Theory-guided experimental design in battery materials research

Toward waterproof magnesium metal anodes by uncovering water-induced passivation and drawing water-tolerant interphases

Magnesium (Mg) metal is a promising anode candidate for high-energy and cost-effective multivalent metal batteries, but suffers from severe surface passivation in conventional electrolytes, especially aqueous solutions. Here, we uncover that MgH2, in addition to the well-known MgO and Mg(OH)2, can be formed during the passivation of Mg by water. The formation mechanism and spatial distribution of MgH2, and its detrimental effect on interfacial dynamics and stability of Mg anode are revealed by comprehensive experimental and theoretical investigations. Furthermore, a graphite-based hydrophobic and Mg2+-permeable water-tolerant interphase is drawn using a pencil on the surface of Mg anodes, allowing them to cycle stably in symmetric (> 900 h) and full cells (> 500 cycles) even after contact with water. The mechanistic understanding of MgH2-involved Mg passivation and the design of pencil-drawn waterproof Mg anodes may inspire the further development of Mg metal batteries with high water resistance.

Multifunctional Self-Assembled Bio-Interfacial Layers for High-Performance Zinc Metal Anodes

Rechargeable aqueous zinc-ion (Zn-ion) batteries are widely regarded as important candidates for next-generation energy storage systems for low-cost renewable energy storage. However, the development of Zn-ion batteries is currently facing significant challenges due to uncontrollable Zn dendrite growth and severe parasitic reactions on Zn metal anodes. Herein, we report an effective strategy to improve the performance of aqueous Zn-ion batteries by leveraging the self-assembly of bovine serum albumin (BSA) into a bilayer configuration on Zn metal anodes. BSA's hydrophilic and hydrophobic fragments form unique and intelligent ion channels, which regulate the migration of Zn ions and facilitate their desolvation process, significantly diminishing parasitic reactions on Zn anodes and leading to a uniform Zn deposition along the Zn (002) plane. Notably, the Zn||Zn symmetric cell with BSA as the electrolyte additive demonstrated a stable cycling performance for up to 2400 hours at a high current density of 10 mA cm-2. This work demonstrates the pivotal role of self-assembled protein bilayer structures in improving the durability of Zn anodes in aqueous Zn-ion batteries.

Design and Synthesis of Electrocatalysts Base on Catalysis-Unit Engineering

It is a pressing need to develop new energy materials to address the existing energy crisis. However, screening optimal targets out of thousands of material candidates remains a great challenge. Herein, an alternative concept for highly effective materials screening based on dual-atom salphen catalysis units, is proposed and validated. Such an approach simplifies the design of catalytic materials and reforms the trial-and-error experimental model into a building-blocks-assembly like process. First, density functional theory (DFT) calculations are performed on a series of potential catalysis units that are possible to synthesize. Then, machine learning (ML) is employed to define the structure-performance relationship and acquire chemical insights. Afterward, the projected catalysis units are integrated into covalent organic frameworks (COFs) to validate the concept Electrochemical tests confirming that Ni-SalphenCOF and Co-SalphenCOF are promising conductive agent-free oxygen evolution reaction (OER) catalysts. This work provides a fast-tracked strategy for the design and development of functional materials, which serves as a potentially workable framework for seamlessly integrating DFT calculations, ML, and experimental approaches.

Boosting-Crystal Graph Convolutional Neural Network for Predicting Highly Imbalanced Data: A Case Study for Metal-Insulator Transition Materials

Applying machine-learning techniques for imbalanced data sets presents a significant challenge in materials science since the underrepresented characteristics of minority classes are often buried by the abundance of unrelated characteristics in majority of classes. Existing approaches to address this focus on balancing the counts of each class using oversampling or synthetic data generation techniques. However, these methods can lead to loss of valuable information or overfitting. Here, we introduce a deep learning framework to predict minority-class materials, specifically within the realm of metal-insulator transition (MIT) materials. The proposed approach, termed boosting-CGCNN, combines the crystal graph convolutional neural network (CGCNN) model with a gradient-boosting algorithm. The model effectively handled extreme class imbalances in MIT material data by sequentially building a deeper neural network. The comparative evaluations demonstrated the superior performance of the proposed model compared to other approaches. Our approach is a promising solution for handling imbalanced data sets in materials science.

