Chemical short-range disorder in lithium oxide cathodes.

Ordered layered structures serve as essential components in lithium (Li)-ion cathodes1-3. However, on charging, the inherently delicate Li-deficient frameworks become vulnerable to lattice strain and structural and/or chemo-mechanical degradation, resulting in rapid capacity deterioration and thus short battery life2,4. Here we report an approach that addresses these issues using the integration of chemical short-range disorder (CSRD) into oxide cathodes, which involves the localized distribution of elements in a crystalline lattice over spatial dimensions, spanning a few nearest-neighbour spacings. This is guided by fundamental principles of structural chemistry and achieved through an improved ceramic synthesis process. To demonstrate its viability, we showcase how the introduction of CSRD substantially affects the crystal structure of layered Li cobalt oxide cathodes. This is manifested in the transition metal environment and its interactions with oxygen, effectively preventing detrimental sliding of crystal slabs and structural deterioration during Li removal. Meanwhile, it affects the electronic structure, leading to improved electronic conductivity. These attributes are highly beneficial for Li-ion storage capabilities, markedly improving cycle life and rate capability. Moreover, we find that CSRD can be introduced in additional layered oxide materials through improved chemical co-doping, further illustrating its potential to enhance structural and electrochemical stability. These findings open up new avenues for the design of oxide cathodes, offering insights into the effects of CSRD on the crystal and electronic structure of advanced functional materials.

Reconstruction of High Entropy Alloys on a Metal-Organic Framework Approaching Active Oxygen Reduction Electrocatalysts.

High-entropy alloys (HEAs) have garnered considerable attention as promising nanocatalysts for effectively utilizing Pt in catalysis toward oxygen reduction reactions due to their unique properties. Nonetheless, there is a relative dearth of attention regarding the structural evolution of HEAs in response to electrochemical conditions. In this work, we propose a thermal reduction method to synthesize high entropy nanoparticles by leveraging the confinement effect and abundant nitrogen-anchored sites provided by pyrolyzed metal-organic frameworks (MOFs). Notably, the prepared catalysts exhibit enhanced activity accompanied by structural reconstruction during electrochemical activation, approaching 1 order of magnitude higher mass activity compared to Pt/C in oxygen reduction. Atomic-scale structural characterization reveals that abundant defects and single atoms are formed during the activation process, contributing to a significant boost in the catalytic performance for oxygen reduction reactions. This study provides deep insights into surface reconstruction engineering during electrochemical operations, with practical implications for fuel cell applications.

Resolving the Origins of Superior Cycling Performance of Antimony Anode in Sodium-ion Batteries: A Comparison with Lithium-ion Batteries.

Alloying-type antimony (Sb) with high theoretical capacity is a promising anode candidate for both lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs). Given the larger radius of Na+ (1.02 Å) than Li+ (0.76 Å), it was generally believed that the Sb anode would experience even worse capacity degradation in SIBs due to more substantial volumetric variations during cycling when compared to LIBs. However, the Sb anode in SIBs unexpectedly exhibited both better electrochemical and structural stability than in LIBs, and the mechanistic reasons that underlie this performance discrepancy remain undiscovered. Here, using substantial in situ transmission electron microscopy, X-ray diffraction, and Raman techniques complemented by theoretical simulations, we explicitly reveal that compared to the lithiation/delithiation process, sodiation/desodiation process of Sb anode displays a previously unexplored two-stage alloying/dealloying mechanism with polycrystalline and amorphous phases as the intermediates featuring improved resilience to mechanical damage, contributing to superior cycling stability in SIBs. Additionally, the better mechanical properties and weaker atomic interaction of Na-Sb alloys than Li-Sb alloys favor enabling mitigated mechanical stress, accounting for enhanced structural stability as unveiled by theoretical simulations. Our finding delineates the mechanistic origins of enhanced cycling stability of Sb anode in SIBs with potential implications for other large-volume-change electrode materials.

Nanoscale Design for High Entropy Alloy Electrocatalysts.

