Sodium-metal batteries could be competitive against Li-metal batteries, but their applications depend on the stability of electrolytes against sodium-metal anodes and cathodes simultaneously. Here, we propose hybrid solvating electrolytes (HSEs), composed of both strongly and weakly solvating solvents of sodium salts, to tune the solubility, solvation structure, and electrochemical decomposition properties. Fifty HSEs are prepared using the pre-screened candidate molecules, validating the mixture selection requirements and correlations between salt/solvent types and their mixture-dependent performance, including oxidative stability, Coulombic efficiency, and cycling overpotential. A model hybrid solvent formed by mixing weakly solvating N,N-dimethyltrifluoromethane sulfonamide (DMTMSA) with strongly solvating tetrahydrofuran (THF) demonstrates strong beyond-rule-of-mixture effects, showing extraordinarily stable cycling performance against Na3V2(PO4)3 and Na0.44MnO2 cathodes and Na-metal anode. Spectroscopic analysis and molecular dynamics simulations reflect the corresponding change in ion-dipole interaction and solvation structures. The strong-weak hybrid solvating principle for electrolyte design enables practical alkali-metal batteries.

The development of readily accessible and interpretable descriptors is pivotal yet challenging in the rational design of metal–organic framework (MOF) catalysts. This study presents a straightforward and physically interpretable activity descriptor for the oxygen evolution reaction (OER), derived from a dataset of bimetallic Ni-based MOFs. Through an artificial-intelligence (AI) data-mining subgroup discovery (SGD) approach, a combination of the d -band center and number of missing electrons in e g states of Ni, as well as the first ionization energy and number of electrons in e g states of the substituents, is revealed as a gene of a superior OER catalyst. The found descriptor, obtained from the AI analysis of a dataset of MOFs containing 3–5d transition metals and 13 organic linkers, has been demonstrated to facilitate in-depth understanding of structure–activity relationship at the molecular orbital level. The descriptor is validated experimentally for 11 Ni-based MOFs. Combining SGD with physical insights and experimental verification, our work offers a highly efficient approach for screening MOF-based OER catalysts, simultaneously providing comprehensive understanding of the catalytic mechanism.

Amorphous metal‐organic frameworks (MOFs) with aperiodic atomic arrangements, featuring high intrinsic activity and rich active sites, have emerged as promising oxygen evolution reaction (OER) catalysts. However, the quantitative structure‐activity relationships (SARs) that determine the OER activity, the key to a rational catalyst design, remain unresolved. Inspired by controllable amorphization engineering, the amorphous MOF structures are rationally constructed as an ideal platform to explore the SAR in catalyzing OER. The mechanistic studies show that the OER activity could be volcano‐shape correlated with either constant adsorption energy difference between OOH* and O* (Δ G OOH* − Δ G O* ) or the position of the d band center. The amorphous MOF (Ni 8 Co 2 ‐BDC), situated close to the volcano summit, possesses an appropriate E d energy level, which exhibits the balanced intermediates adsorption/desorption ability and consequently results in the boosted catalytic activity and long‐term stability. This work supplies new perspectives to investigate the SAR in amorphous MOF structures, thereby guiding the rational design of advanced OER catalysts.

Local symmetry breaking of catalysts has emerged as an effective strategy for finely tuning oxygen evolution reaction (OER) activity, yet the fundamental comprehension regarding asymmetric structure-activity relationships remains limited. Here, we propose the energy band engineering to bridge the correlation between established asymmetric electronic structure and adsorption/desorption ability of reaction intermediates within metal-organic frameworks (MOFs). The deliberate synthesis of CoM-MOFs (M=Cu, Ni, and Fe) with distinct coordination microenvironments enables the customization of asymmetric Co-O-M electronic structure. A volcano-shaped relationship can be revealed between calculated OER overpotential and average d-band center (Ed) energy level for both active Co sites and substituted M. The CoFe-MOF, located close to the summit, showcases the balanced reaction intermediate behavior and thus for enhanced OER activity. This work presents a promising approach to thoroughly understand asymmetric electronic structure-activity relationships from the perspective of energy band engineering and further guide the discovery of high-efficiency MOF-based OER catalysts.

Although numerous efforts are made to synthesize active electrocatalysts for green hydrogen production; catalyst stability, and facile synthesis to scale up the production are still challenging. Herein, the production of novel non-PGM catalysts for the oxygen reduction reaction (OER) in an alkaline aqueous medium is reported, which is based on the synthesis of a trimetallic metal-organic framework (MOF) precursors. Fine-tuning of the composition of the metal centers (Ni, Co, and Fe) shows a great effect on OER activity after the MOF undergoes dynamic chemical and structural transformations under OER conditions. In situ characterization reveals the origin of OER activity enhancement as metals' oxidation state increases, inducing compressive mechanical strain on metal centers, enhancing the electronic conductivity through the formation of oxygen vacancies, and stronger metal-oxygen covalency. Catalysts are used in membrane electrode assembly (MEA) setup within an industrial full-cell anion exchange membrane electrolyzer (AEMEC), showing a stable performance for 550 h without noticeable decay at 750 and 1000 mA cm(-2) industrial level current densities.