Machine Learning on Microstructure-Property Relationship of Lithium-Ion Conducting Oxide Solid Electrolytes

Understanding the structure-property relationship of lithium-ion conducting solid oxide electrolytes is essential to accelerate their development and commercialization. However, the structural complexity of nonideal materials increases the difficulty of study. Here, we develop an algorithmic framework to understand the effect of microstructure on the properties by linking the microscopic morphology images to their ionic conductivities. We adopt garnet and perovskite polycrystalline oxides as examples and quantify the microscopic morphologies via extracting determined physical parameters from the images. It directly visualizes the effect of physical parameters on their corresponding ionic conductivities. As a result, we can determine the microstructural features of a Li-ion conductor with high ionic conductivity, which can guide the synthesis of highly conductive solid electrolytes. Our work provides a novel approach to understanding the microstructure-property relationship for solid-state ionic materials, showing the potential to extend to other structural/functional ceramics with various physical properties in other fields.

Data-Driven Evolutionary Design of Multienzyme-like Nanozymes

Multienzyme-like nanozymes are nanomaterials with multiple enzyme-like activities and are the focus of nanozyme research owing to their ability to facilitate cascaded reactions, leverage synergistic effects, and exhibit environmentally responsive selectivity. However, multienzyme-like nanozymes exhibit varying enzyme-like activities under different conditions, making them difficult to precisely regulate according to the design requirements. Moreover, individual enzyme-like activity in a multienzyme-like activity may accelerate, compete, or antagonize each other, rendering the overall activity a complex interplay of these factors rather than a simple sum of single enzyme-like activity. A theoretically guided strategy is highly desired to accelerate the design of multienzyme-like nanozymes. Herein, nanozyme information was collected from 4159 publications to build a nanozyme database covering element type, element ratio, chemical valence, shape, pH, etc. Based on the clustering correlation coefficients of the nanozyme information, the material features in distinct nanozyme classifications were reorganized to generate compositional factors for multienzyme-like nanozymes. Moreover, advanced methods were developed, including the quantum mechanics/molecular mechanics method for analyzing the surface adsorption and binding energies of substrates, transition states, and products in the reaction pathways, along with machine learning algorithms to identify the optimal reaction pathway, to aid the evolutionary design of multienzyme-like nanozymes. This approach culminated in creating CuMnCo7O12, a highly active multienzyme-like nanozyme. This process is named the genetic-like evolutionary design of nanozymes because it resembles biological genetic evolution in nature and offers a feasible protocol and theoretical foundation for constructing multienzyme-like nanozymes.

Insights into Nano- and Micro-Structured Scaffolds for Advanced Electrochemical Energy Storage

Adopting a nano- and micro-structuring approach to fully unleashing the genuine potential of electrode active material benefits in-depth understandings and research progress toward higher energy density electrochemical energy storage devices at all technology readiness levels. Due to various challenging issues, especially limited stability, nano- and micro-structured (NMS) electrodes undergo fast electrochemical performance degradation. The emerging NMS scaffold design is a pivotal aspect of many electrodes as it endows them with both robustness and electrochemical performance enhancement, even though it only occupies complementary and facilitating components for the main mechanism. However, extensive efforts are urgently needed toward optimizing the stereoscopic geometrical design of NMS scaffolds to minimize the volume ratio and maximize their functionality to fulfill the ever-increasing dependency and desire for energy power source supplies. This review will aim at highlighting these NMS scaffold design strategies, summarizing their corresponding strengths and challenges, and thereby outlining the potential solutions to resolve these challenges, design principles, and key perspectives for future research in this field. Therefore, this review will be one of the earliest reviews from this viewpoint.