Due to their distinctive physical and chemical characteristics, high entropy alloys (HEAs), a class of alloys comprising multiple elements, have garnered a lot of attention. It is demonstrated recently that HEA electrocatalysts increase the activity and stability of several processes. In this paper, the most recent developments in HEA electrocatalysts research are reviewed, and the performance of HEAs in catalyzing key reactions in water electrolysis and fuel cells is summarized. In addition, the design strategies for HEA electrocatalysts optimization is introduced, which include component selection, size optimization, morphology control, structural engineering, crystal phase regulation, and theoretical prediction, which can guide component selection and structural design of HEA electrocatalysts.

Phenoxazine Polymer-based p-type Positive Electrode for Aluminum-ion Batteries with Ultra-long Cycle Life.

Aluminum-ion batteries (AIBs) are a promising candidate for large-scale energy storage due to the abundant reserves, low cost, good safety, and high theoretical capacity of Al. However, AIBs with inorganic positive electrodes still suffer from sluggish kinetics and structural collapse upon cycling. Herein, we propose a novel p-type poly(vinylbenzyl-N-phenoxazine) (PVBPX) positive electrode for AIBs. The dual active sites enable PVBPX to deliver a high capacity of 133 mAh g-1 at 0.2 A g-1 . More impressively, the expanded π-conjugated construction, insolubility, and anionic redox chemistry without bond rearrangement of PVBPX for AIBs contribute to an amazing ultra-long lifetime of 50000 cycles. The charge storage mechanism is that the AlCl4 - ions can reversibly coordinate/dissociate with the N and O sites in PVBPX sequentially, which is evidenced by both experimental and theoretical results. These findings establish a foundation to advance organic AIBs for large-scale energy storage.

Data-Driven Strategies for Accelerated Materials Design.

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency.In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

Fluorinated Rocksalt Cathode with Ultra-high Active Li Content for Lithium-ion Batteries.

The key to increasing the energy density of lithium-ion batteries is to incorporate high contents of extractable Li into the cathode. Unfortunately, this triggers formidable challenges including structural instability and irreversible chemistry under operation. Here, we report a new kind of ultra-high Li compound: Li4+x MoO5 Fx (1≤x≤3) for cathode with an unprecedented level of electrochemically active Li (>3 Li+ per formula), delivering a reversible capacity up to 438 mAh g-1 . Unlike other reported Li-rich cathodes, Li4+x MoO5 Fx presents distinguished structure stability to immunize against irreversible behaviors. Through spectroscopic and electrochemical techniques, we find an anionic redox-dominated charge compensation with negligible oxygen release and voltage decay. Our theoretical analysis reveals a "reductive effect" of high-level fluorination stabilizes the anionic redox by reducing the oxygen ions in pure-Li conditions, enabling a facile, reversible, and high Li-portion cycling.

In Situ, Atomic-Resolution Observation of Lithiation and Sodiation of WS2 Nanoflakes: Implications for Lithium-Ion and Sodium-Ion Batteries.

WS2 nanoflakes have great potential as electrode materials of lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs) because of their unique 2D structure, which facilitates the reversible intercalation and extraction of alkali metal ions. However, a fundamental understanding of the electrochemical lithiation/sodiation dynamics of WS2 nanoflakes especially at the nanoscale level, remains elusive. Here, by combining battery electrochemical measurements, density functional theory calculations, and in situ transmission electron microscopy, the electrochemical-reaction kinetics and mechanism for both lithiation and sodiation of WS2 nanoflakes are investigated at the atomic scale. It is found that compared to LIBs, SIBs exhibit a higher reversible sodium (Na) storage capacity and superior cyclability. For sodiation, the volume change due to ion intercalation is smaller than that in lithiation. Also, sodiated WS2 maintains its layered structure after the intercalation process, and the reduced metal nanoparticles after conversion in sodiation are well-dispersed and aligned forming a pattern similar to the layered structure. Overall, this work shows a direct interconnection between the reaction dynamics of lithiated/sodiated WS2 nanoflakes and their electrochemical performance, which sheds light on the rational optimization and development of advanced WS2 -based electrodes.

