Direct Nanoscale Characterization of Deep Levels in AgCuInGaSe2 Using Electron Energy‐Loss Spectroscopy in the Scanning Transmission Electron Microscope

A new experimental framework for the characterization of defects in semiconductors is demonstrated. Through the direct, energy‐resolved correlation of three analytical techniques spanning six orders of magnitude in spatial resolution, a critical mid‐bandgap electronic trap level (E_V + 0.56 eV) within Ag_0.2Cu_0.8In_1?xGa_xSe₂ is traced to its nanoscale physical location and chemical source. This is achieved through a stepwise, site‐specific correlated characterization workflow consisting of device‐scale (≈1 mm²) deep level transient spectroscopy (DLTS) to survey the traps present, scanning probe–based DLTS (scanning‐DLTS) for mesoscale‐resolved (hundreds of nanometers) mapping of the target trap state's spatial distribution, and scanning transmission electron microscope based electron energy‐loss spectroscopy (STEM‐EELS) and X‐ray energy‐dispersive spectroscopy for nanoscale energy‐, structure, and chemical‐resolved investigation of the defect source. This first demonstration of the direct observation of sub‐bandgap defect levels via STEM‐EELS, combined with the DLTS methods, provides strong evidence that the long‐suspected Cu_In/Ga substitutional defects are indeed the most likely source of the E_V + 0.56 eV trap state and serves as a key example of this approach for the fundamental identification of defects within semiconductors, in general.     

An Air‐Stable and Dendrite‐Free Li Anode for Highly Stable All‐Solid‐State Sulfide‐Based Li Batteries

Li metal is a promising anode material for all‐solid‐state batteries, owing to its high specific capacity and low electrochemical potential. However, direct contact of Li metal with most solid‐state electrolytes induces severe side reactions that can lead to dendrite formation and short circuits. Moreover, Li metal is unstable when exposed to air, leading to stringent processing requirements. Herein, it is reported that the Li₃PS₄/Li interface in all‐solid‐state batteries can be stabilized by an air‐stable Li_xSiS_y protection layer that is formed in situ on the surface of Li metal through a solution‐based method. Highly stable Li cycling for over 2000 h in symmetrical cells and a lifetime of over 100 cycles can be achieved for an all‐solid‐state LiCoO₂/Li₃PS₄/Li cell. Synchrotron‐based high energy X‐ray photoelectron spectroscopy in‐depth analysis demonstrates the distribution of different components within the protection layer. The in situ formation of an electronically insulating Li_xSiS_y protection layer with highly ionic conductivity provides an effective way to prevent Li dendrite formation in high‐energy all‐solid‐state Li metal batteries.     

A New P2‐Type Layered Oxide Cathode with Extremely High Energy Density for Sodium‐Ion Batteries

Herein, a new P2‐type layered oxide is proposed as an outstanding intercalation cathode material for high energy density sodium‐ion batteries (SIBs). On the basis of the stoichiometry of sodium and transition metals, the P2‐type Na_0.55[Ni_0.1Fe_0.1Mn_0.8]O₂ cathode is synthesized without impurities phase by partially substituting Ni and Fe into the Mn sites. The partial substitution results in a smoothing of the electrochemical charge/discharge profiles and thus greatly improves the battery performance. The P2‐type Na_0.55[Ni_0.1Fe_0.1Mn_0.8]O₂ cathode delivers an extremely high discharge capacity of 221.5 mAh g^?1 with a high average potential of ≈2.9 V (vs Na/Na⁺) for SIBs. In addition, the fast Na‐ion transport in the P2‐type Na_0.55[Ni_0.1Fe_0.1Mn_0.8]O₂ cathode structure enables good power capability with an extremely high current density of 2400 mA g^?1 (full charge/discharge in 12 min) and long‐term cycling stability with ≈80% capacity retention after 500 cycles at 600 mA g^?1. A combination of electrochemical profiles, in operando synchrotron X‐ray diffraction analysis, and first‐principles calculations are used to understand the overall Na storage mechanism of P2‐type Na_0.55[Ni_0.1Fe_0.1Mn_0.8]O₂.     