Superionic lithium transport via multiple coordination environments defined by two-anion packing

Fast cation transport in solids underpins energy storage. Materials design has focused on structures that can define transport pathways with minimal cation coordination change, restricting attention to a small part of chemical space. Motivated by the greater structural diversity of binary intermetallics than that of the metallic elements, we used two anions to build a pathway for three-dimensional superionic lithium ion conductivity that exploits multiple cation coordination environments. Li7Si2S7I is a pure lithium ion conductor created by an ordering of sulphide and iodide that combines elements of hexagonal and cubic close-packing analogously to the structure of NiZr. The resulting diverse network of lithium positions with distinct geometries and anion coordination chemistries affords low barriers to transport, opening a large structural space for high cation conductivity.

Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery

Thermally activated delayed fluorescence (TADF) material has attracted great attention as a promising metal-free organic light-emitting diode material with a high theoretical efficiency. To accelerate the discovery of novel TADF materials, computer-aided material design strategies have been developed. However, they have clear limitations due to the accessibility of only a few computationally tractable properties. Here, we propose TADF-likeness, a quantitative score to evaluate the TADF potential of molecules based on a data-driven concept of chemical similarity to existing TADF molecules. We used a deep autoencoder to characterize the common features of existing TADF molecules with common chemical descriptors. The score was highly correlated with the four essential electronic properties of TADF molecules and had a high success rate in large-scale virtual screening of millions of molecules to identify promising candidates at almost no cost, validating its feasibility for accelerating TADF discovery. The concept of TADF-likeness can be extended to other fields of materials discovery.

A Polytetrafluoroethylene-Based Solvent-Free Procedure for the Manufacturing of Lithium-Ion Batteries

Lithium-ion batteries (LIBs) have recently become popular for energy storage due to their high energy density, storage capacity, and long-term cycle life. Although binders make up only a small proportion of LIBs, they have become the key to promoting the transformation of the battery preparation process. Along with the development of binders, the battery manufacturing process has evolved from the conventional slurry-casting (SC) process to a more attractive solvent-free (SF) method. Compared with traditional LIBs manufacturing method, the SF method could dramatically reduce and increase the energy density due to the reduced preparation steps and enhanced electrode loading. Polytetrafluoroethylene (PTFE), as a typical binder, has played an important role in fabricating high-performance LIBs, particularly in regards to the SF technique. In this paper, the development history and application status of PTFE binder was introduced, and then its contributions and the inherent problems involved in the SF process were described and analyzed. Finally, the viewpoints concerning the future trends for PTFE-based SF manufacturing methods were also discussed. We hope this work can inspire future research concerning high-quality SF binders and assist in promoting the evolution of the SF manufacturing technology in regards to LIBs.

Aqueous batteries: from laboratory to market

This perspective discusses the fundamental benefits and drawbacks of aqueous batteries and the challenges of the development of such battery technology from laboratory scale to industrial applications.

A NiS2/C composite as an innovative anode material for sodium-ion batteries: ex situ XANES and EXAFS studies to investigate the sodium storage mechanism

The successful deployment of sodium-ion batteries (SIBs) requires high-performance sustainable and cost-effective anode materials having a high current density. In this regard, sodium disulphide (NiS2) has been prepared as a composite with activated carbon (C) using a facile hydrothermal synthesis route in the past. The X-ray diffraction pattern of the as-prepared NiS2/C composite material shows well-defined diffraction peaks of NiS2. Most carbonaceous materials are amorphous, and the Brunauer-Emmett-Teller (BET) study shows that the surface area is close to 148 m2 g-1. At a current density of 50 mA g-1, the NiS2/C composite exhibits a high capacity of 480 mA h g-1 during the initial cycle, which subsequently decreases to 333 mA h g-1 after the completion of the 100th cycle. The NiS2/C composite electrode provides an exceptional rate capability by delivering a capacity of 270 mA h g-1 at a high current density of 2000 mA g-1, suggesting the suitability of the NiS2/C composite for SIBs. Ex situ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) analyses at the Ni K-edge have been used to examine the type of chemical bonding present in the anode and also how it changes during electrochemical redox cycling. The understanding of the sodium storage mechanism is improved by the favorable results, which also offer insights for developing high-performance electrode materials for rechargeable SIBs.