Revealing High Na-Content P2-Type Layered Oxides as Advanced Sodium-Ion Cathodes.

Layered Na-based oxides with the general composition of NaxTMO2 (TM: transition metal) have attracted significant attention for their high compositional diversity that provides tunable electrochemical performance for electrodes in sodium-ion batteries. The various compositions bring forward complex structural chemistry that is decisive for the layered stacking structure, Na-ion conductivity, and the redox activity, potentially promising new avenues in functional material properties. In this work, we have explored the maximum Na content in P2-type layered oxides and discovered that the high-content Na in the host enhances the structural stability; moreover, it promotes the oxidation of low-valent cations to their high oxidation states (in this case Ni2+). This can be rationalized by the increased hybridization of the O(2p)-TM(3d-eg*) states, affecting both the local TM environment as well as the interactions between the NaO2 and TMO2 layers. These properties are highly beneficial for the Na storage capabilities as required for cathode materials in sodium-ion batteries. It leads to excellent Na-ion mobility, a large storage capacity (>100 mAh g-1 between 2.0-4.0 V), yet preventing the detrimental sliding of the TMO2 layers (P2-O2 structural transition), as reflected by the ultralong cycle life (3000 (dis)charge cycles demonstrated). These findings expand the horizons of high Na-content P2-type materials, providing new insights of the electronic and structural chemistry for advanced cathode materials.

Direct Observation of Defect-Aided Structural Evolution in a Nickel-Rich Layered Cathode.

Ni-rich LiNi1-x-y Mnx Coy O2 (NMC) layered compounds are the dominant cathode for lithium ion batteries. The role of crystallographic defects on structure evolution and performance degradation during electrochemical cycling is not yet fully understood. Here, we investigated the structural evolution of a Ni-rich NMC cathode in a solid-state cell by in situ transmission electron microscopy. Antiphase boundary (APB) and twin boundary (TB) separating layered phases played an important role on phase change. Upon Li depletion, the APB extended across the layered structure, while Li/transition metal (TM) ion mixing in the layered phases was detected to induce the rock-salt phase formation along the coherent TB. According to DFT calculations, Li/TM mixing and phase transition were aided by the low diffusion barriers of TM ions at planar defects. This work reveals the dynamical scenario of secondary phase evolution, helping unveil the origin of performance fading in Ni-rich NMC.

Quaternary Pavonites A1+xSn2-xBi5+xS10 (A+ = Li+, Na+): Site Occupancy Disorder Defines Electronic Structure.

The field of mineralogy represents an area of untapped potential for the synthetic chemist, as there are numerous structure types that can be utilized to form analogues of mineral structures with useful optoelectronic properties. In this work, we describe the synthesis and characterization of two novel quaternary sulfides A1+xSn2-xBi5+xS10 (A = Li+, Na+). Though not natural minerals themselves, both compounds adopt the pavonite structure, which crystallizes in the C2/m space group and consists of two connected, alternating defect rock-salt slabs of varying thicknesses to create a three-dimensional lattice. Despite their commonalities in structure, their crystallography is noticeably different, as both structures have a heavy degree of site occupancy disorder that affects the actual positions of the atoms. The differences in site occupancy alter their electronic structures, with band gap values of 0.31(2) eV and 0.07(2) eV for the lithium and sodium analogues, respectively. LiSn2Bi5S10 exhibits ultralow thermal conductivity of 0.62 W m-1 K-1 at 723 K, and this result is corroborated by phonon dispersion calculations. This structure type is a promising host candidate for future thermoelectric materials investigation, as these materials have narrow band gaps and intrinsically low thermal conductivities.

Kinetically-Driven Phase Transformation during Lithiation in Copper Sulfide Nanoflakes.