We investigate whether large language models can perform the creative hypothesis generation that human researchers regularly do. While the error rate is high, generative AI seems to be able to effectively structure vast amounts of scientific knowledge and provide interesting and testable hypotheses. The future scientific enterprise may include synergistic efforts with a swarm of "hypothesis machines", challenged by automated experimentation and adversarial peer reviews.

The exploration and discovery of materials for electrochemical reactions have traditionally been a tedious and time-intensive process. The complexity inherent in the design of materials with high-dimensional parameters and the exhaustive nature of data acquisition are the primary causes of this bottleneck [1]. To overcome this challenge, we introduce the Copilot for Real-world Experimental Scientist (CRESt). CRESt employs a large multimodal model (LMM) to guide a robotic system that is adept at active learning (driven by the Gaussian process-Bayesian optimization process), thereby streamlining the entire workflow—ranging from the selection of composition through to the high-throughput synthesis of materials, electrochemical screening, materials characterization, and device testing—for the optimization of electrocatalysts (see video demonstrations in [2-4]). Through this method, we have been able to rapidly screen thousands of catalysts with minimal human intervention. Our development of high entropy alloy catalysts, which comprise more than five elements, have demonstrated exceptional performance in applications such as direct formate fuel cells and alkaline water electrolyzers. This strategy holds the promise of broad implementation across a spectrum of electrochemical systems. Reference: [1] Ren, Z., Ren, Z., Zhang, Z. et al. Autonomous experiments using active learning and AI. Nat. Rev. Mater. 8, 563–564 (2023). [2] https://www.youtube.com/watch?v=iRauT95ECmo&t=82s [3] https://www.youtube.com/watch?v=POPPVtGueb0&t=340s [4] https://www.youtube.com/watch?v=sibCICesrEY

This review provides a comprehensive overview of liquid fuel oxidation electrocatalysts, from fundamental principles to state-of-the-art materials in an effort to unify design principles for future materials.

Active learning and automation will not easily liberate humans from laboratory workflows. Before they can really impact materials research, artificial intelligence systems will need to be carefully set up to ensure their robust operation and their ability to deal with both epistemic and stochastic errors. As autonomous experiments become more widely available, it is essential to think about how to embed reproducibility, reconfigurability and interoperability in the design of autonomous labs.

Autonomous laboratories were previously controlled mainly by scripting languages such as Python, limiting their usage among experimentalists. The recent release of OpenAI's ChatGPT API's function calling feature has enabled seamless integration and execution of Python subroutines in experimental workflows using voice commands. We have developed a system of Copilot for Real-world Experimental Scientist (CRESt) system, with a demonstration shown on YouTube. Large language models (LLMs) empower all research group members, regardless of coding experience, to leverage the robotic platform for their own projects, simply by talking with CRESt.

CO2 electroreduction (CO2ER) is a promising route to carbon-neutral production of various chemicals and fuels. Carbon efficiency is one of the most pressing problems for CO2ER today. While there have been studies on anion exchange membrane (AEM) electrolyzers with CO2(gas) and bipolar membrane (BPM) electrolyzers with HCO3–(aq) feedstock, both suffer from significant carbon efficiency loss. In AEM electrolyzers, this is due to carbonate anion crossover, whereas in BPM electrolyzers, the exsolution of CO2(gas) from the bicarbonate solution is the culprit. Here, we first elucidate the root cause of the low carbon efficiency of liquid bicarbonate electrolyzers with thermodynamic calculations, then achieve carbon-efficient CO2ER by adopting a near-neutral-pH cation exchange membrane (CEM) and CO2(gas) partial pressure management, with tin nanoparticle catalysts. We have converted highly concentrated bicarbonate solution to solid formate fuel with a yield (carbon efficiency) of > 96%. The device test was demonstrated at 100 mA cm–2 with a full-cell voltage of 3.1 V for over 100 h. This strategy enables full conversion of HCO3–(aq) feedstock to energy-dense solid formate fuel at ambient pressure and temperature with renewable electricity. Importantly, it can power direct formate fuel cells (DFFCs) which exhibit promising power density for seasonal energy storage.