Double-Transition-Metal MXene Films Promoting Deeply Rechargeable Magnesium Metal Batteries

Magnesium metal batteries are promising candidates for next-generation high-energy-density and low-cost energy storage systems. Their application, however, is precluded by infinite relative volume changes and inevitable side reactions of Mg metal anodes. These issues become more pronounced at large areal capacities that are required for practical batteries. Herein, for the first time, double-transition-metal MXene films are developed to promote deeply rechargeable magnesium metal batteries using Mo2 Ti2 C3 as a representative example. The freestanding Mo2 Ti2 C3 films, which are prepared using a simple vacuum filtration method, possess good electronic conductivity, unique surface chemistry, and high mechanical modulus. These superior electro-chemo-mechanical merits of Mo2 Ti2 C3 films help to accelerate electrons/ions transfer, suppress electrolyte decomposition and dead Mg formation, as well as maintain electrode structural integrity during long-term and large-capacity operation. As a result, the as-developed Mo2 Ti2 C3 films exhibit reversible Mg plating/stripping with high Coulombic efficiency of 99.3% at a record-high capacity of 15 mAh cm-2 . This work not only sheds innovative insights into current collector design for deeply cyclable Mg metal anodes, but also paves the way for the application of double-transition-metal MXene materials in other alkali and alkaline earth metal batteries.

Uncovering the Binder Interactions with S-PAN and MXene for Room Temperature Na-S Batteries

MXenes and sulfurized polyacrylonitrile (S-PAN) are emerging as possible contenders to resolve the polysulfide dissolution and volumetric expansion issues in sodium-sulfur batteries. Herein, we explore the interactions between Ti₃C₂T_x MXenes and S-PAN with traditional binders such as polyvinylidene difluoride (PVDF), poly(acrylic acid) (PAA), and carboxymethyl cellulose (CMC) in Na-S batteries for the first time. We hypothesize that the linearity and polarity of the binder significantly influence the dispersion of S-PAN over Ti₃C₂T_x. The three-dimensional polar CMC binder resulted in better contact surface area with both S-PAN and Ti₃C₂T_x. Moreover, the improved binding of the discharge products with the CMC binder effectively traps them and prevents unwanted shuttling. Consequently, the Na-S battery using the CMC binder displayed a high initial capacity of 1282 mAh/g_(s) at 0.2 C and a low capacity fading of 0.092% per cycle over 300 cycles. This work highlights the importance of understanding MXene-binder interactions in sulfur cathodes.

Additive-Driven Interfacial Engineering of Aluminum Metal Anode for Ultralong Cycling Life

Rechargeable Al batteries (RAB) are promising candidates for safe and environmentally sustainable battery systems with low-cost investments. However, the currently used aluminum chloride-based electrolytes present a significant challenge to commercialization due to their corrosive nature. Here, we report for the first time, a novel electrolyte combination for RAB based on aluminum trifluoromethanesulfonate (Al(OTf)3) with tetrabutylammonium chloride (TBAC) additive in diglyme. The presence of a mere 0.1 M of TBAC in the Al(OTf)3 electrolyte generates the charge carrying electrochemical species, which forms the basis of reaction at the electrodes. TBAC reduces the charge transfer resistance and the surface activation energy at the anode surface and also augments the dissociation of Al(OTf)3 to generate the solid electrolyte interphase components. Our electrolyte's superiority directly translates into reduced anodic overpotential for cells that ran for 1300 cycles in Al plating/stripping tests, the longest cycling life reported to date. This unique combination of salt and additive is non-corrosive, exhibits a high flash point and is cheaper than traditionally reported RAB electrolyte combinations, which makes it commercially promising. Through this report, we address a major roadblock in the commercialization of RAB and inspire equivalent electrolyte fabrication approaches for other metal anode batteries.

