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Rethinking brittleness in ceramics: The emergence of room-temperature plasticity

For decades, brittleness has been regarded as an intrinsic characteristic of ceramics. Unlike metals, which can bend or deform before breaking, ceramic materials have long been expected to fail suddenly once their strength limit is reached. This conventional understanding has defined both the scientific perception of ceramics and their practical applications in engineering. Recently, a team of materials scientists led by Kexin Chen from the Advanced Structural Ceramics Innovation Center at Yongjiang Laboratory, China, published a comprehensive review that reexamines the long-held perception of ceramics as inherently brittle materials. The review brings together recent advances in room-temperature plasticity, covering deformation mechanisms such as dislocation motion, phase transformation, and grain boundary sliding; emerging strategies for enhancing plasticity; advanced in situ characterization and strain measurement techniques to reveal the interplay between microstructure, defects, and mechanical behavior; as well as potential engineering applications and future research priorities. The team published their work in Journal of Advanced Ceramics on July 21, 2026. “In this report, we reviewed systematically the research advancements in room temperature plasticity in various ceramics. Drawing together recent breakthroughs across multiple ceramic systems, it shows that room-temperature plasticity—once considered nearly impossible in ceramics—is becoming an emerging reality. The review demonstrates that ceramics are capable of irreversible deformation through a variety of mechanisms, fundamentally reshaping how scientists understand these traditionally brittle materials.” Said Kexin Chen, Director of the Advanced Structural Ceramics Innovation Center at Ningbo Yongjiang Laboratory (China), a senior expert whose research interests focus on the fabrication and plastic deformation mechanisms of room-temperature plastic ceramics, controllable synthesis of high-quality ultrafine ceramic powders, high-performance materials with ordered functional building blocks, and high-performance thermal management composite materials. “In this review, we examine the advances that have accumulated over the past several years across oxide ceramics, nitrides, carbides, layered ceramics, nanostructured materials, and architected ceramic systems. Rather than presenting a single experimental breakthrough, we provide what we believe is the first comprehensive framework that unifies the rapidly expanding body of evidence demonstrating that plastic deformation in ceramics can occur under ambient conditions. Historically, ceramics have been valued for their exceptional hardness, chemical stability, wear resistance, and ability to withstand extreme temperatures. These properties have made them indispensable in aerospace, electronics, energy systems, biomedical devices, and advanced manufacturing. However, their intrinsic brittleness has remained a major obstacle to broader structural applications. Because the stress required to activate dislocation motion in strongly ionic and covalent ceramics typically exceeds their fracture strength, cracks usually propagate before any significant plastic deformation can occur. This limitation has long been regarded as one of the fundamental challenges in materials science. In this review, we argue that this traditional picture is no longer sufficient. Recent studies have revealed multiple pathways through which ceramics can accommodate deformation at room temperature. These include dislocation-mediated plasticity, stress-induced phase transformations, grain-boundary sliding, deformation twinning, interface-mediated deformation, and amorphous flow. We emphasize that these mechanisms are no longer confined to isolated microscale experiments. Instead, increasing evidence demonstrates that carefully designed bulk ceramics and architected ceramic materials can also exhibit substantial deformability while maintaining their inherent strength and thermal stability. Beyond summarizing these deformation mechanisms, we highlight how advances in materials design are making room-temperature plasticity increasingly achievable. We show that defect engineering can activate mobile dislocations and lower the barriers to plastic deformation. Structural engineering—including coherent interfaces, layered architectures, nanocrystalline structures, and crystalline–amorphous composites—can improve deformation compatibility while suppressing catastrophic fracture. In addition, external-field regulation and nanoscale microstructural design provide further opportunities for tailoring mechanical behavior. We also emphasize that progress in this field has been driven by major improvements in characterization techniques. Modern in situ transmission electron microscopy, synchrotron-based measurements, high-resolution strain mapping, and advanced mechanical testing now allow researchers to directly observe dislocation motion, phase transformations, grain-boundary behavior, and interface evolution during deformation. These experimental capabilities have significantly enhanced our understanding of how atomic-scale defects and microstructures govern macroscopic mechanical performance. Importantly, we distinguish several concepts that are often confused in ceramic research. Improved fracture toughness does not necessarily imply plasticity, and nonlinear deformation does not always represent true irreversible plastic flow. Accordingly, we propose a clearer framework for distinguishing intrinsic plasticity arising from crystal-lattice deformation from extrinsic plasticity originating from grain boundaries, interfaces, or engineered architectures. We believe that this unified perspective provides a common language for comparing different ceramic systems and evaluating future advances. Although remarkable progress has been achieved, we recognize that significant challenges remain before plastically deformable ceramics can be widely adopted in engineering applications. Most demonstrations of room-temperature plasticity have been limited to specific materials, carefully engineered microstructures, or small-scale specimens. Achieving reliable and scalable plastic deformation in bulk ceramics while maintaining high strength, long-term stability, and manufacturing feasibility remains an important objective for future research. Looking forward, we suggest that future efforts should focus on discovering intrinsically plastic ceramic systems, developing scalable fabrication strategies, integrating multiscale structural design, and combining experimental characterization with computational modeling. We believe that such advances could enable a new generation of ceramic materials that combine exceptional hardness, thermal stability, and chemical resistance with unprecedented damage tolerance and deformability. Overall, rather than overturning decades of ceramic science, we present a more nuanced understanding of ceramic mechanics. In our view, brittleness should no longer be regarded as an unavoidable material property, but rather as a mechanical behavior that can be tailored through atomic-scale defects, microstructural architecture, and materials design. As research in this area continues to expand, we anticipate that room-temperature plasticity will become a defining feature of next-generation structural ceramics, opening new opportunities for applications ranging from aerospace and energy technologies to electronics and advanced manufacturing.” Other contributors include: Zhitong Xu, Jie Zhang, Liran Dong, Yuanwei Chao from Advanced Structural Ceramics Innovation Center, YongJiang Laboratory in Ningbo, China; Guanghua Liu from State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing in Beijing, China.   About Author Kexin Chen, Director of the Advanced Structural Ceramics Innovation Center at Ningbo Yongjiang Laboratory, Research Professor and Doctoral Supervisor at the State Key Laboratory for Advanced Metals and Materials. He is a Distinguished Young Expert with Outstanding Contributions under the National Ten-Thousand Talents Program and a Recipient of the Special Government Allowance from the State Council. After earning his doctoral degree from the University of Science and Technology Beijing (USTB) in 1997, he successively served as Lecturer, Associate Professor and Professor in the Department of Materials Science and Engineering, Tsinghua University. He previously worked at the National Natural Science Foundation of China (NSFC). Currently, he is affiliated with the State Key Laboratory for Advanced Metals and Materials, USTB, and serves as. He also holds concurrent posts as Deputy Secretary-General of the Chinese Ceramic Society, and serves on the editorial boards of academic journals including Journal of Materials Research, Journal of the Chinese Ceramic Society, Chinese Science Bulletin, and Journal of Materiomics. Funding This work was supported by the National Key Research and Development Program of China (No.2025YFF0520903), the National Natural Science Foundation of China (No.U23A20566 and No.52531005), Natural Science Foundation of Zhejiang Province (No.LZYQ25E020001 and No.LD26E010002), “Pioneer” and “Leading Goose” R & D Program of Zhejiang (Grant No.2024SSYS0051), Young Scientists Innovation Team of Zhejiang Province (Grant No.2025TD2072), the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (CAST) (Grant No. 2024QNRC001). DOI Link: https://doi.org/10.26599/JAC.2026.9221353 About Journal of Advanced Ceramics Journal of Advanced Ceramics (JAC) is an international academic journal that presents the state-of-the-art results of theoretical and experimental studies on the processing, structure, and properties of advanced ceramics and ceramic-based composites. JAC is Fully Open Access, monthly published by Tsinghua University Press, and exclusively available via SciOpen. JAC’s 2025 IF is 14, ranking in Top 1 (1/34, Q1) among all journals in “Materials Science, Ceramics” category, and its 2025 CiteScore is 24.6 (6/133) in Scopus database. ResearchGate homepage: https://www.researchgate.net/journal/Journal-of-Advanced-Ceramics-2227-8508
Ceramics

