Rational synthesis and structural engineering of two-dimensional inorganic nanosheets for electrochemical energy storage

Lithium-ion batteries have dominated the portable electronics industry and solid-state electrochemical R&D for the past two decades due to the relatively high energy density. However, the limited lithium resources and their non-uniform distribution are becoming big concerns. Therefore, exploring high-performance, safe rechargeable batteries based on abundant resources is urgent. Sodium-ion batteries are of great interest as a potentially low-cost and safe alternative to the prevailing lithium-ion battery technology owing to the high abundance of sodium in earth crust, even distribution in nature and its favorable redox potential (only ~0.3 V above that of lithium). Figures of merit for future SIBs call for a breakthrough in energy (>200 Wh kg⁻¹) and power density (>2000 W kg⁻¹) as well as the cycle life (>4000 cycles) by designing new electrode structures, materials engineering and identifying new chemistries, to satisfy the requirements of many potential applications ranging from ubiquitous portable electronics to grid energy storage. Two-dimensional (2D) inorganic nanosheets offer exciting opportunities for fundamental studies and many technological applications due to their unique and fascinating physical and chemical properties. Preparation of 2D materials via exfoliation/delamination from intrinsically layered materials has been greatly limited by the categories of materials with such suitably layered host crystals. It is critically challenging to obtain 2D nanocrystals from the materials of non-layered structures. This dissertation focuses on the rational synthesis and structural engineering of 2D inorganic nanosheets for high-performance electrochemical energy storage. Several 2D energy materials, such as MnO₂, LiFePO₄, VOPO₄ nanosheets, for electrochemical energy storage are presented. The synthesis and characterizations of these 2D energy materials are discussed in details. Their electrochemical characteristics for H⁺, Li⁺ and Na⁺ storage and the corresponding energy storage mechanisms are also investigated for each case. 2D energy materials have proven effective in constructing kinetically favorable ion channels, but the irreversible restacking of the individual 2D nanosheets during materials processing or device fabrication may lead to the decrease of active sites for ion storage and the sluggish ion transport. To address this issue, two possible strategies are developed in this dissertation to improve the ion transport in 2D nanomaterials. One possible strategy is to increase the interlayer spacing to facilitate ion transport by creating a lower energy barrier for ion transport through the interlayer space. A general interlayer-engineering strategy to improve the sodium-ion transport in VOPO₄ nanosheets via organic molecules intercalation is presented in Chapter 5. Another strategy is to make porous/holey materials to facilitate the ion transport. Chapter 6 summarizes the porosity engineering of 2D transition metal oxide nanosheets for improved rate capability and cycling stability for both lithium and sodium-ion storage. Rational synthesis and structural engineering of 2D inorganic nanosheets has allowed us to make progress on (i) understanding the materials chemistry of 2D energy materials for electrochemical energy storage, (ii) developing promising strategies to address the key problems in 2D nanomaterials for energy-related applications, and (iii) fabricating high-performance lithium- and sodium-ion batteries for the next generationMechanical Engineerin

Nanostructured Conductive Polymers for Advanced Energy Storage

Conductive polymers combine the attractive properties associated with conventional polymers and unique electronic properties of metals or semiconductors. Recently, nanostructured conductive polymers have aroused considerable research interest owing to their unique properties over their bulk counterparts, such as large surface areas and shortened pathways for charge/mass transport, which make them promising candidates for broad applications in energy conversion and storage, sensors, actuators, and biomedical devices. Numerous synthetic strategies have been developed to obtain various conductive polymer nanostructures, and high-performance devices based on these nanostructured conductive polymers have been realized. This Tutorial review describes the synthesis and characteristics of different conductive polymer nanostructures; presents the representative applications of nanostructured conductive polymers as active electrode materials for electrochemical capacitors and lithium-ion batteries and new perspectives of functional materials for next-generation high-energy batteries, meanwhile discusses the general design rules, advantages, and limitations of nanostructured conductive polymers in the energy storage field; and provides new insights into future directions.University of Texas at Austin3M Non-tenured Faculty awardWelch Foundation F-1861Materials Science and Engineerin

Case Report: A rare case of multicentric angiosarcomas of bone mimicking multiple myeloma on 18F-FDG PET/CT

