.”   “Our study demonstrates that even small differences between isotopes can be amplified through responsive material behavior,” added Zhang, who was also lead author of the paper. “This provides a new strategy for isotope separation using materials-based approaches rather than relying solely on large-scale physical processes.”    Beyond its performance, the MOF stands out for its practical viability. It is constructed from commercially available ligands and built upon a modular framework type, which can be readily adapted to different metals. These characteristics, combined with its exceptional selectivity, suggest strong potential for future scaling and industrial integration.   This project was the result of a close international collaboration involving researchers from Japan, Germany, Australia, and the United States. It also exemplifies the importance of interdisciplinary research, combining expertise in materials chemistry, condensed matter physics, neutron scattering, and computational modeling. By combining diverse expertise, the team revealed mechanisms of isotope-selective adsorption that would remain hidden within any single field. Publication Details: Title: Isotopologue-induced structural dynamics of a triazolate metal-organic framework for efficient hydrogen isotope separation Authors: Linda Zhang, Richard Röß-Ohlenroth, Vanessa K. Peterson, Samuel G. Duyker, Cheng Li, Jhonatan Luiz Fiorio, Jan-Ole Joswig, Robert Dinnebier, Dirk Volkmer, Michael Hirscher Journal: Nature Communications DOI: https://doi.org/10.1038/s41467-025-61107-3 Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/researchers_achieve_record_hydrogen_isotope_separation_via_isotopologuedriven_dynamics.html Advanced Institute for Materials Research, Tohoku University https://www.wpi-aimr.tohoku.ac.jp/en/achievements/press/2025/20250723_002011.html  

A study led by Tohoku University and The Japan Aerospace Exploration Agency (JAXA) developed a novel copper-based alloy that exhibits a special shape memory effect at temperatures as low as -220°C. Shape memory alloys can be molded into different shapes when cold, but will revert back to their original shape when heated (as if “remembering” their default state, like memory foam). This exciting new alloy has the potential to be used for space equipment and hydrogen-related technologies, where challenging, cold environments below -100°C are the norm. Dr. Sheng Xu from FRIS also participated in this research.   Figure 1: Strain change during cooling and heating under stress in Cu-Al-Mn-based alloy ©Shunsuke Sato et al.   Previously studied shape memory alloys using Ni-Ti could not maintain their shape memory ability below 0°C, despite their otherwise practical characteristics. In contrast, the known existing shape memory alloys that can actually operate below -100°C aren’t suitable for practical implementation. This study met the challenge of finding the first functional actuator material capable of large output at temperatures below -100°C. Actuators are components that turn some sort of input into mechanical energy (movement). They can be found not only in machines bound for outer space, but in everyday devices all around us.   The team of researchers prototyped a mechanical heat switch using a new alloy (Cu-Al-Mn) as an actuator. This switch was shown to operate effectively at -170°C, controlling heat transfer by switching between contact and non-contact states based on temperature changes. The operating temperature of the alloy can be adjusted by modifying its composition.   “We were very happy when we saw that it worked at -170°C,” remarks Toshihiro Omori (Tohoku University), “Other shape memory alloys simply can’t do this.”   Figure 2: Comparison of work output with several actuator materials and the Cu-Al-Mn shape memory alloys. ©Shunsuke Sato et al.   The Cu-Al-Mn alloy is the first actuator material capable of large output at temperatures below -100°C. This development paves the way for the realization of high-performance actuators that can operate even under cryogenic conditions, which could not be realized before. Potential applications include a reliable mechanical heat switch for cooling system in space telescopes. The simplicity and compactness of such mechanical heat switches make them a crucial technology for future space missions and for advancing carbon-neutral initiatives like hydrogen transportation and storage.   Figure 3:  (a) Mechanical heat switch using shape memory alloy and (b) temperature change during heating ©Shunsuke Sato et al. Publication Details: Title: Shape memory alloys for cryogenic actuators Authors: Shunsuke Sato, Hirobumi Tobe, Kenichiro Sawada, Chihiro Tokoku, Takao Nakagawa, Eiichi Sato, Yoshikazu Araki, Sheng Xu, Xiao Xu, Toshihiro Omori, Ryosuke Kainuma Journal: Communications Engineering DOI：https://doi.org/10.1038/s44172-025-00464-9 Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/new_cryogenic_shape_memory_alloy_designed_for_outer_space.html  