New cathode material brings aqueous zinc-ion batteries closer to reality

One of the biggest challenges facing scientists and engineers in the clean energy era isn’t how to make energy using sun and wind, it’s how to store it.Traditionally, lithium-ion batteries have been used in vehicles because they can store a large amount of power in a small space, waste only a small amount of energy during charging and discharging and respond quickly to shifts in power demand. Despite these advantages, lithium-ion batteries pose flammability risks, are prone to supply chain shortages and are expensive, prompting research into other material technologies for the batteries of the future. One technology researchers have investigated for use in battery applications is aqueous zinc-ion batteries (AZIBs). In contrast to traditional lithium-ion batteries, AZIBs use divalent zinc ions (Zn²⁺, a positively charged metal atom that has lost two electrons) instead of monovalent lithium ions (Li⁺) as a charge carrier, or the moving particle that carries an electric charge to create a flow of electricity. Further, AZIBs use safe, water-based mild acid or neutral salt solutions instead of volatile, highly flammable organic liquid solvents as an electrolyte, making them non-flammable. The anodes of AZIBs, or source of electrons and the place where chemical oxidation occurs, are also made of cheap, abundant zinc rather than lithium compounds, making them more cost effective. Finding an ideal cathode, or positively charged electrode that acquires electrons during discharge, for AZIBs has been the major bottleneck for developing the technology. To address this issue, a team of researchers from Chongqing University, Guizhou Education University, Hainan University and Taizhou University explored the use of manufactured electrolytic manganese dioxide (MnO2) as an AZIB cathode material due to its low cost, abundance, high capacity for energy storage and safety. The team published their paper, “Unveiling the action mechanism of synergistic d/p-band center modulation on the zinc storage capability of industrial-grade MnO2 cathode,” on July 15 in Nano Research Energy, published by Tsinghua University Press. “The practical application of industrial manufactured electrolytic MnO2 (EMD) is hampered by its poor intrinsic conductivity ability to conduct electricity, which slows reaction kinetics, and its structural instability during cycling charging and discharging. The latter leads to irreversible phase transitions thermodynamic shifts that cannot return the system to its initial state without adding outside energy, structural degradation and consequent manganese dissolution, causing irreversible capacity loss. Therefore, the exploration of EMD cathodes represents a critical step in bridging the gap between fundamental research and the practical implementation of AZIBs… and commercially viable grid-scale energy storage solutions,” said Zhenyue Xing, associate professor in the School of Materials Science and Engineering at Hainan University in Haikou, China and an author of the research study. One way to enhance the electronic conductivity, weaken the electrostatic trapping of Zn²⁺ ions and accelerate the ion diffusion kinetics of EMD is to engineer oxygen defects, or missing oxygen atoms in the crystal structure of a solid material, like MnO2, in commercial EMD. These defects leave extra electrons behind and allow electrons to move freely through the material. The researchers used ball milling, a process using the mechanical tumbling or vibrating of heavy balls inside a container to grind powders, as a cost-effective way to engineer oxygen defects in EMD. Through this process, mechanical shear striking energy allows lattice oxygen in EMD to escape. The team measured the basic properties of ball-milled EMD compared to native EMD, such as adsorption energies (the binding strength between a molecule and a surface) and kinetic barriers, reflected in Zn2+ and H+ ion migration energies, or the energy barriers that charged atoms or molecules must overcome to move through a solid material or crystal lattice. “Following ball-milling treatment, the oxygen content of EMD decreases from 68.93% to 61.17%, while the manganese content correspondingly increases from 31.07% to 38.83%. This compositional shift indicates the formation of oxygen vacancies (Ov) within the MnO2 structure. The presence of Ov promotes electron transport via the induced half-metallicity (a property where electrons of one spin direction conduct electricity like a metal, while electrons of the opposite spin behave like an insulator) that improves conductivity, which can improve MnO2 cathode electrochemical performance,” said Xing. The researchers discovered that the oxygen defects in ball-milled EMD shift the energy levels of metal (d)-bands and non-metal (p)-bands, which refer to the atomic orbitals that confer conductive metal or nonmetal properties, to balance ion binding energies, preventing trapping or retention of Zn2+ and H+ ions, one of the disadvantages of native EMD. This shift in energy levels also lowers diffusion barriers (the energy required for ions to move through a lattice structure) and limits the structural distortions observed in EMD during cycling. “This study not only provides a high-performance electrode material for advanced ZIBs but also offers profound mechanistic insights into the critical role of defect chemistry in regulating reaction kinetics, presenting a promising and scalable pathway for the development of next-generation energy storage materials,” said Xing. Pengyang Xia, Zutao Zhu, Liang Luo, Linfang Hu and Bin Xiang from the College of Chemistry and Chemical Engineering at Chongqing University in Chongqing, China; Xuefeng Zou, Kaiwen Zhang and Yao Zhang from the Guizhou Provincial Key Laboratory of Critical Materials and Devices for Solid-State Batteries in the Guizhou Provincial Key Laboratory of Computational Nano-Material Science at Guizhou Education University in Guiyang, China; Mingyang Chen and Xiaodong Shi from the State Key Laboratory of Tropic Ocean Engineering Materials and Materials Evaluation in the School of Materials Science and Engineering at Hainan University in Haikou, China; Yang Zhou from the Analytical and Testing Center of Chongqing University in  Chongqing University; and Lijin Yan from the School of Pharmaceutical and Chemical Engineering at Taizhou University in Zhejiang, China also contributed to this research. This work was supported by the National Natural Science Foundation of China (22569005, 22562010), the Science and Technology Project of Guizhou Province (QKHJC-ZK[2023]ZD030), the Natural Science Foundation of Chongqing(CSTB2025NSCQ-GPX0762), the Major Science and Technology Project of Guizhou Province (QKHZDZXZ[2024]022), the National Defense Science and Technology Key Laboratory Foundation (61420052022WD008), the Doctoral Program of Guizhou Education University (X2024071), and Guizhou Provincial Key Laboratory of Critical Materials and Devices for Solid-State Batteries (No.ZSYS(2025)036). DOI Link: https://doi.org/10.26599/NRE.2026.9120255
Nanoscience and Nanotechnology