BackgroundAngiosarcoma, a rare endothelial-origin tumor, can develop throughout the body, with the head and neck skin being the most commonly affected areas. It can also originate in other sites such as the breast, iliac artery, and visceral organs including the liver, spleen, and kidneys. Angiosarcoma of the bone is remarkably rare, presenting as either unifocal or multifocal bone lesions and often leading to a grim prognosis. Diagnosing bone angiosarcoma poses a significant challenge. 18F-FDG PET/CT serves as a reliable and indispensable imaging modality for evaluating distant metastases and clinically staging angiosarcomas.Case reportA 57-year-old woman presented with a 10-day history of dizziness and headaches. Cranial CT scan revealed bone destruction of the parietal bone, accompanied by soft tissue lesions, protruding into the epidural space. MRI examination demonstrated lesions with slightly elevated signal intensity on T2FLAIR, showing moderate enhancement. Furthermore, multiple foci were observed within the T12, L1-5, and S1-2 vertebrae, as well as in the bilateral iliac bones. For staging, 18F-FDG PET/CT was performed. The MIP PET showed multifocal FDG-avid lesions in the sternum, bilateral clavicles, bilateral scapulae, multiple ribs, and pelvic bones. Heterogeneous FDG uptake was observed in multiple bone lesions, including intracranial (SUVmax = 11.3), right transverse process of the T10 vertebra (SUVmax = 5.8), ilium (SUVmax = 3.3), and pubis (SUVmax = 4.7). The patient underwent surgical resection of the cranial lesion. The pathological diagnosis was made with a highly differentiated angiosarcoma.ConclusionAngiosarcoma of bone on FDG PET/CT scans is characterized by abnormal FDG uptake along with osteolytic destruction. This case highlights that angiosarcoma of bone can manifest as multicentric FDG uptake, resembling the pattern seen in multiple myeloma. FDG PET/CT can be a useful tool for staging this rare malignant tumor, offering the potential to guide biopsy procedures toward the most metabolically active site. And it should be considered in the differential diagnosis of multiple osteolytic lesions, including metastatic carcinoma, multiple myeloma, and lymphoma of bone

A Chemistry and Material Perspective On Lithium Redox Flow Batteries Towards High-Density Electrical Energy Storage

Electrical energy storage system such as secondary batteries is the principle power source for portable electronics, electric vehicles and stationary energy storage. As an emerging battery technology, Li-redox flow batteries inherit the advantageous features of modular design of conventional redox flow batteries and high voltage and energy efficiency of Li-ion batteries, showing great promise as efficient electrical energy storage system in transportation, commercial, and residential applications. The chemistry of lithium redox flow batteries with aqueous or non-aqueous electrolyte enables widened electrochemical potential window thus may provide much greater energy density and efficiency than conventional redox flow batteries based on proton chemistry. This Review summarizes the design rationale, fundamentals and characterization of Li-redox flow batteries from a chemistry and material perspective, with particular emphasis on the new chemistries and materials. The latest advances and associated challenges/opportunities are comprehensively discussed.Zhao, Yu, Yu Ding, Yutao Li, Lele Peng, Hye Ryung Byon, John B. Goodenough, and Guihua Yu. "A chemistry and material perspective on lithium redox flow batteries towards high-density electrical energy storage." Chemical Society Reviews 44, no. 22 (Nov., 2015): 7968-7996.Materials Science and Engineerin

Charge redistribution, charge order and plasmon in La2−x_{2-x}Srx_{x}CuO4_{4}/La2_{2}CuO4_{4} superlattices

Interfacial superconductors have the potential to revolutionize electronics, quantum computing, and fundamental physics due to their enhanced superconducting properties and ability to create new types of superconductors. The emergence of superconductivity at the interface of La$_{2-x}$Sr$_{x}$CuO$_{4}$/La$_{2}$CuO$_{4}$ (LSCO/LCO), with a T$_c$ enhancement of $\sim$ 10 K compared to the La$_{2-x}$Sr$_{x}$CuO$_{4}$ bulk single crystals, provides an exciting opportunity to study quantum phenomena in reduced dimensions. To investigate the carrier distribution and excitations in interfacial superconductors, we combine O K-edge resonant inelastic X-ray scattering and atomic-resolved scanning transmission electron microscopy measurements to study La$_{2-x}$Sr$_{x}$CuO$_{4}$/La$_{2}$CuO$_{4}$ superlattices (x=0.15, 0.45) and bulk La$_{1.55}$Sr$_{0.45}$CuO$_{4}$ films. We find direct evidence of charge redistribution, charge order and plasmon in LSCO/LCO superlattices. Notably, the observed behaviors of charge order and plasmon deviate from the anticipated properties of individual constituents or the average doping level of the superlattice. Instead, they conform harmoniously to the effective doping, a critical parameter governed by the T$_c$ of interfacial superconductors.Comment: 8 pages, 5 figure

A local mesh refinement approach for large-eddy simulations of turbulent flows

In this paper, a local mesh refinement (LMR) scheme on Cartesian grids for large-eddy simulations is presented. The approach improves the calculation of ghost cell pressures and velocities and combines LMR with high-order interpolation schemes at the LMR interface and throughout the rest of the computational domain to ensure smooth and accurate transition of variables between grids of different resolution. The approach is validated for turbulent channel flow and flow over a matrix of wall-mounted cubes for which reliable numerical and experimental data are available. Comparisons of predicted first-order and second-order turbulence statistics with the validation data demonstrated a convincing agreement. Importantly, it is shown that mean streamwise velocities and fluctuating turbulence quantities transition smoothly across coarse-to-fine and fine-to-coarse interfaces

Spatiotemporal heterogeneity and impact factors of hepatitis B and C in China from 2010 to 2018: Bayesian space–time hierarchy model

IntroductionViral hepatitis is a global public health problem, and China still faces great challenges to achieve the WHO goal of eliminating hepatitis.MethodsThis study focused on hepatitis B and C, aiming to explore the long-term spatiotemporal heterogeneity of hepatitis B and C incidence in China from 2010 to 2018 and quantify the impact of socioeconomic factors on their risk through Bayesian spatiotemporal hierarchical model.ResultsThe results showed that the risk of hepatitis B and C had significant spatial and temporal heterogeneity. The risk of hepatitis B showed a slow downward trend, and the high-risk provinces were mainly distributed in the southeast and northwest regions, while the risk of hepatitis C had a clear growth trend, and the high-risk provinces were mainly distributed in the northern region. In addition, for hepatitis B, illiteracy and hepatitis C prevalence were the main contributing factors, while GDP per capita, illiteracy rate and hepatitis B prevalence were the main contributing factors to hepatitis C.DisussionThis study analyzed the spatial and temporal heterogeneity of hepatitis B and C and their contributing factors, which can serve as a basis for monitoring efforts. Meanwhile, the data provided by this study will contribute to the effective allocation of resources to eliminate viral hepatitis and the design of interventions at the provincial level

Prediction of Deleterious Non-Synonymous SNPs Based on Protein Interaction Network and Hybrid Properties

Non-synonymous SNPs (nsSNPs), also known as Single Amino acid Polymorphisms (SAPs) account for the majority of human inherited diseases. It is important to distinguish the deleterious SAPs from neutral ones. Most traditional computational methods to classify SAPs are based on sequential or structural features. However, these features cannot fully explain the association between a SAP and the observed pathophysiological phenotype. We believe the better rationale for deleterious SAP prediction should be: If a SAP lies in the protein with important functions and it can change the protein sequence and structure severely, it is more likely related to disease. So we established a method to predict deleterious SAPs based on both protein interaction network and traditional hybrid properties. Each SAP is represented by 472 features that include sequential features, structural features and network features. Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection (IFS) were applied to obtain the optimal feature set and the prediction model was Nearest Neighbor Algorithm (NNA). In jackknife cross-validation, 83.27% of SAPs were correctly predicted when the optimized 263 features were used. The optimized predictor with 263 features was also tested in an independent dataset and the accuracy was still 80.00%. In contrast, SIFT, a widely used predictor of deleterious SAPs based on sequential features, has a prediction accuracy of 71.05% on the same dataset. In our study, network features were found to be most important for accurate prediction and can significantly improve the prediction performance. Our results suggest that the protein interaction context could provide important clues to help better illustrate SAP's functional association. This research will facilitate the post genome-wide association studies

Cooperativity among Short Amyloid Stretches in Long Amyloidogenic Sequences

Amyloid fibrillar aggregates of polypeptides are associated with many neurodegenerative diseases. Short peptide segments in protein sequences may trigger aggregation. Identifying these stretches and examining their behavior in longer protein segments is critical for understanding these diseases and obtaining potential therapies. In this study, we combined machine learning and structure-based energy evaluation to examine and predict amyloidogenic segments. Our feature selection method discovered that windows consisting of long amino acid segments of ∼30 residues, instead of the commonly used short hexapeptides, provided the highest accuracy. Weighted contributions of an amino acid at each position in a 27 residue window revealed three cooperative regions of short stretch, resemble the β-strand-turn-β-strand motif in A-βpeptide amyloid and β-solenoid structure of HET-s(218–289) prion (C). Using an in-house energy evaluation algorithm, the interaction energy between two short stretches in long segment is computed and incorporated as an additional feature. The algorithm successfully predicted and classified amyloid segments with an overall accuracy of 75%. Our study revealed that genome-wide amyloid segments are not only dependent on short high propensity stretches, but also on nearby residues