Results for “Energy storage materials” — Page 6

DOE OSTI2022

Spontaneous Lithiation of Binary Oxides during Epitaxial Growth on LiCoO 2

Epitaxial growth is a powerful tool for synthesizing heterostructures and integrating multiple functionalities. Interfacial mixing can readily occur at temperatures required for complete film crystallization and can significantly modify the properties of layered structures, particularly for those containing energy storage materials with smaller cations. Here we show a two-step sequence involving the growth of an epitaxial LiCoO 2 cathode layer followed by the deposition of a binary transition metal oxide (WO 3 , TiO 2 , and others) in which controlled lithiation of the binary oxide occurs. Orientation-controlled epitaxial synthesis of the model solid-state-electrolyte Li 2 WO 4 and model anode material Li 4 Ti 5 O 12 occurs as WO 3 and TiO 2 nucleate their respective host lattices and attract Li ions from the underlying cathode. The cathode layer readily provides a tunable amount of Li ions for the controlled lithiation of the subsequent layer. We demonstrate that this approach can be used for energy materials discovery and exploring different combinations of epitaxial interfaces that can serve as well-defined model systems for mechanistic studies of energy storage and conversion processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Ionothermally Synthesized Nanoporous Ti 0.95 W 0.05 Nb 2 O 7 : a Novel Anode Material for High-Performance Lithium-Ion Batteries

Although TiNb 2 O 7 is regarded as a fast-rechargeable lithium-ion battery (LIB) anode material, the intrinsic poor electrochemical kinetics of TiNb 2 O 7 still dramatically impedes its development. Herein, an ionothermal synthesis-assisted doping strategy is proposed for the preparation of a new W 6+ -doped TiNb 2 O 7 material (Ti 0.95 W 0.05 Nb 2 O 7 ) with nanoporous structure (denoted as NPTWNO). The improved Li + diffusion coefficient of NPTWNO suggests that the ionic-liquid-templated nanoporous architecture improves the Li+ diffusion kinetics. The density functional theory computational study reveals that the doped W 6+ successfully boosts the electronic conductivity due to the narrowed conduction-valance bandgap resulted from charge redistribution, which is reflected by the electrochemical impedance spectroscopy data. With the simultaneously enhanced Li+ diffusivity and electronic conductivity, NPTWNO achieves fast-rechargeability in LIBs. So this work indicates the potential of ionothermal synthesis-assisted doping strategy on energy storage materials and offers NPTWNO material with promising electrochemical performance.

25 ENERGY STORAGE↗

DOE OSTI2023

Water-coupled monovalent and divalent ion transport in polyviologen networks

Redox-active polymers (RAPs) are of interest as environmentally friendly and earth-abundant energy storage materials. Polyviologens are promising RAPs, but they tend to dissolve during operation. Further, the two-electron redox reaction for polyviologens in various electrolytes is not always reversible, highlighting the need for a deeper understanding of the redox mechanism. Here, the energy storage mechanism for a cross-linked viologen (PTPM) is demonstrated using electrochemical quartz crystal microbalance with dissipation monitoring (EQCM-D), comparing NaCl and Na2SO4 aqueous electrolytes. E-QCMD reveals that the ion-electron transport mechanism is strongly dependent on the valency of the anion. More sudden and dramatic changes in the electrode's mass were observed for the divalent sulfate ion as compared to the smooth mass transitions associated with the monovalent chloride ion. Meanwhile, there was marked hysteresis in the mass transfer profile for NaCl, but little hysteresis for Na2SO4. Our results demonstrate that electrolyte design, and specifically ion valency, will have a large impact on the nature of mass transport in polymer-based electrodes. This work enables electrolyte selection for the next generation polymer batteries with improved performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗

DOE OSTI2024

Beyond the Hype: Navigating the Promise and Pitfalls of Multi-Modal Models for Materials Science

Multi-modal models offer great potential for accelerating discovery in materials and chemical systems, but their adoption raises crucial questions: What materials science challenges are best addressed by multi-modal approaches? How do we weigh the benefits against the resource investment required for multi-modal data acquisition? And critically, how can we optimize experimental workflows to leverage these models effectively? In this presentation, I will delve into the development of multi-modal characterization and analytics, focusing on their application in the demanding fields of next-generation microelectronics and energy storage materials. I will share challenges encountered in designing these workflows, highlighting lessons learned and posing questions that remain unanswered.