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

Ceramic fuel/electrolysis cells are key energy/material conversion devices. Here, we report that, by thermal shock, mixed ionic and electronic conducting electrode powders with a perovskite structure can be successfully synthesized within 2 min, while this procedure requires a two-step calcination and almost 40 h when a conventional furnace is used. This benefits from the high temperature supplied to the system, greatly enhancing the reaction kinetics among the raw materials. Moreover, typical electrolyte powders with a fluorite structure, such as (Y2O3)(0.08)(ZrO2)(0.92) (YSZ) and Sm0.2Ce0.8O1.95 (SDC), are also synthesized in several minutes through a thermal shock, which significantly reduces the fabrication time of a solid oxide cell. Also, one can easily prepare multiple samples at one time via tailoring the carbon support size. The availability of fast synthesis of the thermal-shock technique enables the development of new functional ceramic powders for solid-oxide cells in a high-throughput and economical manner.

Mercury, lead, and cadmium are among the most toxic and carcinogenic heavy metal ions (HMIs), posing serious threats to the sustainability of aquatic ecosystems and public health. There is an urgent need to remove these ions from water by a cheap but green process. Traditional methods have insufficient removal efficiency and reusability. Structurally robust, large surface‐area adsorbents functionalized with high‐selectivity affinity to HMIs are attractive filter materials. Here, an adsorbent prepared by vulcanization of polyacrylonitrile (PAN), a nitrogen‐rich polymer, is reported, giving rise to PAN‐S nanoparticles with cyclic π‐conjugated backbone and electronic conductivity. PAN‐S can be coated on ultra‐robust melamine (ML) foam by simple dipping and drying. In agreement with hard/soft acid/base theory, N‐ and S‐containing soft Lewis bases have strong binding to Hg2+, Pb2+, Cu2+, and Cd2+, with extraordinary capture efficiency and performance stability. Furthermore, the used filters, when collected and electrochemically biased in a recycling bath, can release the HMIs into the bath and electrodeposit on the counter‐electrode as metallic Hg0, Pb0, Cu0, and Cd0, and the PAN‐S@ML filter can then be reused at least 6 times as new. The electronically conductive PAN‐S@ML filter can be fabricated cheaply and holds promise for scale‐up applications.

In an electrochemical cell, unequal mechanical work due to mass action into the two electrodes can generate chemical potential difference that drives Li+ flow across the electrolyte, constituting the fundamental basis for electrochemically driven mechanical energy harvesting. The diffusional time scale inherent to the electrochemical setting renders efficient low-frequency energy conversion. From thermodynamic analyses we reveal that there exist two distinct paradigms for electrochemically driven mechanical energy harvesting, enabled by pressure or molar-volume asymmetry of the electrodes. Guided by the thermodynamic framework, we prototype the first molar-volume asymmetry based energy harvester consisting of an intercalation-conversion electrode couple. The harvester can operate under globally uniform pressure and deliver a high power density of similar to 0.90 mu W cm(-2) with long-term durability. Under an open-circuit condition, the device operates in a novel ratchetting mode under which compression/decompression cycling causes continuous rise in voltage, yielding a blasting power output of similar to 143.60 mu W cm(-2). Such a ratchet effect arises due to the chemomechanically induced residual stress in the electrodes during cycling. Compared to the pressure-asymmetry based harvesters, the new harvester offers high scalability, processability, safety, and large working area, which make it easy to increase the output power through synchronizing multilayer with large areas. Our device enables mechanical energy harvesting from low-frequency resources, including human daily activities.

Free-standing macroporous air electrodes with enhanced interfacial contact, rapid mass transport, and tailored deposition space for large amounts of Li2 O2 are essential for improving the rate performance of Li-O2 batteries. An ordered mesoporous carbon membrane with continuous macroporous channels was prepared by inversely topological transformation from ZnO nanorod array. Utilized as a free-standing air cathode for Li-O2 battery, the hierarchically porous carbon membrane shows superior rate performance. However, the increased cross-sectional area of the continuous macropores on the cathode surface leads to a kinetic overpotential with large voltage hysteresis and linear voltage variation against Butler-Volmer behavior. The kinetics were investigated based on the rate-determining step of second electron transfer accompanied by migration of Li+ in solid or quasi-solid intermediates. These discoveries shed light on the design of the air cathode for Li-O2 batteries with high-rate performance.

The operation of Li-air batteries is currently limited to O-2 instead of air, mainly attributed to the formation of wide-bandgap insulator Li2CO3 during discharge caused by the presence of CO2 in air. A thorough understanding of the decomposition mechanism of Li2CO3 is crucial but challenging owing to the existence of side reactions induced by the large charge overpotential. Here, monodisperse RuO2 supported on layered double oxide is utilized as cathodes for Li-CO2 batteries with ultralow charge overpotential (only similar to 0.4 V larger than equilibrium potential, 2.80 V). The reversibility of Li-CO2 battery is mainly attributed to the decomposition of Li2CO3 upon charging instead of the degradation of the electrolyte. These results advance the fundamental understanding of the carbonate decomposition in Li-CO2 batteries and offer a promising route to utilizing agglomeration of layered-confined monodisperse catalyst to enlarge the layered spacings of layered support with complementary catalytic activity for Li-CO2 batteries with high energy efficiency and superior cycle life.