Researchers uncover the origin of activation in high-capacity lithium-ion anodes

Rechargeable lithium-ion batteries with high energy density and long cycle life are increasingly needed for applications ranging from portable electronics to electric vehicles and smart grids. To meet these demands, researchers have been exploring high-capacity anode materials that operate through conversion and/or alloying reactions. These materials can store far more lithium than conventional graphite anodes, but they also face major challenges during battery operation. One particularly puzzling issue is a phenomenon known as activation. In many high-capacity anodes, battery capacity initially drops and only gradually recovers over repeated charge-discharge cycles. This process delays full capacity utilization and can compromise the structural integrity of the electrode. Although activation has been widely observed in high-capacity materials, its origin has remained unclear. The research team led by Prof. Fangxi Xie and Mingmei Wu at Sun Yat-sen University, China, in collaboration with Dr. Shengfu Tong from Jinhua Advanced Research Institute, China, and Prof. David Kisailus from the University of California, Irvine, USA, systematically revealed the origin of the activation process in high-capacity lithium-ion battery materials and elucidated its underlying size-dependent mechanism. Their findings show that particle size plays a decisive role in determining whether activation occurs. The team published their research in Nano Research on July 2, 2026. They found that electrodes made of large particles (~500 nm) exhibited pronounced activation behavior during cycling, whereas electrodes made of small particles (~65 nm) showed little to no activation. By tracking the evolution of characteristic elements at different cycling stages, the researchers discovered that lithiation proceeds very differently in the two systems. In small-particle electrodes, electrolyte can rapidly penetrate and facilitate lithiation. In contrast, large-particle electrodes require substantially more time for the electrolyte to fully access the active material. To understand the origin of this size dependence, the researchers combined experimental observations with finite-element simulations and electrochemical kinetic analyses. They found that the distinct activation behaviors arise from a stress-induced retardation effect associated with a core-shell lithiation mode. During the lithiation of larger particles, compressive stress accumulates in the lithiated outer shell, hindering lithium transport and delaying the inward lithiation. This stress-induced kinetic retardation gives rise to the prolonged activation behavior observed in large-particle electrodes. In contrast, the stress effect is much less pronounced in smaller particles, allowing lithiation to proceed more easily and enabling stable cycling with little to no activation. The findings provide a new mechanistic understanding of activation in high-capacity lithium-ion anodes and suggest practical strategies for improving battery performance. By tailoring particle size and controlling lithiation kinetics, it may be possible to reduce or even avoid activation, accelerate full capacity utilization, and improve the cycling stability of advanced battery materials. Other contributors include Shuting Fu, Shiman He, Xuxu Wang, Xiaohui Li, and Junyu Hong from Sun Yat-sen University, China. This work was supported by the National Natural Science Foundation of China (NSFC) (Nos. 22405297, 51672315, U1801251 and 21403106), the talent recruitment project of Guangdong (No. 2023QN10C330), the Multi-University Research Initiative (AFOSR-FA9550-15-1-0009) and the Winston Chung Global Energy Center. DOI Link: https://doi.org/10.26599/NR.2026.94908669 About Nano Research Nano Research is a peer-reviewed, open access, international and interdisciplinary research journal, sponsored by Tsinghua University and the Chinese Chemical Society, published by Tsinghua University Press on the platform SciOpen. It publishes original high-quality research and significant review articles on all aspects of nanoscience and nanotechnology, ranging from basic aspects of the science of nanoscale materials to practical applications of such materials. After 18 years of development, it has become one of the most influential academic journals in the nano field. Nano Research has published more than 1,000 papers every year from 2022, with its cumulative count surpassing 8,000 articles. In 2025 InCites Journal Citation Reports, its 2025 IF is 9.4 (8.3, 5 years), and it continues to be the Q1 area among the four subject classifications. Nano Research Award, established by Nano Research together with TUP and Springer Nature in 2013, and Nano Research Young Innovators (NR45) Awards, established by Nano Research in 2018, have become international academic awards with global influence.
Nanoscience and Nanotechnology