AI↗

DOE OSTI2021

Giant Polarization in Nanodielectrics

The relative permittivity of a material is a scaling factor for capacitors and the devices based upon them; the larger the relative permittivity, the greater the degree of miniaturization, or potential for energy storage. Materials with a relative permittivity than that of silicon nitride (approximately 7) are referred to as high-dielectric constant materials. Values of about 100 are typical in titanium dioxide rutile. Values of about 10,000 are observed in barium titanate in the region of the ferroelectric transition, which while impressive, is not very useful due to the strong temperature dependence. The observation of a relative permittivity of over 100,000 in the calcium copper titanate material sparked considerable interest because it showed little temperature dependence between 100 and 600 K over most of the radio-frequency range. Further investigation revealed that this material appears to be naturally nanotextured and that the colossal permittivity was likely due to the surface and/or internal barrier layer capacitance effect, although the issue is not settled. Unfortunately, the dielectric losses in this class materials are relatively high. A new strategy to achieve high dielectric permittivity with low loss involves using localized lattice defect states through ambipolar co-doping; these intrinsic defect complexes give rise to strong dipoles that are responsible for a relative permittivity of 10,000 with exceptionally low dielectric losses over most of the radio frequency range and excellent thermal stability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Giant polarization in nanodielectrics

The relative permittivity of a material is a scaling factor for capacitors and the devices based upon them; the larger the relative permittivity, the greater the degree of miniaturization, or potential for energy storage. Materials with a relative permittivity than that of silicon nitride (approximately 7) are referred to as high-dielectric constant materials. Values of about 100 are typical in titanium dioxide rutile. Values of about 10,000 are observed in barium titanate in the region of the ferroelectric transition, which while impressive, is not very useful due to the strong temperature dependence. The observation of a relative permittivity of over 100,000 in the calcium copper titanate material sparked considerable interest because it showed little temperature dependence between 100 and 600 K over most of the radio-frequency range. Further investigation revealed that this material appears to be naturally nanotextured and that the colossal permittivity was likely due to the surface and/or internal barrier layer capacitance effect, although the issue is not settled. Unfortunately, the dielectric losses in this class materials are relatively high. A new strategy to achieve high dielectric permittivity with low loss involves using localized lattice defect states through ambipolar co-doping; these intrinsic defect complexes give rise to strong dipoles that are responsible for a relative permittivity of 10,000 with exceptionally low dielectric losses over most of the radio frequency range and excellent thermal stability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Progress in High-Dielectric Constant Materials

The relative permittivity of a material is a scaling factor for capacitors and the devices based upon them; the larger the relative permittivity, the greater the degree of miniaturization, or potential for energy storage. Materials with a relative permittivity than that of silicon nitride (approximately 7) are referred to as high-dielectric constant materials. Values of about 100 are typical in titanium dioxide rutile. Values of about 10,000 are observed in barium titanate in the region of the ferroelectric transition, which while impressive, is not very useful due to the strong temperature dependence. The observation of a relative permittivity of over 100,000 in the calcium copper titanate material sparked considerable interest because it showed little temperature dependence between 100 and 600 K over most of the radio-frequency range. Further investigation revealed that this material appears to be naturally nanotextured and that the colossal permittivity was likely due to the surface and/or internal barrier layer capacitance effect, although the issue is not settled. Unfortunately, the dielectric losses in this class materials are relatively high. A new strategy to achieve high dielectric permittivity with low loss involves using localized lattice defect states through ambipolar co-doping; these intrinsic defect complexes give rise to strong dipoles that are responsible for a relative permittivity of 10,000 with exceptionally low dielectric losses over most of the radio frequency range and excellent thermal stability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

In situ x-ray photoelectron spectroscopy analysis of electrochemical interfaces in battery: Recent advances and remaining challenges