High-Performance NiS2 Hollow Nanosphere Cathodes in Magnesium-Ion Batteries Enabled by Tunable Redox Chemistry

Two-dimensional metal dichalcogenides have demonstrated outstanding potential as cathodes for magnesium-ion batteries. However, the limited capacity, poor cycling stability, and severe electrode pulverization, resulting from lack of void space for expansion, impede their further development. In this work, we report for the first time, nickel sulfide (NiS₂) hollow nanospheres assembled with nanoparticles for use as cathode materials in magnesium-ion batteries. Notably, the nanospheres were prepared by a one-step solvothermal process in the absence of an additive. The results show that regulating the synergistic effect between the rich anions and hollow structure positively affects its electrochemical performance. Crystallographic and microstructural characterizations reveal the reversible anionic redox of S^2-/(S₂)^2-, consistent with density functional theory results. Consequently, the optimized cathode (8-NiS₂ hollow nanospheres) could deliver a large capacity of 301 mA h g^-1 after 100 cycles at 50 mA g^-1, supporting the promising practical application of NiS₂ hollow nanospheres in magnesium-ion batteries.

Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture

Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress in machine learning has stimulated technological breakthroughs in the discovery, design, and deployment of materials with potential for high-performance and low-cost clean energy applications. This review summarizes basic machine learning methods-data collection, featurization, model generation, and model evaluation-and reviews their use in the development of robust adsorbent materials. Key case studies are provided where these methods are used to accelerate adsorbent materials design and discovery, optimize synthesis conditions, and understand complex feature-property relationships. The review provides a concise resource for researchers wishing to use machine learning methods to rapidly develop effective adsorbent materials with a positive impact on the environment.

In Situ Formed Magnesiophilic Sites Guiding Uniform Deposition for Stable Magnesium Metal Anodes

Owing to its high volumetric capacity and natural abundance, magnesium (Mg) metal has attracted tremendous attention as an ideal anode material for rechargeable Mg batteries. Despite Mg deposition playing an integral role in determining the cycling lifespan, its exact behavior is not clearly understood yet. Herein, for the first time, we introduce a facile approach to build magnesiophilic In/MgIn sites in situ on a Mg metal surface using InCl₃ electrolyte additive for rechargeable Mg batteries. These magnesiophilic sites can regulate Mg deposition behaviors by homogenizing the distributions of Mg-ion flux and electric field at the electrode-electrolyte interphase, allowing flat and compact Mg deposition to inhibit short-circuiting. The as-designed Mg metal batteries achieve a stable cycling lifespan of 340 h at 1.0 mA cm^-2 and 1.0 mAh cm^-2 using Celgard separators, while the full cell coupled with Mo₆S₈ cathode maintains a high capacity retention of 95.5% over 800 cycles at 1 C.

Spherical Templating of CoSe2 Nanoparticle-Decorated MXenes for Lithium-Sulfur Batteries

Two-dimensional MXenes produce competitive performances when incorporated into lithium-sulfur batteries (LSBs), solving key problems such as the poor electronic conductivity of sulfur and dissolution of its polysulfide intermediates. However, MXene nanosheets are known to easily aggregate and restack during electrode fabrication, filtration, or water removal, limiting their practical applicability. Furthermore, in complex electrocatalytic reactions like the multistep sulfur reduction process in LSBs, MXene alone is insufficient to ensure an optimal reaction pathway. In this work, we demonstrate for the first time a loose templating of sulfur spheres using Ti₃C₂T_x MXene nanosheets decorated with polymorphic CoSe₂ nanoparticles. This work shows that the templating of sulfur spheres using nanoparticle-decorated MXene nanosheets can prevent nanosheet aggregation and exert a strong electrocatalytic effect, thereby enabling improved reaction kinetics and battery performance. The S@MXene-CoSe₂ cathode demonstrated a long cycle life of 1000 cycles and a low capacity decay rate of 0.06% per cycle in LSBs.