Wind-assisted propulsion could help put greener shipping within reach

International shipping carries much of the world’s trade and accounts for approximately 3% of global human-caused greenhouse gas (GHG) emissions. As international and regional regulations place increasingly stringent limits on GHG emissions, the maritime industry needs technologies that can reduce fuel. Wind-assisted propulsion systems (WAPSs), offer one possible near-term solution. Rather than converting wind into electricity, they use aerodynamic forces to produce thrust directly. They operate alongside a ship’s main propulsion system, reducing engine load and fuel consumption when wind conditions are favorable. A team led by Wenzhe Zhang from the Universidad Politécnica de Madrid has now published a comprehensive techno-economic review of WAPSs in Ocean. The researchers examined scientific studies, industrial developments, classification-society guidance and lifecycle assessment methods to determine how wind-assisted propulsion can be integrated into commercial shipping safely, efficiently and economically. The review classifies modern WAPS into four main categories. Rotor sails use electrically driven rotating cylinders to generate force through the Magnus effect. Boundary-layer control sails use active suction or air injection to prevent airflow separation and increase lift. Wing sails rely on aerodynamic profiles and adjustable angles or flaps, while kite sails fly at altitude and can follow dynamic crosswind trajectories to generate towing force. “Wind-assisted propulsion is not simply a return to traditional sailing. Modern systems combine aerodynamic design, automation and ship-level control with conventional propulsion, allowing vessels to use wind energy without sacrificing operational reliability,” Zhang said. The authors screened more than 400 records and selected 212 highly relevant publications for detailed analysis. Their assessment shows that research activity has risen rapidly, particularly since 2020. Wing sails have received the greatest academic attention, whereas rotor sails and boundary-layer control sails currently attract stronger commercial interest. Rotor sails, boundary-layer control sails and wing sails have reached full commercial maturity in some applications. Kite sails remain at a lower and more variable level of technological readiness because reliable automated launching, recovery and flight control remain challenging. The review emphasizes that aerodynamic efficiency alone does not determine whether a system will succeed. Wind-assisted devices can affect vessel stability, visibility, maneuverability, deck operations and interactions with the main engine and propeller. Their design must therefore balance three objectives: safety, propulsion efficiency and lifecycle cost. Real-world performance is another major issue. Numerical simulations and scaled experiments sometimes indicate fuel savings of around 20%, but operational measurements summarized in the review generally report savings below 10%. Complex marine environments, differences among routes and ships, system-control strategies and ship–sail interactions can all contribute to this gap. “Shipowners need credible estimates of fuel savings and investment returns under realistic operating conditions. Standardized sea-trial procedures, full-scale operational datasets and digital twins could help connect theoretical predictions with actual performance,” Zhang said. The researchers propose evaluating the technology across its full lifecycle. Such assessments should include emissions and costs associated with manufacturing, transportation, installation, dry-docking, maintenance, additional electricity use, possible cargo-space losses, decommissioning and recycling. Fuel savings, avoided emissions and reductions in carbon-related expenses should be considered alongside those costs. The review identifies nine priorities for future research: optimizing high-lift and kite technologies; improving multi-device layouts; developing dedicated design standards; integrating WAPS with ship-level predictive control; introducing structural health monitoring and digital twins; assessing maneuverability and collision avoidance; building data-driven performance models; conducting comprehensive lifecycle assessments; and quantifying the effects of carbon pricing and other policy incentives. The ultimate goal is to move from controlling individual sails for maximum thrust to optimizing the vessel as a complete system. By jointly managing weather routing, engine load, vessel speed and wind-assisted devices, ships could capture more wind energy while maintaining safety and schedule reliability. “Wind-assisted propulsion will not be a universal or stand-alone solution to shipping emissions, but it can become an important part of an integrated decarbonization strategy—particularly for existing ships that need practical reductions in the near term,” Zhang said. This research has been funded by the Ministry of Science, Innovation and Universities (MCIU) of Spain under the project FOWTDAMP2 (Grant No. PID2021-123437OB-C21), and project RENEWFLOAT (Grant No. PID2024-161775OB-C21).   DOI Link: https://doi.org/10.26599/OCEAN.2026.9470019   About Ocean Ocean is an international peer-reviewed journal that offers open access and serves as a multidisciplinary platform for the state-of-the-art research and practice in the domains of ocean science, technology, and engineering. The journal is dedicated to publishing articles, reviews and perspectives in these areas, with the goal of promptly disseminating and promoting theoretical, numerical, site-based, and experimental advancements in the context of global sustainability.
Physical Sciences and Engineering