Two-dimensional (2D) transition metal chalcogenides have been widely studied and utilized as electrode materials for lithium ion batteries due to their unique layered structures to accommodate reversible lithium insertion. Real-time observation and mechanistic understanding of the phase transformations during lithiation of these materials are critically important for improving battery performance by controlling structures and reaction pathways. Here, we use in situ transmission electron microscopy methods to study the structural, morphological, and chemical evolutions in individual copper sulfide (CuS) nanoflakes during lithiation. We report a highly kinetically driven phase transformation in which lithium ions rapidly intercalate into the 2D van der Waals-stacked interlayers in the initial stage, and further lithiation induces the Cu extrusion via a displacement reaction mechanism that is different from the typical conversion reactions. Density functional theory calculations have confirmed both the thermodynamically favored and the kinetically driven reaction pathways. Our findings elucidate the reaction pathways of the Li/CuS system under nonequilibrium conditions and provide valuable insight into the atomistic lithiation mechanisms of transition metal sulfides in general.

Designing lithium halide solid electrolytes.

All-solid-state lithium batteries have attracted widespread attention for next-generation energy storage, potentially providing enhanced safety and cycling stability. The performance of such batteries relies on solid electrolyte materials; hence many structures/phases are being investigated with increasing compositional complexity. Among the various solid electrolytes, lithium halides show promising ionic conductivity and cathode compatibility, however, there are no effective guidelines when moving toward complex compositions that go beyond ab-initio modeling. Here, we show that ionic potential, the ratio of charge number and ion radius, can effectively capture the key interactions within halide materials, making it possible to guide the design of the representative crystal structures. This is demonstrated by the preparation of a family of complex layered halides that combine an enhanced conductivity with a favorable isometric morphology, induced by the high configurational entropy. This work provides insights into the characteristics of complex halide phases and presents a methodology for designing solid materials.

Regulating Surface Oxygen Activity by Perovskite-Coating-Stabilized Ultrahigh-Nickel Layered Oxide Cathodes.

Ultrahigh-Ni layered oxides are proposed as promising cathodes to fulfill the range demand of electric vehicles; yet, they are still haunted by compromised cyclability and thermal robustness. State-of-the-art surface coating has been applied to solve the instability via blocking the physical contact between the electrolyte and the highly active Ni4+ ions on the cathode surface, but it falls short in handling the chemo-physical mobility of the oxidized lattice oxygen ions in the cathode. Herein, a direct regulation strategy is proposed to accommodate the highly active anionic redox within the solid phase. By leveraging the stable oxygen vacancies/interstitials in a lithium and oxygen dual-ion conductor (layered perovskite La4 NiLiO8 ) coating layer, the reactivity of the surface lattice oxygen ion is dramatically restrained. As a result, the oxygen release from the lattice is suppressed, as well as the undesired irreversible phase transition and intergranular mechanical cracking. Meanwhile, the introduced dual-ion conductor can also facilitate lithium-ion diffusion kinetics and electronic conductivity on the particle surface. This work demonstrates that accommodating the anionic redox chemistry by dual-ion conductors is an effective strategy for capacity versus stability juggling of the high-energy cathodes.

High entropy liquid electrolytes for lithium batteries.

High-entropy alloys/compounds have large configurational entropy by introducing multiple components, showing improved functional properties that exceed those of conventional materials. However, how increasing entropy impacts the thermodynamic/kinetic properties in liquids that are ambiguous. Here we show this strategy in liquid electrolytes for rechargeable lithium batteries, demonstrating the substantial impact of raising the entropy of electrolytes by introducing multiple salts. Unlike all liquid electrolytes so far reported, the participation of several anionic groups in this electrolyte induces a larger diversity in solvation structures, unexpectedly decreasing solvation strengths between lithium ions and solvents/anions, facilitating lithium-ion diffusivity and the formation of stable interphase passivation layers. In comparison to the single-salt electrolytes, a low-concentration dimethyl ether electrolyte with four salts shows an enhanced cycling stability and rate capability. These findings, rationalized by the fundamental relationship between entropy-dominated solvation structures and ion transport, bring forward high-entropy electrolytes as a composition-rich and unexplored space for lithium batteries and beyond.

Machine learning for a sustainable energy future.

