Unleashing the power of AI in science-key considerations for materials data preparation.

The release of ChatGPT has triggered global attention on artificial intelligence (AI), and AI for science is thus becoming a hot topic in the scientific community. When we think about unleashing the power of AI to accelerate scientific research, the question coming to our mind first is whether there is a continuous supply of highly available data at a sufficiently large scale.

Fundamental Understanding of Hydrogen Evolution Reaction on Zinc Anode Surface: A First-Principles Study.

Hydrogen evolution reaction (HER) has become a key factor affecting the cycling stability of aqueous Zn-ion batteries, while the corresponding fundamental issues involving HER are still unclear. Herein, the reaction mechanisms of HER on various crystalline surfaces have been investigated by first-principle calculations based on density functional theory. It is found that the Volmer step is the rate-limiting step of HER on the Zn (002) and (100) surfaces, while, the reaction rates of HER on the Zn (101), (102) and (103) surfaces are determined by the Tafel step.

FFMDFPA: A FAIRification Framework for Materials Data with No-Code Flexible Semi-Structured Parser and Application Programming Interfaces.

The FAIR Data Principles are guidelines to ensure Findability, Accessibility, Interoperability, and Reusability of digital resources, which are essential to accelerate data-driven materials science. Despite the development and growing adoption of the FAIR principles, appropriate implementation solutions and software to make data FAIR are still sparse, particularly in standardization of heterogeneous data and subsequent data access. Here, we introduce a FAIRification Framework for Materials Data with No-Code Flexible Semi-Structured Parser and API (FFMDFPA) (API, application programming interface) for raw data processing.

Spatial-temporal dynamics of land surface phenology over Africa for the period of 1982-2015.

Knowledge of the dynamics of vegetation phenology is essential for the understanding of vegetation-climate interactions. Although the interest in phenology study is growing, vegetation phenology in Africa received far less attention compared to the Northern Hemisphere. Africa straddles the northern and southern hemispheres, and the climate has a clear latitudinal gradient, which facilitates the study of the interaction between phenology and climate.

Liquid-Like Li-Ion Conduction in Oxides Enabling Anomalously Stable Charge Transport across the Li/Electrolyte Interface in All-Solid-State Batteries.

The softness of sulfur sublattice and rotational PS tetrahedra in thiophosphates result in liquid-like ionic conduction, leading to enhanced ionic conductivities and stable electrode/thiophosphate interfacial ionic transport. However, the existence of liquid-like ionic conduction in rigid oxides remains unclear, and modifications are deemed necessary to achieve stable Li/oxide solid electrolyte interfacial charge transport. In this study, by combining the neutron diffraction survey, geometrical analysis, bond valence site energy analysis, and ab initio molecular dynamics simulation, 1D liquid-like Li-ion conduction is discovered in LiTa PO and its derivatives, wherein Li-ion migration channels are connected by four- or five-fold oxygen-coordinated interstitial sites.

Data quantity governance for machine learning in materials science.

Data-driven machine learning (ML) is widely employed in the analysis of materials structure-activity relationships, performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate prediction. However, because of the laborious process of materials data acquisition, ML models encounter the issue of the mismatch between a high dimension of feature space and a small sample size (for traditional ML models) or the mismatch between model parameters and sample size (for deep-learning models), usually resulting in terrible performance. Here, we review the efforts for tackling this issue via feature reduction, sample augmentation and specific ML approaches, and show that the balance between the number of samples and features or model parameters should attract great attention during data quantity governance.

Auto-MatRegressor: liberating machine learning alchemists.

Machine learning (ML) is widely used to uncover structure-property relationships of materials due to its ability to quickly find potential data patterns and make accurate predictions. However, like alchemists, materials scientists are plagued by time-consuming and labor-intensive experiments to build high-accuracy ML models. Here, we propose an automatic modeling method based on meta-learning for materials property prediction named Auto-MatRegressor, which automates algorithm selection and hyperparameter optimization by learning from previous modeling experience, i.

Enabling the Operation of Highly Compatible LiI-3-Hydroxypropionitrile Small-Molecule Solid-State Electrolytes in Lithium Metal Batteries via Stepped-Amorphization Strategy.

Integrating the advantages of both inorganic ceramic and organic polymer solid-state electrolytes, small-molecule solid-state electrolytes represented by LiI-3-hydroxypropionitrile (LiI-HPN) inorganic-organic hybrid systems possess good interfacial compatibility and high modulus. However, their lack of intrinsic Li conduction ability hinders potential application in lithium metal batteries until now, despite containing LiI phase composition. Herein, inspired by evolution tendency of ionic conduction behaviors together with first-principles molecular dynamics simulations, we propose a stepped-amorphization strategy to break the Li conduction bottleneck of LiI-HPN.