Solving the increasing complexity of AI problem-solving one bite at a time

“How do you eat an elephant? One bite at a time,” goes the proverb that dates back to the early 1920s. Turns out the same idea may apply to advancing artificial intelligence (AI), according to a team from the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University. The researchers developed a framework they call the “calculus of intelligence,” or COIN, capable of breaking down the increasingly complex problems agentic AI — the systems expected to operate with minimal human oversight to do things like monitor for cybersecurity breaches, write code and much more — is tasked with solving. They published their approach on July 17 in iFuture. “The calculus of intelligence is a mathematical framework for decomposing a complex task into smaller, well-defined subtasks that are simple enough to solve, and then combining their solutions into a coherent whole,” said Yang Yuan, associate professor and corresponding author on the paper. “Just as classical calculus can calculate the area under a complicated curve by dividing it into tiny pieces and adding them up, this framework provides a way to build and understand complex systems through the step-by-step composition of numerous simple components.” The framework translates splices up the overarching AI goal into smaller tasks within a logic system called a Grothendieck topos, which Yuan described as a mathematical rulebook for facilitating the coordination of building something as complex as a large airplane. “It must be divided into many local components — such as the wings, engines and control systems — which are designed by different teams,” Yuan said, explaining that these limited perspectives are the local views, with each team only seeing the information relevant to its own task rather than every detail of the entire airplane, while still retaining the shared information needed to connect its component to the rest of the system. “This allows different teams to work independently while ensuring that the components they produce match at their shared boundaries.” The Grothendieck topos expresses the structure of local design, shared interfaces and global coordination in mathematical language. It specifies what each local component can see, what requirements it must meet and how different components must agree where they overlap. According to Yuan, COIN takes the next step by providing the rules for decomposing tasks and reliably recomposing local solutions that comply with the larger system’s rulebook. “Intelligence resides in structure, and structure can be decomposed, learned and recompose,” Yuan said, noting that complexity does not mean incomprehensibility. “Many systems that appear overwhelmingly complex may simply be waiting for the right decomposition. A good structure can turn a difficult global problem into a collection of clearly bounded local problems that can be analyzed step by step. Through appropriate structural decomposition, many complex tasks can become easier to understand, execute and verify.” This structure can also lend itself to making extremely large systems with limited intelligence, Yuan pointed out. “The truly transformative future may not be an infinitely powerful individual intelligence — how some may imagine AI — but rather humans using many limited intelligences to construct systems far beyond the scale that any single person or model could independently understand or complete,” Yuan said.  According to Yuan, COIN is a step in that direction. “The broader goal is to develop a common mathematical language for intelligence: One that can describe what models learn, how complex tasks are decomposed and how many limited intelligences can be organized into larger systems,” Yuan said. Andrew Chi-Chih Yao, professor and dean of IIIS, co-authored this paper. Yuan and Yao are also affiliated with the Shanghai QiZhi Institute. DOI Link: https://doi.org/10.26599/IF.2026.9710001 About iFuture iFuture is a premier open-access journal published by Tsinghua University Press on the SciOpen platform, with academic support​ from the Institute for Interdisciplinary Information Sciences at Tsinghua University. Led by Turing Award Laureate Prof. Andrew Chi-Chih Yao​ as Editor-in-Chief, the journal is the core component of the AI Open Alliance. Its core mission is to break through AI’s theoretical bottlenecks and foundational infrastructure.
Information Sciences

Can Large Language Models Capture Human Risk Preferences?

Large language models (LLMs) are increasingly used as agents to simulate human behavior, yet their fidelity in complex decision-making under uncertainty remains insufficiently understood. To address this gap, we develop a comparative framework that benchmarks LLM-simulated risk preferences against empirical human behavior. Using demographic profiles from surveys conducted in Sydney, Hong Kong, and Nanjing, we construct role-playing prompts and evaluate three LLMs on abstract lottery-choice tasks. We adopt the classical Constant Relative Risk Aversion (CRRA) framework as a domain-neutral “standard ruler” to compare risk attitudes. The analysis yields three main findings. First, off-the-shelf LLMs do not exhibit a universal risk profile: the two GPT models are more risk-averse than human benchmarks, whereas Gemini is more risk-seeking. Second, prompt language systematically affects simulated risk attitudes, with English-to-Chinese switching inducing a more conservative shift in most cases. Third, LLMs do not reliably reproduce the empirical heterogeneity of human risk preferences, tending either to generate overly concentrated distributions or unrealistically large dispersion. Taken together, these findings show that off-the-shelf LLMs remain vulnerable to model-family-specific miscalibration, language-sensitive distortions, and failures in distributional fidelity. Rigorous empirical calibration is therefore necessary before off-the-shelf LLMs can be reliably deployed in computational social science and choice modeling. The team published their study in Communications in Transportation Research (https://doi.org/10.26599/COMMTR.2026.9640025). Our findings highlight an important limitation of using off-the-shelf LLMs as tools for behavioral prediction. Since different model families exhibit different baseline calibration biases, the choice of model can materially affect the inferred pattern of public risk preferences. In practice, one model family may overstate conservatism, whereas another may overstate willingness to accept risk. Without empirical calibration, such biases can distort inference and lead researchers to draw policy conclusions that do not accurately reflect observed human behavior. This limitation is particularly consequential in transportation research, where risk perception is central to decision-making under uncertainty. Travel behavior frequently involves probabilistic trade-offs, including route choice under unreliable travel times, mode switching during service disruptions, and the adoption of emerging mobility technologies under safety and performance uncertainty. If the underlying risk preference parameters are systematically miscalibrated, demand forecasts, welfare evaluation, and policy design may all be biased. For example, using uncalibrated LLM-generated data to infer willingness to adopt safety-critical systems such as autonomous vehicles or low-altitude mobility services could yield either overly conservative or overly optimistic projections, depending on the model family used. The multilingual results add a further layer of caution. In linguistically diverse settings, prompt language is not a neutral implementation choice: it can systematically perturb the behavioral calibration of the model. This is especially relevant for transportation systems serving multilingual populations, where researchers may be tempted to use native-language prompting as a straightforward way to improve realism. Our results suggest that such an assumption is unwarranted unless the model has first been validated against human benchmarks in the relevant linguistic context.   Overall, the implications of this study are methodological as much as substantive. Off-the-shelf LLMs should not be treated as direct substitutes for human respondents in risk-sensitive behavioral applications. Instead, they should be regarded as tools whose outputs require domain-specific and language-sensitive calibration. Rigorous validation against human ground truth remains a necessary prerequisite for deploying these models in transportation and other cross-cultural social science settings.   DOI Link: https://doi.org/10.26599/COMMTR.2026.9640025   About Communications in Transportation Research Communications in Transportation Research was launched in 2021, with academic support provided by Tsinghua University and China Intelligent Transportation Systems Association. The Editors-in-Chief are Professor Xiaobo Qu, a member of the Academia Europaea from Tsinghua University, and Professor Xiaopeng (Shaw) Li from University of Wisconsin–Madison. The journal mainly publishes high-quality, original research and review articles that are of significant importance to emerging transportation systems, aiming to serve as an international platform for showcasing and exchanging innovative achievements in transportation and related fields, fostering academic exchange and development between China and the global community. It has been indexed in SCIE, SSCI, Ei Compendex, Scopus, CSTPCD, CSCD, OAJ, DOAJ, TRID and other databases. It was selected as Q1 Top Journal in the Engineering and Technology category of the Chinese Academy of Sciences (CAS) Journal Ranking List. In 2022, it was selected as a High-Starting-Point new journal project of the “China Science and Technology Journal Excellence Action Plan”. In 2024, it was selected as the Support the Development Project of “High-Level International Scientific and Technological Journals”. The same year, it was also chosen as an English Journal Tier Project of the “China Science and Technology Journal Excellence Action Plan Phase Ⅱ”. In 2024, it received the first impact factor (2023 IF) of 12.5, ranking Top1 (1/58, Q1) among all journals in "TRANSPORTATION" category. In 2026, its 2025 IF was announced as 12.7, maintaining the Top1 position (1/66, Q1) in the same category. From Volume 6 (2026), Communications in Transportation Research will be published by Tsinghua University Press on the SciOpen platform with the official journal website at https://www.sciopen.com/journal/2097-5023. We kindly request that all new manuscript submissions be made through the journal’s submission system at https://mc03.manuscriptcentral.com/commtr. For any submission-related inquiries, please contact the Editorial Office at commtr_e@mail.tsinghua.edu.cn.
Physical Sciences and Engineering