Rabi-like splitting is one of the key concepts in modern quantum technology. Fully understanding it can help us advance our knowledge in quantum information processing. Assistant Professor Aakanksha Sud (Tohoku University), Dr. Kei Yamamoto (JAEA), Professor Shigemi Mizukami (Tohoku University), and collaborators discovered that Rabi-like splitting could be achieved using nonlinear coupling, which remarkably preserves the symmetries of the system. This result opens up various possibilities to deepen our understanding of nonlinear dynamics and coupling phenomena in artificial control.   In quantum physics, when there is a coupling between two harmonic oscillators with an ideal oscillation frequency, the oscillation frequency splits to two different frequencies in the coupled system. The difference in these two frequencies is referred to as Rabi splitting.   The physics behind Rabi-splitting and the coupling of oscillations arising from artificial magnets have been popular topics for research. The system possesses two spatially uniform magnon modes: an in-phase mode resembling ferromagnetic behavior and an anti-phase mode with characteristic antiferromagnetic properties. Although the frequencies of these two modes are identical under some conditions (fulfilled by an externally applied magnetic field), a symmetry breaking within the system is required to manifest Rabi-like splitting. However, the current research study found a way to bend the rules.   “Typically, you need to break the symmetry of the system to achieve Rabi-like splitting in artificial magnet,” explains Shigemi Mizukami, “However, we were thrilled that both our experimental and theoretical studies showed that it could occur while still maintaining the symmetry of the system.” Figure: Schematic illustration of an artificial magnet, two oscillation modes, and non-linear coupling of two modes resulting in Rabi-like splitting. ©A. Sud et al. To achieve this, the researchers took advantage of nonlinear coupling. They induced nonlinear coupling with large radio-frequency currents, targeting an artificial magnet. This technique allows for the controlled manipulation of energy between modes.    These findings help deepen our understanding of nonlinear dynamics and coupling phenomena in artificial control, and may inform further research studies in this area. The research team plans to continue this project by directly applying this approach to devices that use high-speed signal processing.   The research was led by WPI Advanced Institute for Materials Research (AIMR), the Frontier Research Institute for Interdisciplinary Sciences (FRIS), the Research Institute of Electrical Communication (RIEC), the Center for Science and Innovation in Spintronics (CSIS), and the Graduate School of Engineering at Tohoku University, in collaboration with the Japan Atomic Energy Agency (JAEA) and University College London (UCL). The findings were published in Physical Review Letters on June 20, 2025. Publication Details: Title: Electrically Controlled Nonlinear Magnon-Magnon Coupling in a Synthetic Antiferromagnet Authors: A. Sud, K. Yamamoto, S. Iihama, K. Ishibashi, S. Fukami, H. Kurebayashi, and S. Mizukami Journal: Physical Review Letters DOI: https://doi.org/10.1103/sc6y-rxbg Press Release: Tohoku University https://www.tohoku.ac.jp/en/press/observation_of_rabilike_splitting_under_electrical_control_in_artificial_magnets.html Advanced Institute for Materials Research, Tohoku University https://www.wpi-aimr.tohoku.ac.jp/en/achievements/press/2025/20250716_002005.html Research Institute of Electrical Communication, Tohoku University https://www.tohoku.ac.jp/en/press/observation_of_rabilike_splitting_under_electrical_control_in_artificial_magnets.html Center for Science and Innovation in Spintronics, Tohoku University https://www.tohoku.ac.jp/en/press/observation_of_rabilike_splitting_under_electrical_control_in_artificial_magnets.html    

Book " Research Handbook on the Law of Artificial Intelligence: Current and Future Directions - 2nd Edition " Yueh-Hsuan Weng (Creative Interdisciplinary Research Division) co-authored   The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.   Publisher: Edward Elgar Publishing Date Published: June 2025 Format: Hardback ISBN： 978 1 03531 648 9 https://www.e-elgar.com/shop/gbp/research-handbook-on-the-law-of-artificial-intelligence-9781035316489.html