A customized strategy to design intercalation-type Li-free cathodes for all-solid-state batteries.

Pairing Li-free transition-metal-based cathodes (MX) with Li-metal anodes is an emerging trend to overcome the energy-density limitation of current rechargeable Li-ion technology. However, the development of practical Li-free MX cathodes is plagued by the existing notion of low voltage due to the long-term overlooked voltage-tuning/phase-stability competition. Here, we propose a p-type alloying strategy involving three voltage/phase-evolution stages, of which each of the varying trends are quantitated by two improved ligand-field descriptors to balance the above contradiction.

The Origin of Solvent Deprotonation in LiI-added Aprotic Electrolytes for Li-O Batteries.

LiI and LiBr have been employed as soluble redox mediators (RMs) in electrolytes to address the sluggish oxygen evolution reaction kinetics during charging in aprotic Li-O batteries. Compared to LiBr, LiI exhibits a redox potential closer to the theoretical one of discharge products, indicating a higher energy efficiency. However, the reason for the occurrence of solvent deprotonation in LiI-added electrolytes remains unclear.

Broadband stealth devices based on encoded metamaterials.

Based on the generalized Snell's law, the relationship between the phase gradient of the metasurface and the incident frequency is demonstrated, and the principle of the achromatic metasurface is developed. By adjusting the phase gradient and linear dispersion simultaneously, the function of achromatic aberration is realized, and the influence of chromatic aberration on the metasurface is reduced. We propose a metasurface stealth device with achromatic multilayer frame metasurfaces with beam deflection, steering, and collection functions so that the incident electromagnetic beam is transmitted around the stealth object without scattering.

Breaking the Electronic Conductivity Bottleneck of Manganese Oxide Family for High-Power Fluorinated Graphite Composite Cathode by Ligand-Field High-Dimensional Constraining Strategy.

Primary lithium fluorinated graphite (Li/CF ) batteries with superior energy density are an indispensable energy supply for multiple fields but suffer from sluggish reaction kinetics of the CF cathode. Designing composite cathodes emerges as a solution to this problem. Despite the optimal composite component for CF , the manganese oxide family represented by MnO is still faced with an intrinsic electronic conductivity bottleneck, which severely limits the power density of the composite cathode.

Insights into LiMXOF (M-X = Al-P and Mg-S) as Cathode Coatings for High-Performance Lithium-Ion Batteries.

Cathode coatings have received extensive attention due to their ability to delay electrochemical performance degradation in lithium-ion batteries. However, the development of cathode coatings possessing high ionic conductivity and good interfacial stability with cathode materials has proven to be a challenge. Here, we performed first-principles computational studies on the phase stability, thermodynamic stability, and ionic transport properties of LiMXOF (M-X = Al-P and Mg-S) used as cathode coatings.

Software for Evaluating Long-Range Electrostatic Interactions Based on the Ewald Summation and Its Application to Electrochemical Energy Storage Materials.

Electrochemical characteristics such as open-circuit voltage and ionic conductivity of electrochemical energy storage materials are easily affected, typically negatively, by mobile ion/vacancy ordering. Ordered phases can be identified based on the lattice gas model and electrostatic energy screening. However, the evaluation of long-range electrostatic energy is not straightforward because of the conditional convergence.

MgSiO/Si-Coated Disproportionated SiO Composite Anodes with High Initial Coulombic Efficiency for Lithium Ion Batteries.

Silicon monoxide (SiO) is considered as one of the most promising anode material candidates for next-generation high-energy-density lithium ion batteries (LIBs) due to its high specific capacity and relatively lower volume expansion than that of Si. However, a large number of irreversible products are formed during the first charging and discharging process, resulting in a low initial Coulombic efficiency (ICE) of SiO. Herein, we report an economical and convenient method to increase the ICE of SiO without sacrificing its specific capacity by a solid reaction between magnesium silicide (MgSi) and micron-sized SiO.

Metallic VS/graphene heterostructure as an ultra-high rate and high-specific capacity anode material for Li/Na-ion batteries.

Graphene has been used as a conductive substrate to improve the electrochemical performance of layered VS as an anode material for lithium-ion batteries. However, there is still a lack of in-depth understanding of the synergistic effect between the layered VS and graphene, which contributes to the enhanced performance of Li/Na-ion batteries. In this work, using first-principles calculations, we have systematically studied the VS/graphene heterostructure as an anode material for Li/Na-ion batteries.

Machine learning prediction of activation energy in cubic Li-argyrodites with hierarchically encoding crystal structure-based (HECS) descriptors.