Vanadate‐Based Materials for Li‐Ion Batteries: The Search for Anodes for Practical Applications

While the practical application of electrode materials depends intensively on the Li⁺ ion storage mechanisms correlating ultimately with the coulombic efficiency, reversible capacity, and morphology variation of electrode material upon cycling, only intercalation‐type electrode materials have proven viable for commercialization up to now. This paper reviews the promising anode materials of metal vanadates (M_xV_yO_z, M = Co, Cu, Mn, Fe, Zn, Ni, Li) that have high capacity, low cost, and abundant resource, and also discusses the related Li⁺ ion storage mechanism. It is concluded that most of these (M_xV_yO_z, M = Co, Cu, Mn, Fe, Zn, Ni) exhibit irreversible redox reactions upon lithiation/delithiation accompanied by large volume expansion, which is not favorable for industrial applications. In particular, Li₃VO₄ with specific intercalation Li⁺ ion storage mechanism and compatible merits of safety and energy density exhibits great potential for practical application. This review systematically summarizes the latest progress in Li₃VO₄ research, including the representative fabrication approaches for advanced morphology and state‐of‐the‐art technologies to boost performance and the morphology variation associated with Li⁺ ion storage mechanisms. Furthermore, an outlook on where breakthroughs for Li₃VO₄ may be most likely achieved will be provided.     

An In Situ Interface Reinforcement Strategy Achieving Long Cycle Performance of Dual‐Ion Batteries

Dual‐ion batteries (DIBs) with high operation voltage offer promising candidates for low‐cost clean energy chemistries. However, there still exist tough issues, including structural collapse of the graphite cathode due to solvent co‐intercalation and electrolyte decomposition on the electrode/electrolyte interface, which results in unsatisfactory cyclability and fast battery failure. Herein, Li₄Ti₅O₁₂ (LTO) modified mesocarbon microbeads (MCMBs) are proposed as a cathode material. The LTO layer functions as a skeleton and offers electrocatalytic active sites for in situ generation of a favorable and compatible cathode electrolyte interface (CEI) layer. The synergetic LTO‐CEI network can change the thermodynamic behavior of the PF₆^? intercalation process and maintain the structural integrity of the graphite cathode, as a “Great Wall” to protect the cathode from structural collapse and electrolyte decomposition. Such LTO‐CEI reinforced cathode exhibits a prolonged cyclability with 85.1% capacity retention after 2000 cycles even at cut‐off potential of 5.4 V versus Li⁺/Li. Moreover, the LTO‐modified MCMB (+)//prelithiated MCMB (?) full cell exhibits a high energy density of ≈200 Wh kg^?1, remarkably enhanced cyclability with 93.5% capacity retention after 1000 cycles. Undoubtedly, this work offers in‐depth insight into interface chemistry, which can arouse new originality to boost the development of DIBs.     

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

sam βada is a genome–environment association software, designed to search for signatures of local adaptation. However, pre‐ and postprocessing of data can be labour‐intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r ‐package providing a pipeline for landscape genomic analysis based on sam βada , spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).     

RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: A case study in roe deer

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree‐free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long‐term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD‐sequencing for estimating heritability in a free‐ranging roe deer (Capreolous capreolus) population for which no prior genomic resources were available. We propose a step‐by‐step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the single nucleotide polymorphism (SNP) calling and filtering processes on the GRM structure and GRM‐based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7,000). Genomic relatedness matrix‐based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP data set. We also showed that quality filters, such as the removal of low‐frequency variants, affect the relatedness structure of the GRM, generating lower h² estimates. Our work illustrates the huge potential of RAD‐sequencing for estimating GRM‐based heritability in virtually any natural population.