Can China maintain power supply security while phasing down coal?

China’s renewable power expansion is reshaping the country’s electricity system and raising a question: how can China maintain power supply security while reducing its reliance on coal? Wind and solar power are variable by nature, and their rising share changes the role of conventional power plants. As noted in the paper, variable renewable energy reached 18.2% of China’s power generation in 2024 and is expected to grow to 65%-70% by 2060. As this transition continues, coal plants may operate fewer hours and face weaker revenues, while the system requires more flexibility to balance fluctuating renewable output. A research team led by Tsinghua University examined this challenge using causal loop diagrams to trace feedback mechanisms among renewable deployment, storage investment, market price signals, capacity remuneration, and coal retirement decisions. The article was published in Energy and Climate Management on May 25, 2026. According to the study, China’s current coal capacity payment mechanism may help stabilize coal plant revenues, but it also has potential drawbacks. Because the mechanism mainly supports incumbent coal and gas capacity, it may exclude emerging flexible resources such as battery storage, demand-side response, distributed resources, and virtual power plants. The paper also points out that administratively determined payments may create risks of overpayment, weaker innovation incentives, and delayed retirement of inefficient coal assets. The study contrasts this approach with the United Kingdom’s capacity market, which uses competitive auctions to procure reliable capacity from multiple technologies. The UK experience suggests that market-based capacity mechanisms can help reveal capacity prices and support a more diverse resource mix. At the same time, the paper notes a design challenge: if capacity markets treat all resources similarly without considering duration, short-duration batteries may be favored even when longer-duration resources are needed during prolonged system stress events. As noted in the paper, battery energy storage systems can absorb surplus renewable electricity and discharge it when demand rises, helping reduce curtailment and improve system flexibility. However, China’s earlier energy storage mandates produced mixed effects. Although these policies encouraged physical deployment, the average utilization rate of covered storage capacity was only 9% in 2023. One reason highlighted by the study is that storage assets often lacked sufficient market access and revenue opportunities. In the first half of 2023, thermal generators received 91.4% of ancillary service market revenues. The paper suggests that China could deepen spot market reforms, adjust overly restrictive price limits, and expand competitive ancillary service markets so storage can earn revenues from arbitrage, frequency regulation, capacity mechanisms, and other services. Rather than requiring each renewable project to self-balance with its own storage, the study points to the value of treating flexibility as a system-wide resource. The paper also discusses long-duration energy storage as an important option for maintaining supply security. It notes that China may require more than 700 GW of long-duration storage capacity in a fully decarbonized power system. Strategic reserves are presented as another possible transitional tool, under which some retiring coal units could be kept outside the regular electricity market and called upon only during system stress events. The study suggests piloting capacity markets, creating broader revenue channels for storage, supporting long-duration storage, strengthening carbon pricing through an emissions cap and price floor, and using strategic reserves where older coal fleets may still be relevant for reliability. The research was primarily conducted by Ying Zhou (first author), Jian Han (corresponding author) and Da Zhang (corresponding author). This work was supported by the National Natural Science Foundation of China (Nos. 72401160 and 72504282), the International Science and Technology Cooperation Project (No. 20253000014), the China Three Gorges Corporation Research Project (No. 202303160), and the Sichuan Province Science and Technology Innovation Cooperation Project for Hong Kong, Macao and Taiwan (No. 2025YFHZ0226).   DOI Link: https://doi.org/10.26599/ECM.2026.9400033   About the Authors: Ying Zhou conducted her postdoctoral research at the Institute of Energy, Environment and Economy, Tsinghua University, China. She is currently a faculty member in the School of Management, China University of Mining and Technology-Beijing. Her research focuses on energy and power system decarbonization, renewable electricity markets, electricity market design, and climate policy evaluation. Jian Han conducted his postdoctoral research at the Institute of Energy, Environment and Economy, Tsinghua University, China. He is focusing on energy economics, electricity markets, and agent-based modeling. Da Zhang is Assistant Director of the Institute of Energy, Environment and Economy at Tsinghua University, Tenured Associate Professor, and Ph.D. Supervisor. He also serves as Deputy Director of the Tsinghua-Three Gorges Climate and Low-Carbon Center. His research focuses on energy economics, climate policy, low-carbon energy transition, integrated assessment modeling, and electricity market design.
Humanities and Social Sciences

Research team combines machine learning with environmental technology to achieve healthier soil

Scientists have environmental recycling processes that convert farm and forestry waste and polluted soil into useful energy and other useful materials. However, it has been very challenging to precisely control these processes. A research team is using machine learning to regulate the environmental processes, so they are more effective and predictable. Their work provides a technical path for achieving precise, intelligent, and sustainable remediation of polluted soil. Their research was published in the journal Environmental Chemistry and Safety on July 1, 2026. Co-pyrolysis technology is an environmental recycling process that heats waste products from farms and forests, along with polluted soil, in an oxygen-limited environment. This heating reaction converts the waste products and polluted soil into fuel and other useful materials. The challenge that scientists have faced with the co-pyrolysis technology lies with the differences in the raw materials. Because each batch of raw materials behaves a little differently, it is difficult for scientists to accurately control the co-pyrolysis process. The research team from Panzhihua University, Tsinghua University, and Harbin Institute of Technology has developed a theoretical framework that combines machine learning with the co-pyrolysis technology to provide a precise and sustainable solution to turn polluted soil to clean soil. The world produces over 2 billion tons of farm and forest waste every year. Most of this waste is not used in any way. At the same time, more than one-third of the world’s farmlands cannot be used for farming because the soil is polluted with toxic chemicals. Much of the plant waste is dumped in landfills or burned, which causes air pollution. Cleaning the polluted soil requires methods that harm the soil’s health and create new pollution. These two environmental problems are connected to each other. The co-pyrolysis technology offers a solution for farm and forest waste and polluted soil. This process “bakes” the plant waste and polluted soil under oxygen limited conditions.  The plant waste and polluted soil react better together than either of them would work on their own. The reaction that occurs cracks and destroys the organic pollutants and traps the heavy metals so they can no longer harm the environment. Finally, the process turns the waste and soil into a high-performance charcoal-like substance called biochar. While the co-pyrolysis technology offers a promising solution to these environmental problems, the process has been hard to control. Each batch of plant waste and polluted soil is different, making it hard to predict and control the exact repair effects they can achieve. The advances in machine learning technology in recent years give scientists the tools they need to better manage the co-pyrolysis process. Algorithms, such as deep learning, neural networks, and reinforcement learning, help scientists better understand the complex data related to the co-pyrolysis process. Machine learning tools let them to fix the polluted soil at different sizes, ranging from the molecular level all the way to the larger ecosystem. Using machine learning with the co-pyrolysis methods allows scientists to predict the connections across entire process. “Compared to traditional experience-oriented process development models, the core advantage of machine learning driven co-pyrolysis closed-loop design lies in its ability to model and predict high-dimensional nonlinear relationships across the entire chain of raw materials, processes, products, and ecological responses,” said Yuanchuan Ren, Panzhihua University, China. Looking to the future, the research team suggests that the co-pyrolysis closed-loop system that recycles waste could have potential for use beyond Earth. “The technical framework and engineering methods of the co-pyrolysis closed-loop system are expanding beyond the scope of Earth's environmental remediation, gradually extending to the utilization of in-situ resources in extraterrestrial celestial bodies and the construction of interstellar human settlements,” said Ren. The research team includes Yuanchuan Ren, Yuhang Lin, Xuejun Zhu, Hongbo Han, Shiyong Zhao, Renjie Huang, Tingfeng Su, Yan Guo, Fenghui Wu, Qiang Niu, Dandan Chen from Panzhihua University; Cheng Wang from Tsinghua University; and Nanqi Ren from Harbin Institute of Technology. This research is funded by Sichuan Science and Technology Program, the Panzhihua Key Laboratory of Chemical Resource Utilization Open Science Project, Panzhihua Association for Science and Technology Youth Science and Technology Talent Support Project, the Key Laboratory of Dry-hot Valley Characteristic Bio-Resources Development at University of Sichuan Province, and The College Students' Innovation and Entrepreneurship Training Program. DOI Link: https://doi.org/10.26599/ECS.2026.9600049  
Physical Sciences and Engineering

Spinning up a better understanding of molecules

One hundred years after the technique was recognized with the Nobel Prize in Chemistry, analytical ultracentrifugation (AUC) is still making waves in the scientific world. Theodor Svedberg developed the approach in the 1920s, using it to characterize tiny gold particles. Now, AUC helps researchers determine specific properties of individual molecules clustered together, such as those used in pharmaceuticals or industrial chemicals.     A team led by researchers at the University Akron recently published a review of the technology, cataloging use cases focused on how AUC can help solve challenges in characterizing molecular clusters. These clusters comprise clumps of proteins, sugars and other particles that scientists need to understand in deep detail to predict interactions, stability and more of the many diverse solutions encountered across a bevy of areas. They published their work on May 27 in Polyoxometalates. “Analytic ultracentrifugation is a powerful and information-rich technique for characterizing the molecular weight, size, shape, dispersity and association behavior of species in their native solution environment,” said corresponding author Tianbo Liu, professor in the Department of Polymer Science at the University of Akron. “With recent instrumentation and data analysis software, AUC enables more accurate and reliable characterization of diverse species in solution systems, including biomacromolecules, like proteins and carbohydrates; colloids, such as nanoparticle suspensions; surfactants assemblies such as micelle; and polymers, including synthetic polymers in solution and polymer-based nanoparticles in dispersion.” AUC works by spinning solution samples up to 60,000 rotations per minute, forcing the contents to sediment, or to disperse into concentrated gradients based on size and weight. The approach also integrates optical analytics to monitor and characterize the sedimentation of each molecule, taking AUC a step beyond traditional centrifugation, according to Liu. “This overcomes a key limitation of techniques such as light and X-ray scattering, which typically measure the collective properties of solute mixtures,” Liu said, explaining that the other techniques work by assessing how light or X-rays at a sample scatter. He noted that AUC also lacks the need for stationary phases or calibration standards like other techniques, such as chromatography, enabling direct, absolute determination of molecular properties. Another benefit of AUC is that the measurements are performed in solution, meaning surface interactions and system perturbations — and the artifacts they may result in — are minimized. To demonstrate the wide array of information AUC can glean, the researchers highlighted several examples. The first pointed to how AUC reveals the more complicated nature of hydration shells, or the water encapsulating various molecules. Rather than a homogenous layer of oxygen and hydrogen atoms, the water shifts in physical properties and behaviors through the shell, which also varies in thickness. The second example focused on determining the distance between components in molecular cluster solutions. According to the researchers, measuring intermolecular distances is key to understanding how charged macroions self-assemble in dilute solution and how changes in these distances correlate with transitions between different macroscopic phases. The third example detailed the interactions of molecular clusters with amino acids — the compounds that make up proteins. Understanding how amino acids interact with the surfaces of molecular clusters can help inform understanding of how the clusters will interact with biomolecules. Liu noted that these structures are governed by weak, noncovalent interactions between molecules. Although these forces are difficult to measure directly, AUC can reveal their effects by detecting subtle changes in molecular size, weight and shape in solution. “AUC is a powerful technique for investigating complex solution systems,” Liu said. “Owing to their well-defined and uniform size, shape and mass, molecular clusters are particularly well suited for AUC measurements. … AUC offers the distinct advantage of resolving different species prior to analysis, enabling direct determination of their individual concentrations.”  According to the researchers, there is a drawback, however. “The technique requires substantial expertise, experience and instrumentation resources,” Liu said. “As a result, the barrier to entry for new users can be relatively high, with a need for extensive training covering both experimental operation and data analysis.” Other contributors include Ruixin Li, Xiaohan Xu, Kexing Xiao and Bahareh Afsari, all with the University Akron; and Lake N. Paul, with BioAnalysis, LLC. The University of Akron supported this research. DOI Link: https://doi.org/10.26599/POM.2026.9140132  About Polyoxometalates Polyoxometalates (ISSN 2957-9821) is a peer-reviewed (single-blind), open-access and interdisciplinary journal, sponsored by Tsinghua University. Polyoxometalates publishes original high-quality research papers and significant review articles that focus on cutting-edge advancements in Polyoxometalates, and clusters of metals, metal oxides and chalcogenides. Rapid review to ensure quick publication is a key feature of Polyoxometalates. The journal is indexed by ESCI (IF 2025 = 10.4, Top 3), Scopus (CiteScore 2025 = 17.6, Top 3), Ei Compendex, CAS, and DOAJ. For details about Polyoxometalates, please visit: https://www.sciopen.com/journal/2957-9821.
Physical Sciences and Engineering

ZnAl-layered double hydroxides template-induced formation of ZnO/ZnSe heterostructures on the surface of coal-tar-pitch derived carbon for high-efficiency sodium storage

Sodium-ion batteries are considered a promising technology for large-scale energy storage because sodium is abundant and widely distributed. A major challenge, however, is finding anode materials that combine high capacity, fast reaction kinetics and long cycling stability while remaining practical and low cost. A research team from Taiyuan University of Technology and Taiyuan University of Science and Technology has reported a strategy that addresses this challenge by using coal tar pitch, an industrial carbon-rich byproduct, as the carbon source for a new composite anode. Their work was published in Energy Materials and Devices on June 11, 2026. The team used a zinc-aluminum layered double hydroxide (ZnAl-LDH) as a template to induce the formation of ZnO/ZnSe heterostructures embedded in hierarchical porous carbon. During synthesis, the LDH template serves two functions: it guides the local structure of the active material and helps generate pores in the carbon framework. This produces intimately connected ZnO/ZnSe-carbon interfaces rather than simply mixing active particles with carbon. The heterostructure is important because ZnO and ZnSe can work together at their interface. The interfacial contact promotes charge transfer, while the mixed oxygen and selenium anion environment, the nanoscale dispersion of ZnO/ZnSe and the conductive carbon network help improve reaction kinetics and reduce the mechanical strain that usually occurs during repeated sodium insertion and extraction.  “Our goal was to turn an inexpensive industrial byproduct into a functional carbon host and then use interface engineering to overcome the kinetic limitations of metal selenide anodes,” said Jian Wang, the corresponding authors of this paper, professor in the College of Materials Science and Engineering at Taiyuan University of Technology. “The LDH template allowed us to build the active heterostructure and the porous carbon architecture in one integrated design.” Electrochemical tests showed that the composite anode achieved a reversible capacity of 637.5 mAh g−1 at 100 mA g−1. Under high-rate cycling, it retained 259.7 mAh g−1 after 1000 cycles at 5 A g−1. Kinetic analysis further showed that capacitive storage dominated the response, contributing 93.3% of the total charge storage at 1.2 mV s−1. This behavior explains the material’s strong rate capability. The team also assembled a full cell using an Na3V2(PO4)3 cathode to evaluate practical potential. The full cell retained 147.5 mAh g−1 after 100 cycles, indicating that the material design is not limited to half-cell testing. “This study shows that template-directed heterostructure engineering can be an effective route for developing advanced sodium-ion battery anodes from low-cost carbon resources,” the Dr. Wang said. “The next step is to further optimize electrode formulation and evaluate the material under more practical cell conditions.” Other contributors include the Yiming Liu, the professor in the College of Environmental Science and Engineering at Taiyuan University of Technology and deputy dean of School of Chemical Engineering and Technology at Taiyuan University of Science and Technology; Yibo Zhao also from the College of Environmental Science and Engineering at Taiyuan University of Technology and in Taiyuan, China. Peihua Li, Haochen Xie, Yalong Wang and Wanggang Zhang from the College of Materials Science and Engineering at Taiyuan University of Technology; Rufeng Tian and Xiaohong Li from the College of Chemistry and Chemical Engineering at Taiyuan University of Technology. This work was supported by the National Natural Science Foundation of China (Grant Nos. U25B20110, 22075197 and 22278290), the Shanxi Provincial Central Guidance Fund for Local Science and Technology Development Projects (Grant No. YDZJSX2024D022), and the Key Research and Development (R&D) Projects of Shanxi Province (Grant No. 202102040201003). DOI Link: https://doi.org/10.26599/EMD.2026.9370093
Physical Sciences and Engineering
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