Rational design of solid-state electrolytes (SSEs) with high ionic conductivity and low activation energy (E) is vital for all solid-state batteries. Machine learning (ML) techniques have recently been successful in predicting Li conduction property in SSEs with various descriptors and accelerating the development of SSEs. In this work, we extend the previous efforts and introduce a framework of ML prediction for E in SSEs with hierarchically encoding crystal structure-based (HECS) descriptors.

Perfluorinated organics regulating LiO formation and improving stability for Li-oxygen batteries.

Lithium-oxygen batteries have a high theoretical capacity, but they are still far from meeting the capacity required for practical applications. In this study, we systematically investigate the synergistic effect of perfluorotributylamine (PFTBA) as an additive in a TEGDME-based electrolyte to optimize the electrochemical performance of Li-O batteries. PFTBA promotes cyclic LiO growth, and the discharge capacity is increased to 9548.

"Water in salt/ionic liquid" electrolyte for 2.8 V aqueous lithium-ion capacitor.

Development of high-voltage electrolytes with non-flammability is significantly important for future energy storage devices. Aqueous electrolytes are inherently non-flammable, easy to handle, and their electrochemical stability windows (ESWs) can be considerably expanded by increasing electrolyte concentrations. However, further breakthroughs of their ESWs encounter bottlenecks because of the limited salt solubility, leading to that most of the high-energy anode materials can hardly function reversibly in aqueous electrolytes.

High Quality Pyrazinoquinoxaline-Based Graphdiyne for Efficient Gradient Storage of Lithium Ions.

N-doping of graphdiyne with atomic precision is very important for the study of heteroatom doping effect and the structure-properties relationships of graphdiyne. Here we report the bottom-up synthesis and characterizations of high-quality pyrazinoquinoxaline-based graphdiyne (PQ-GDY) film. First-principle studies of the layered structure were performed to examine the stacking mode, lithium binding affinity, and bulk lithium storage capacity.

Efficient potential-tuning strategy through p-type doping for designing cathodes with ultrahigh energy density.

Designing new cathodes with high capacity and moderate potential is the key to breaking the energy density ceiling imposed by current intercalation chemistry on rechargeable batteries. The carbonaceous materials provide high capacities but their low potentials limit their application to anodes. Here, we show that Fermi level tuning by p-type doping can be an effective way of dramatically raising electrode potential.

Europium-Doped Ceria Nanowires as Anode for Solid Oxide Fuel Cells.

CeO-based materials have been studied intensively as anodes for intermediate temperature solid oxide fuel cells (IT-SOFCs). In this work, pristine and europium (Eu)-doped CeO nanowires were comprehensively investigated as anode materials for IT-SOFCs, by a combination of theoretical predictions and experimental characterizations. The results demonstrate: (1) Oxygen vacancies can be energetically favorably introduced into the CeO lattice by Eu doping; (2) The lattice parameter of the ceria increases linearly with the Eu content when it varies from 0 to 35 .

CAVD, towards better characterization of void space for ionic transport analysis.

Geometric crystal structure analysis using three-dimensional Voronoi tessellation provides intuitive insights into the ionic transport behavior of metal-ion electrode materials or solid electrolytes by mapping the void space in a framework onto a network. The existing tools typically consider only the local voids by mapping them with Voronoi polyhedra vertices and then define the mobile ions pathways using the Voronoi edges connecting these vertices. We show that in some structures mobile ions are located on Voronoi polyhedra faces and thus cannot be located by a standard approach.

High-throughput screening platform for solid electrolytes combining hierarchical ion-transport prediction algorithms.

The combination of a materials database with high-throughput ion-transport calculations is an effective approach to screen for promising solid electrolytes. However, automating the complicated preprocessing involved in currently widely used ion-transport characterization algorithms, such as the first-principles nudged elastic band (FP-NEB) method, remains challenging. Here, we report on high-throughput screening platform for solid electrolytes (SPSE) that integrates a materials database with hierarchical ion-transport calculations realized by implementing empirical algorithms to assist in FP-NEB completing automatic calculation.

Mobile Ions in Composite Solids.

Fast ion conduction in solid-state matrices constitutes the foundation for a wide spectrum of electrochemical systems that use solid electrolytes (SEs), examples of which include solid-state batteries (SSBs), solid oxide fuel cells (SOFCs), and diversified gas sensors. Mixing different solid conductors to form composite solid electrolytes (CSEs) introduces unique opportunities for SEs to possess exceptional overall performance far superior to their individual parental solids, thanks to the abundant chemistry and physics at the new interfaces thus created. In this review, we provide a comprehensive and in-depth examination of the development and understanding of CSEs for SSBs, with special focus on their physiochemical properties and mechanisms of ion transport therein.