We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided by machine learning-based methods. The discovery of new solid Li superionic conductors is of critical importance to the development of safe all-solid-state Li-ion batteries. With a predictive universal structure-property relationship for fast ion conduction not well understood, the search for new solid Li ion conductors has relied largely on trial-and-error computational and experimental searches over the last several decades. In this work, we perform a guided search of materials space with a machine learning (ML)-based prediction model for material selection and density functional theory molecular dynamics (DFT-MD) simulations for calculating ionic conductivity. These materials are screened from over 12,000 experimentally synthesized and characterized candidates with very diverse structures and compositions. When compared to a random search of materials space, we find that the ML-guided search is 2.7 times more likely to identify fast Li ion conductors, with at least a 45x improvement in the log-average of room temperature Li ion conductivity. The F1 score of the ML-based model is 0.50, 3.5 times better than the F1 score expected from completely random guesswork. In a head-to-head competition against six Ph.D. students working in the field, we find that the ML-based model doubles the F1 score of human experts in its ability to identify fast Li-ion conductors from atomistic structure with a thousand- fold increase in speed, clearly demonstrating the utility of this model for the research community. All conducting materials reported here lack transition metals and are predicted to exhibit low electronic conduction, high stability against oxidation, and high thermodynamic stability.
For machine learning of interatomic potentials a scalable sparse Gaussian process regression formalism is introduced with a data-efficient on-the-fly adaptive sampling algorithm. With this approach, the computational cost is effectively reduced to those of the Bayesian linear regression methods whilst maintaining the appealing characteristics of the exact Gaussian process regression. As a showcase, experimental melting and glass-crystallization temperatures are reproduced for Li7P3S11, Li diffusivity is simulated, and an unchartered phase is revealed with much lower Li diffusivity which should…
Limitations of In$_2$O$_3$ as a transparent conducting oxide
Sn掺杂的In $_2$ O $_3$或ITO是最广泛使用的透明导电氧化物。我们使用第一性原理计算来研究由于声子或带电缺陷介导的自由载流子吸收对其透明性的限制。我们发现，声子辅助的间接吸收的主要贡献是由于发射（而不是吸收）的声子，这解释了为什么该过程是相对不敏感的温度。这种间接吸收过程的波长依赖性可以用幂律来描述。由带电缺陷或杂质介导的间接吸收也是不可避免的，因为需要掺杂以获得导电性。在高载流子浓度下，通过自由载流子的筛选变得重要。我们发现当杂质浓度大于10 $^{20}$ cm $^{-3}$时，带电杂质辅助吸收大于声子辅助吸收。这两个过程的光子能量依赖性的差异可以通过能带结构效应来解释。
Structural, Electrical Properties and Dielectric Relaxation in Na+ Ion Conducting Solid Polymer Electrolyte
本文报道了由PEO_8-NaPF_6 + x wt.组成的钠基固体聚合物电解质膜的结构、微观结构、电性能、介电性能和离子动力学。% SN。用XRD和FESEM研究了样品的结构和表面形貌。通过FTIR分析了聚合物、盐和SN之间的不同微观相互作用。介电常数和损耗角正切使我们能够估计直流电导率，介电强度，双层电容和弛豫时间。损耗角正切弛豫峰向高频侧移动，表明弛豫时间缩短，离子动力学加快。此外，各种弛豫时间之间的关系......它是系统地发展起来的。离子电导率已估计在整个频率窗口，包括JPL和显示强烈的依赖于SN含量。sigma表示法...通过突出Cole-Cole图中的色散区域来探索离子动力学（........）在较低的频率窗口和半径的增加表明弛豫时间的减少。一个很有说服力/逻辑的计划已被提出证明记录的实验数据。
Switching behavior of bulk Fast Ion Conducting AgI-Ag2O-MoO3 glasses with inert electrode
开发高效、快速性能和热稳定的基于碘化银的快速离子传导固体对于电阻开关应用具有极大的兴趣，但仍然存在挑战。金属化的散装，阈值电压曲线的行为组成和腐蚀反应是这些挑战的几个。本文研究了快离子导电玻璃体（AgI）x-（Ag_2O）_25-（MoO_3）_75-x（60 < x < 40）固体的开关行为，以了解惰性电极的开关机理。通过使用惰性电极，开关变成不可逆的记忆型。开关机制是电化学金属化过程。惰性电极抑制离子传质，但对电子转移表现出低势垒，允许阴极金属化反应更快地达到能斯特平衡。该过程中涉及的阳离子在固体结构内的自由体积中传输，并遵循电场驱动的热激活离子跳跃电导模型的Mott-Gurney模型。该模型与热稳定性曲线一起提供了组合物内的窄区域，该组合物具有基于达到阈值电压的不稳定性的更好的开关性能和更少的功率损耗。痕量的阴离子对金属化的贡献是不存在的。此外，阳极氧化涉及导致气泡形成和腐蚀的反应。
Solid-state ionic conduction is a key enabler of electrochemical energy storage and conversion. The mechanistic connections between material processing, defect chemistry, transport dynamics, and practical performance are of considerable importance, but remain incomplete. Here, inspired by studies of fluids and biophysical systems, we re-examine anomalous diffusion in the iconic two-dimensional fast-ion conductors, the $β$- and $β^{\prime\prime}$-aluminas. Using large-scale simulations, we reproduce the frequency dependence of alternating-current ionic conductivity data. We show how the distrib…
SrVO3 thin films with a high figure of merit for applications as transparent conductors were crystallized from amorphous layers using solid phase epitaxy (SPE). Epitaxial SrVO3 films crystallized on SrTiO3 using SPE exhibit a room temperature resistivity of 2.5 x 10-5 Ohms cm, a residual resistivity ratio of 3.8, and visible light transmission above 0.5 for a 60 nm-thick film. SrVO3 layers were deposited at room temperature using radio-frequency sputtering in an amorphous form and subsequently crystallized by heating in controlled gas environment. The lattice parameters and mosaic angular widt…
Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?
Bakar Institute of Digital Materials for the Planet, UC Berkeley（加州大学伯克利分校巴卡尔数字材料行星研究所）；Materials Sciences Division, Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室材料科学部）；Department of Materials Science and Engineering, National University of Singapore（新加坡国立大学材料科学与工程系）
We propose a microscopic, first-principles description of the ionic conduction in crystals. This formalism allows us to gain new insights into the ideal characteristics of general ionic conducting materials and, in particular, solid electrolytes. Using \textit{ab initio} calculations, we show that our formalism results in ionic mobilities consistent with experiments for several materials. Our work opens the possibility of developing solid electrolytes based on fundamental physical principles rather than empirical descriptions of the underlying processes.
In Situ Nanometer-Resolution Strain and Orientation Mapping for Gas-Solid Reactions via Precession-Assisted Four-dimensional Scanning Transmission Electron Microscopy
To accelerate the development of novel ion-conducting materials, we present a general graph-theoretic analysis framework for ion migration in any crystalline structure. The nodes of the graph represent metastable sites of the migrating ion and the edges represent discrete migration events between adjacent sites. Starting from a collection of possible metastable migration sites, the framework assigns a weight to the edges by calculating the individual migration energy barriers between those sites. Connected pathways in the periodic simulation cell corresponding to macroscopic ion migration are …
A first principles analysis of the Colossal Ion Conductivity cubic Zirconia structural hypothesis and disorder, mechanics, and space charge mechanistic hypotheses
Flexible, solid electrolyte-based lithium battery composed of LiFePO4 cathode and Li4Ti5O10 anode for applications in smart textiles
在这里，我们报告制造的灵活和可拉伸的电池组成的应变自由LiFePO 4阴极，Li 4 Ti 5 O 10阳极和固体聚环氧乙烷（PEO）电解质作为隔膜层。该电池是从智能纺织品应用的角度开发的。该电池以固体热塑性电解质为关键使能元件，可挤压或拉伸成纤维或细条，直接与智能纺织品制造中使用的编织工艺兼容。本文首先详细介绍了材料的选择，电极和隔膜层的制造和表征。然后组装电池并对其进行表征，最后，将由几个长条制成的大型电池样品编织成织物，用导电线连接，并进行表征。在本文中，我们详细研究了电池设计的两个实际方面：第一是以导电碳和聚合物粘合剂材料的优化比例制备阴极/阳极材料的复合材料，第二是电池性能，包括循环，可逆性和阴极/阳极材料的相容性。最后，当铸造电极和隔膜层时，我们主要关注使用水溶液代替有机溶剂，以使制造过程环境友好。
We present a gradient-based theoretical framework for predicting hydrogen assisted fracture in elastic-plastic solids. The novelty of the model lies in the combination of: (i) stress-assisted diffusion of solute species, (ii) strain gradient plasticity, and (iii) a hydrogen-sensitive phase field fracture formulation, inspired by first principles calculations. The theoretical model is numerically implemented using a mixed finite element formulation and several boundary value problems are addressed to gain physical insight and showcase model predictions. The results reveal the critical role of p…