An in-depth understanding of charge transfer processes at the electrochemical interfaces is a critical knowledge gap impeding the design of energy storage materials. X-ray photoelectron spectroscopy plays an important role in analyzing electronic structures of heterogeneous interfaces, such as electrode-electrolyte interphases. Correspondingly, ex situ studies based on postmortem analysis of electrode materials using x-ray techniques are widely reported in the literature but often fail to capture intermediate and transient species, which are critical for a predictive understanding of the charge transfer process. The lack of extensive in situ/operando x-ray analysis of buried interfaces in energy storage systems can be mainly attributed to technical limitations, such as the requirement of high vacuum conditions. However, in the past decade, considerable efforts have been devoted to overcoming these technical barriers and enable investigation of the solid/solid and solid/liquid interfaces. This review catalogs some of the recent progresses and new experimental designs in the application of in situ and operando x-ray photoelectron spectroscopy toward characterizing interfacial processes and emergent properties, which can help build the design strategy for advanced batteries. The remaining challenges and future research directions are also discussed, as potential paths forward in this field.

Wi, Sungun↗

DOE OSTI2024

The Rise of Intelligent Materials Science: Unleashing the Power of Machine Intelligence in Characterization

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

autonomous↗

DOE OSTI2024

Beyond Human Vision: Exploring Materials with Machine Intelligence

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

artificial intelligence↗

DOE OSTI2022

Insight into the Fast-Rechargeability of a Novel Mo 1.5 W 1.5 Nb 14 O 44 Anode Material for High-Performance Lithium-Ion Batteries

Wadsley–Roth phased niobates are promising anode materials for lithium-ion batteries, while their inherently low electrical conductivity still limits their rate-capability. Herein, a novel doped Mo 1.5 W 1.5 Nb 14 O 44 (MWNO) material is facilely prepared via an ionothermal-synthesis-assisted doping strategy. The detailed crystal structure of MWNO is characterized by neutron powder diffraction and aberration corrected scanning transmission electron microscope, unveiling the full occupation of Mo 6+ -dopant at the t1 tetrahedral site. In half-cells, MWNO exhibits enhanced fast-rechargeability. In this work, the origin of the improved performance is investigated by ultraviolet–visible diffuse reflectance spectroscopy, density functional theory (DFT) computation, and electrochemical impedance spectroscopy, revealing that bandgap narrowing improves the electrical conductivity of MWNO. Furthermore, operando X-ray diffraction elucidates that MWNO exhibits a typical solid-solution phase conversion-based lithium-ion insertion/extraction mechanism with reversible structural evolution during the electrochemical reaction. The boosted lithium-ion diffusivity of MWNO, due to the Mo 6+ /W 6+ doping effect, is confirmed by a galvanostatic intermittent titration technique and DFT. With the simultaneously enhanced electrical conductivity and lithium-ion diffusivity, MWNO successfully demonstrates its fast-rechargeability and practicality in the LiNi 0.5 Mn 1.5 O 4 -coupled full-cells. Therefore, this work illustrates the potential of ionothermal synthesis in energy storage materials and provides a mechanistic understanding of the doping effect on improving material's electrochemical performance.

25 ENERGY STORAGE↗

DOE OSTI2020

The effects of vanadium substitution on one-dimensional tunnel structures of cryptomelane: Combined TEM and DFT study

Rational design of energy storage materials requires mechanistic understanding which relies on atomic scale characterization of structure and defects. In this paper we utilize vanadium (V)-substituted one-dimensional cryptomelane as a model material to study structural features critical to electrochemical reversibility of the cathode in lithium-ion batteries. We found the substitution of manganese (Mn) atoms in the tunnel wall with V enhances structural uniformity in the parent KMn 8 O 16 material by inhibiting formation of irregular (2 × 3 and 2 × 1) manganese oxide tunnel structures. Upon lithiation, both transmission electron microscopy (TEM) and density functional theory (DFT) reveal significant structural evolution, eventually resulting in phase separation and formation of highly reduced manganese oxide. During this process, Mn 4+ accepts electrons donated by intercalated Li, while the V 4+ substituent is not electrochemically reduced but acts to stabilize the tunnel framework structure. As a result, the V substituted material shows higher operating voltage and improved electrochemical reversibility. Our results highlight the benefits of V-substitution in cryptomelane, and the significance of integrating characterization with simulation for understanding and developing design principles for lithium ion battery materials.

25 ENERGY STORAGE↗

DOE OSTI2021

In Situ Wood Delignification toward Sustainable Applications

As one of the most abundant and versatile natural materials on Earth, recently wood has attracted tremendous attention from scientists and engineers due to its outstanding advantages, including hierarchically porous microstructure, high mechanical strength, environmental friendliness, renewability, and biodegradability. Wood’s hierarchically porous structure and chemical components (e.g., cellulose, hemicelluloses, and lignin) enable its mechanical, ionic, optical, and thermal properties to be tuned via physical, chemical, and/or thermal modifications. Among these various approaches, the chemical delignification of bulk wood is the most fascinating, in which the majority of lignin and hemicelluloses is removed while leaving the cellulose intact, maintaining wood’s physical integrity and hierarchical structure. This delignified structure is unique, composed of hollow, aligned channels made up of cellulose microfibrils, and particularly attractive given its origin from a sustainable and renewable resource. As a result, delignified wood has attracted increasing attention for applications that go far beyond traditional wood utilization, such as lightweight yet strong structural materials, energy storage and conversion, environmental remediation, flexible electronics, and bioengineering. Here, we review recent developments in bulk wood delignification strategies toward the achievement of such advanced wood technologies for sustainable applications, with a focus on the research in our group. Similar to chemical pulping and bleaching, wood delignification involves a series of nucleophilic reactions based on alkaline Na 2 SO 3 or Na 2 S systems (i.e., chemical pulping) or electrophilic, radical, and oxidation reactions based on H 2 O 2 , ClO 2 , or NaClO systems (i.e., chemical bleaching) to deconstruct, fragment, and promote the hydrophilicity of lignin macromolecules, which finally make lignin easier to be removed. We discuss the structure and properties of partially and near-completely delignified wood, with a focus on process-structure–property relationships. The resulting delignified wood materials, with tunable structure and properties, demonstrate various advanced functions, in a wide range of advanced applications, such as building and construction, green energy, and electronics. Finally, the potential challenges and appealing perspectives of in situ wood delignification are discussed. In situ wood delignification, as a powerful modification strategy, has speeded up the development of advanced wood technologies and wood-based functional materials and products.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science [Slides]

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗

DOE OSTI2023

Robustness of electronic screening effects in electron spectroscopies: Example of V 2 O 5

In bulk and low-dimensional extended systems, the screening of excitations by the electron cloud is a key feature governing spectroscopic properties. Widely used computational approaches, especially in the framework of many-body perturbation theory, such as the GW approximation and the resulting approximate Bethe-Salpeter equation, are explicitly formulated in terms of the screened Coulomb interaction. In the present work, we explore the effect of screening in absorption and electron energy loss spectroscopy, concentrating on the effect of local distortions on the screening and elucidating the resulting changes in the various spectra. Using the layered bulk oxide V 2 O 5 as prototype material, we show in which way local distortions affect the screening, and in which way changes in the screening impact electron energy loss and absorption spectra including excitons. We highlight cancellations that make many-body effects in the spectra very robust with respect to structural modifications, while the band structure undergoes significant changes and the nature of the excitations may also be affected. Here, this yields insight concerning the structure-properties relations that are crucial for the use of V 2 O 5 as energy storage material, and more generally, that may be used to optimize the analysis and the calculation of electronic spectra in complex materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Data-driven multi-element substitution of TiFe alloys for tunable thermodynamics and enhanced activation behaviour for hydrogen storage

Due to their high volumetric hydrogen storage capacity under moderate storage conditions, TiFe alloys have been widely investigated as candidates for practical solid-state hydrogen storage. Partially substituting Ti or Fe sites can improve the key characteristics of TiFe alloys, such as the first hydrogen absorption step (activation) and the equilibrium hydrogen pressure (thermodynamic properties). However, the selection of substitution elements has heavily relied on intuition and trial-and-error. Also, conventional substitution strategies have mainly focused on single-element substitution within the TiFe alloy, limiting the design space and tunability for target applications. Here, to address this limitation, we report a multi-element substitution strategy motivated by an efficient, data-driven machine learning (ML) approach combined with corroborating density functional theory (DFT) calculations. Our models successfully predict experimentally measured hydride stability in five selected alloys using only compositional descriptors. Most importantly, the multi-element substitution leads to enhanced activation properties compared to pure TiFe, achieving near room-temperature activation behaviour. This work provides a method for on-demand tuning of hydrogen storage and activation properties, which may have broad implications for data-driven discovery of energy storage materials.

Cho, YongJun [Korea Advanced Institute Science and↗