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances - at the materials, devices and systems levels - for the efficient harvesting, storage, conversion and management of renewable energy. Energy researchers have begun to incorporate machine learning (ML) techniques to accelerate these advances. In this Perspective, we highlight recent advances in ML-driven energy research, outline current and future challenges, and describe what is required to make the best use of ML techniques. We introduce a set of key performance indicators with which to compare the benefits of different ML-accelerated workflows for energy research. We discuss and evaluate the latest advances in applying ML to the development of energy harvesting (photovoltaics), storage (batteries), conversion (electrocatalysis) and management (smart grids). Finally, we offer an overview of potential research areas in the energy field that stand to benefit further from the application of ML.

Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction.

Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water. Nevertheless, the conventional "trial and error" method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive. Fortunately, the advancement of machine learning brings new opportunities for electrocatalysts discovery and design. By analyzing experimental and theoretical data, machine learning can effectively predict their hydrogen evolution reaction (HER) performance. This review summarizes recent developments in machine learning for low-dimensional electrocatalysts, including zero-dimension nanoparticles and nanoclusters, one-dimensional nanotubes and nanowires, two-dimensional nanosheets, as well as other electrocatalysts. In particular, the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted. Finally, the future directions and perspectives for machine learning in electrocatalysis are discussed, emphasizing the potential for machine learning to accelerate electrocatalyst discovery, optimize their performance, and provide new insights into electrocatalytic mechanisms. Overall, this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.

Entropy-Driven Liquid Electrolytes for Lithium Batteries.

Developing liquid electrolytes with higher kinetics and enhanced interphase stability is one of the key challenges for lithium batteries. However, the poor solubility of lithium salts in solvents sets constraints that compromises the electrolyte properties. Here, it is shown that introducing multiple salts to form a high-entropy solution, alters the solvation structure, which can be used to raise the solubility of specific salts and stabilize electrode-electrolyte interphases. The prepared high-entropy electrolytes significantly enhance the cycling and rate performance of lithium batteries. For lithium-metal anodes the reversibility exceeds 99%, which extends the cycle life of batteries even under aggressive cycling conditions. For commercial batteries, combining a graphite anode with a LiNi0.8 Co0.1 Mn0.1 O2 cathode, more than 1000 charge-discharge cycles are achieved while maintaining a capacity retention of more than 90%. These performance improvements with respect to regular electrolytes are rationalized by the unique features of the solvation structure in high-entropy electrolytes. The weaker solvation interaction induced by the higher disorder results in improved lithium-ion kinetics, and the altered solvation composition leads to stabilized interphases. Finally, the high-entropy, induced by the presence of multiple salts, enables a decrease in melting temperature of the electrolytes and thus enables lower battery operation temperatures without changing the solvents.

Niobium-doped layered cathode material for high-power and low-temperature sodium-ion batteries.

The application of sodium-based batteries in grid-scale energy storage requires electrode materials that facilitate fast and stable charge storage at various temperatures. However, this goal is not entirely achievable in the case of P2-type layered transition-metal oxides because of the sluggish kinetics and unfavorable electrode|electrolyte interphase formation. To circumvent these issues, we propose a P2-type Na0.78Ni0.31Mn0.67Nb0.02O2 (P2-NaMNNb) cathode active material where the niobium doping enables reduction in the electronic band gap and ionic diffusion energy barrier while favoring the Na-ion mobility. Via physicochemical characterizations and theoretical calculations, we demonstrate that the niobium induces atomic scale surface reorganization, hindering metal dissolution from the cathode into the electrolyte. We also report the testing of the cathode material in coin cell configuration using Na metal or hard carbon as anode active materials and ether-based electrolyte solutions. Interestingly, the Na||P2-NaMNNb cell can be cycled up to 9.2 A g-1 (50 C), showing a discharge capacity of approximately 65 mAh g-1 at 25 °C. Furthermore, the Na||P2-NaMNNb cell can also be charged/discharged for 1800 cycles at 368 mA g-1 and -40 °C, demonstrating a capacity retention of approximately 76% and a final discharge capacity of approximately 70 mAh g-1.

Theory-guided experimental design in battery materials research.

A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided.