RBM10 regulates the tumorigenic potential of human cancer cells by modulating PPM1B and YBX1 activities.

RNA binding protein RBM10 participates in various RNA metabolism, and its decreased expression or loss of function by mutation has been identified in many human cancers. However, how its dysregulation contributes to human cancer pathogenesis remains to be determined. Here, we found that RBM10 expression was decreased in breast tumors, and breast cancer patients with low RBM10 expression presented poorer survival rates. RBM10 depletion in breast cancer cells significantly promotes the cellular proliferation and migration. We further demonstrated that RBM10 forms a triple complex with YBX1 and phosphatase 1B (PPM1B), in which PPM1B serves as the phosphatase of YBX1. RBM10 knock-down markedly attenuated association between YBX1 and PPM1B, leading to elevated levels of YBX1 phosphorylation and its nuclear translocation. Furthermore, cancer cells with RBM10 depletion had a significantly accelerated tumor growth in nude mice. Importantly, these enhanced tumorigenic phenotypes can be reversed by overexpression of PPM1B. Our findings provide the mechanistic bases for functional loss of RBM10 in promoting tumorigenicity, and are potentially useful in the development of combined therapeutic strategies for cancer patients with defective RBM10.

Decoupling Carrier-Phonon Scattering Boosts the Thermoelectric Performance of n-Type GeTe-Based Materials.

The coupled relationship between carrier and phonon scattering severely limits the thermoelectric performance of n-type GeTe materials. Here, we provide an efficient strategy to enlarge grains and induce vacancy clusters for decoupling carrier-phonon scattering through the annealing optimization of n-type GeTe-based materials. Specifically, boundary migration is used to enlarge grains by optimizing the annealing time, while vacancy clusters are induced through the aggregation of Ge vacancies during annealing. Such enlarged grains can weaken carrier scattering, while vacancy clusters can strengthen phonon scattering, leading to decoupled carrier-phonon scattering. As a result, a ratio between carrier mobility and lattice thermal conductivity of ∼492.8 cm3 V-1 s-1 W-1 K and a peak ZT of ∼0.4 at 473 K are achieved in Ge0.67Pb0.13Bi0.2Te. This work reveals the critical roles of enlarged grains and induced vacancy clusters in decoupling carrier-phonon scattering and demonstrates the viability of fabricating high-performance n-type GeTe materials via annealing optimization.

Piezocatalysis for Chemical-Mechanical Polishing of SiC: Dual Roles of t-BaTiO3 as a Piezocatalyst and an Abrasive.

Chemical mechanical polishing (CMP) offers a promising pathway to smooth third-generation semiconductors. However, it is still a challenge to reduce the use of additional oxidants or/and energy in current CMP processes. Here, a new and green atomically smoothing method: Piezocatalytic-CMP (Piezo-CMP) is reported. Investigation shows that the Piezo-CMP based on tetragonal BaTiO3 (t-BT) can polish the rough surface of a reaction sintering SiC (RS-SiC) to the ultra-smooth surface with an average surface roughness (Ra) of 0.45 nm and the rough surface of a single-crystal 4H-SiC to the atomic planarization Si and C surfaces with Ra of 0.120 and 0.157 nm, respectively. In these processes, t-BT plays a dual role of piezocatalyst and abrasive. That is, it piezo-catalytically generates in-situ active oxygen species to selectively oxidize protruding sites of SiC surface, yielding soft SiO2, and subsequently, it acts as a usual abrasive to mechanically remove these SiO2. This mechanism is further confirmed by density functional theory (DFT) calculation and molecular simulation. In this process, piezocatalytic oxidation is driven only by the original pressure and friction force of a conventional polishing process, thus, the piezo-CMP process do not require any additional oxidant and energy, being a green and effective polishing method.

Predictive model and risk analysis for coronary heart disease in people living with HIV using machine learning.

OBJECTIVE: This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical records (EMRs). METHODS: Sixty-one medical characteristics (including demography information, laboratory measurements, and complicating disease) readily available from EMRs were retained for clinical analysis. These characteristics further aided the development of prediction models by using seven ML algorithms [light gradient-boosting machine (LightGBM), support vector machine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression]. The performance of this model was assessed using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was further applied to interpret the findings of the best-performing model. RESULTS: The LightGBM model exhibited the highest AUC (0.849; 95% CI, 0.814-0.883). Additionally, the SHAP plot per the LightGBM depicted that age, heart failure, hypertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and amylase can help identify PLHIV who were at a high or low risk of developing CHD. CONCLUSION: This study developed a CHD risk prediction model for PLHIV utilizing ML techniques and EMR data. The LightGBM model exhibited improved comprehensive performance and thus had higher reliability in assessing the risk predictors of CHD. Hence, it can potentially facilitate the development of clinical management techniques for PLHIV care in the era of EMRs.

Developing an entrustable professional activity for providing health education and consultation in occupational therapy and examining its validity.

BACKGROUND: Entrustable Professional Activities (EPA)-based assessment is easily and intuitively used in evaluating the learning outcomes of competency-based medical education (CBME). This study aimed to develop an EPA for occupational therapy focused on providing health education and consultation (TP-EPA3) and examine its validity. METHODS: Nineteen occupational therapists who had completed online training on the EQual rubric evaluation participated in this study. An expert committee identified six core EPAs for pediatric occupational therapy. TP-EPA3 was developed following the EPA template and refined through consensus meetings. The EQual rubric, a 14-item, five-point criterion-based anchor system, encompassing discrete units of work (DU), entrustable, essential, and important tasks of the profession (EEIT), and curricular role (CR), was used to evaluate the quality of TP-EPA3. Overall scores below 4.07, or scores for DU, EEIT, and CR domains below 4.17. 4.00, and 4.00, respectively, indicate the need for modifications. RESULTS: The TP-EPA3 demonstrated good validity, surpassing the required cut-off score with an average overall EQual score of 4.21 (SD = 0.41). Specific domain scores for DU, EEIT, and CR were 3.90 (SD = 0.69), 4.46 (SD = 0.44), and 4.42 (SD = 0.45), respectively. Subsequent revisions clarified observation contexts, enhancing specificity and focus. Further validation of the revised TP-EPA3 and a thorough examination of its reliability and validity are needed. CONCLUSION: The successful validation of TP-EPA3 suggests its potential as a valid assessment tool in occupational therapy education, offering a structured approach for developing competency in providing health education and consultation. This process model for EPA development and validation can guide occupational therapists in creating tailored EPAs for diverse specialties and settings.

Horizontal Transport in Ti3C2Tx MXene for Highly Efficient Osmotic Energy Conversion from Saline-Alkali Environments.

Osmotic energy from the ocean has been thoroughly studied, but that from saline-alkali lakes is constrained by the ion-exchange membranes due to the trade-off between permeability and selectivity, stemming from the unfavorable structure of nanoconfined channels, pH tolerance, and chemical stability of the membranes. Inspired by the rapid water transport in xylem conduit structures, we propose a horizontal transport MXene (H-MXene) with ionic sequential transport nanochannels, designed to endure extreme saline-alkali conditions while enhancing ion selectivity and permeability. The H-MXene demonstrates superior ion conductivity of 20.67 S m-1 in 1 M NaCl solution and a diffusion current density of 308 A m-2 at a 10-fold salinity gradient of NaCl solution, significantly outperforming the conventional vertical transport MXene (V-MXene). Both experimental and simulation studies have confirmed that H-MXene represents a novel approach to circumventing the permeability-selectivity trade-off. Moreover, it exhibits efficient ion transport capabilities, addressing the gap in saline-alkali osmotic power generation.

Synergizing Machine Learning Algorithm with Triboelectric Nanogenerators for Advanced Self-Powered Sensing Systems.

The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase the economic burden. The triboelectric nanogenerators (TENGs) provide both an energy harvesting scheme and the possibility of self-powered sensing. Based on contact electrification from different materials, TENGs provide a rich material selection to collect complex and diverse data. As the data collected by TENGs become increasingly numerous and complex, different approaches to machine learning (ML) and deep learning (DL) algorithms have been proposed to efficiently process output signals. In this paper, the latest advances in ML algorithms assisting solid-solid TENG and liquid-solid TENG sensors are reviewed based on the sample size and complexity of the data. The pros and cons of various algorithms are analyzed and application scenarios of various TENG sensing systems are presented. The prospects of synergizing hardware (TENG sensors) with software (ML algorithms) in a complex environment and their main challenges for future developments are discussed.

A novel fluorescent probe for visualizing viscosity changes in lipid droplets during chemotherapy-induced ferroptosis.

BACKGROUND: Ferroptosis, as a novel form of cell death, is becoming one of the hot topics in cancer treatment research. It differs from necrosis and autophagy in that it involves the accumulation of lipid peroxides and is triggered by iron dependency. Recent studies have suggested that this mechanism may alter the viscosity or structure of lipid droplets (LDs). The relationship between LDs viscosity and ferroptosis remains an active area of research with limited reports at present. Additionally, there is a lack of effective anticancer drugs targeting the ferroptosis pathway to promote ferroptosis in tumour cells. Therefore, the development of tools to detect viscosity changes during ferroptosis and targeted therapeutic strategies is of great significance. RESULTS: By coupling 1,3-indandione with naphthalimide, including decamethylamine as a LDs recognition group, we designed and synthesized an environmental fluorescent probe that induces intramolecular charge transfer (TICT) effects. Notably, the diffusion and transport of intracellular substances may be affected in highly viscous environments. Under such conditions, intracellular iron ions may accumulate, leading to peroxide production and cellular damage, which can trigger ferroptosis. Therefore, WD-1 achieved excellent in situ bioimaging of LDs targeting and its viscosity during ferroptosis in HeLa cells and zebrafish. Furthermore, it was observed that WD-1 effectively differentiated between malignant and normal cells during this process, highlighting its potential significance in distinguishing cellular states. In addition, we used the antitumour drug paclitaxel to study ferroptosis in cancer cells. These findings not only provide an excellent tool for the development of the ferroptosis response, but also are crucial for understanding the biological properties of LDs during the ferroptosis response. SIGNIFICANCE AND NOVELTY: Based on a powerful tool of fluorescent probe with in vivo bioimaging, we developed WD-1 to track the impact of paclitaxel on the process of ferroptosis in living cells. Therefore, we preliminarily believe that paclitaxel may affect the occurrence of ferroptosis and control apoptosis in cancer cells. These findings not only serve as an exceptional tool for advancing our understanding of the ferroptosis response, but furthermore play a vital role in comprehending the biological characteristics of LDs in relation to ferroptosis.

Impacts of social deprivation on mortality and protective effects of greenness exposure in Hong Kong, 1999-2018: A spatiotemporal perspective.

Addressing health inequality is crucial for fostering healthy city development. However, there is a dearth of literature simultaneously investigating the effects of social deprivation and greenness exposure on mortality risks, as well as how greenness exposure may mitigate the adverse effect of social deprivation on mortality risks from a spatiotemporal perspective. Drawing on socioeconomic, remote sensing, and mortality record data, this study presents spatiotemporal patterns of social deprivation, population weighted greenness exposure, and all-cause and cause-specific mortality in Hong Kong. A Bayesian regression model was applied to investigate the impacts of social deprivation and greenness exposure on mortality and examine how socioeconomic inequalities in mortality may vary across areas with different greenness levels in Hong Kong from 1999 to 2018. We observed a decline in social deprivation (0.67-0.56), and an increase in greenness exposure (0.34-0.41) in Hong Kong during 1999-2018. Areas with high mortality gradually clustered in the Kowloon Peninsula and the northern regions of Hong Kong Island. Adverse impacts of social deprivation on all-cause mortality weakened in recent years (RR from 2009 to 2013: 1.103, 95%CI: 1.051-1.159, RR from 2014 to 2018: 1.041 95%CI: 0.950-1.139), while the protective impacts of greenness exposure consistently strengthened (RR from 1999 to 2003: 0.903, 95%CI: 0.827-0.984, RR from 2014 to 2018: 0.859, 95%CI: 0.763-0.965). Moreover, the adverse effects of social deprivation on mortality risks were found to be higher in areas with lower greenness exposure. These findings provide evidence of associations between social deprivation, greenness exposure, and mortality risks in Hong Kong over the past decades, and highlight the potential of greenness exposure to mitigate health inequalities. Our study provides valuable implications for policymakers to develop a healthy city.

Ionic Rectification by Dynamic Regulation of the Electric Double Layer at the Hydrogel Interface.

Hydrogels play a pivotal role in the realm of iontronics, contributing to the realization of futuristic human-machine interactions. The electric double layer (EDL) between the hydrogel and electrode provides an essential ionic-electronic coupling interface. While prior investigations primarily delved into elucidating the formation mechanism of the EDL, our study shifts the focus to showcasing the current generation through the mechanical modulation of the EDL at the hydrogel-metal interfaces. The dynamic EDL was constructed by the mechano-driven contact-separation process between the polyacrylamide (PAAm) hydrogel and Au. Influencing factors on the dynamic regulation of the EDL such as ion concentration, types of salt, contact-separation frequency, and deformation degree were investigated. Dehydration usually limits the practical applications of hydrogels, and it is a long-standing and difficult problem. However, it seemed to be able to slow the EDL formation process here, resulting in a sustained continuous direct current signal output. Such hydrogel iontronics could rectify the displacement electronic current of a triboelectric nanogenerator by the ionic current. The directional migration of ions could be further enhanced by using charge-collecting metals with different work functions, for example, Au and Al. It offers a paradigm to enable ionic rectification that could be seamlessly incorporated into electronic systems, ushering in a new era for efficient energy harvesting and biomimetic nervous systems.

Triboiontronics with temporal control of electrical double layer formation.

The nanoscale electrical double layer plays a crucial role in macroscopic ion adsorption and reaction kinetics. In this study, we achieve controllable ion migration by dynamically regulating asymmetric electrical double layer formation. This tailors the ionic-electronic coupling interface, leading to the development of triboiontronics. Controlling the charge-collecting layer coverage on dielectric substrates allows for charge collection and adjustment of the substrate-liquid contact electrification property. By dynamically managing the asymmetric electrical double layer formation between the dielectric substrate and liquids, we develop a direct-current triboiontronic nanogenerator. This nanogenerator produces a transferred charge density of 412.54 mC/m2, significantly exceeding that of current hydrovoltaic technology and conventional triboelectric nanogenerators. Additionally, incorporating redox reactions to the process enhances the peak power and transferred charge density to 38.64 W/m2 and 540.70 mC/m2, respectively.

Landscape of targeted therapies for advanced urothelial carcinoma.

Bladder cancer (BC) is the tenth most common malignancy globally. Urothelial carcinoma (UC) is a major type of BC, and advanced UC (aUC) is associated with poor clinical outcomes and limited survival rates. Current options for aUC treatment mainly include chemotherapy and immunotherapy. These options have moderate efficacy and modest impact on overall survival and thus highlight the need for novel therapeutic approaches. aUC patients harbor a high tumor mutation burden and abundant molecular alterations, which are the basis for targeted therapies. Erdafitinib is currently the only Food and Drug Administration (FDA)-approved targeted therapy for aUC. Many potential targeted therapeutics aiming at other molecular alterations are under investigation. This review summarizes the current understanding of molecular alterations associated with aUC targeted therapy. It also comprehensively discusses the related interventions for treatment in clinical research and the potential of using novel targeted drugs in combination therapy.

RegionSizeR- A Novel App for Regional Sample Size Planning in MRCTs.

In multi-regional clinical trials, planning the sample size for participating regions is essential for the evaluation of the treatment effect consistency across regions. Based on the MRCT design and sample size allocation to regions, consistency probability is usually used to predict the consistent trend between regions and the overall population, while preserving a certain proportion of the overall treatment effect. Specific enrollment characteristics in a region of interest should also be considered during the time of the sample size planning. To facilitate efficient and harmonized regional sample size planning, we have developed RegionSizeR, a comprehensive and user-friendly interactive web-based R shiny application that can be obtained from https://github.com/rsr-ss/RegionSizeR . This simulation-based app can serve as an initial point for discussions on sample size allocation plans, following preservation of treatment effect method in ICH E17. The app accommodates various types of endpoints and designs, including continuous, binary, and time-to-event endpoints, for superiority, non-inferiority, and MCP-Mod designs. To ensure the validity of this app, independent testing is conducted allowing a discrepancy of no more than 1% across all results considering various scenarios.

Altered N-linked glycosylation in depression: A pre-clinical study.

BACKGROUND: Neuroimmune plays an important role in major depressive disorders (MDD). N-linked protein glycosylation (NLG) might contribute to depression by regulating the neuroinflammatory response. As microglia is the main executor of neuroimmune function in the central neural system (CNS), targeting the process of N-linked protein glycosylation of microglia in the mice used for studying depression might potentially offer new avenues for the strategy for MDD. METHODS: The chronic unpredictable mild stress (CUMS) mouse model was established for the whole brain microglia isolating. Then, RNA samples of microglia were extracted for transcriptome sequencing and mRNA analysis. Immunofluorescence (IF) was used to identify the expression level of NLG-related enzyme, B4galt1, in microglia. RESULTS: The data showed that NLG was positively related to depression. Moreover, the NLG-related gene, B4galt1 increased expression in the microglia of CUMS mice. Then, the inhibition of NLG reversed the depressive behavior in CUMS mice. The expression level of B4galt1 in CUMS mice was upregulating following the NLG-inhibitor treatment. Similar results haven't been observed in neurons. Information obtained from these experiments showed increasing expression of B4galt1 in microglia following depressive-like behaviors. CONCLUSIONS: These findings indicate that NLG in microglia is associated with MDD, and suggest that therapeutically targeting NLG might be an effective strategy for depression. LIMITATIONS: How to modulate the B4galt1 or NLG pathways in microglia efficiently and economically request new technologies.

Site-selective sulfur anchoring produces sintering-resistant intermetallic ORR electrocatalysts for membrane electrode assemblies.

Intermetallic compounds are emerging as promising oxygen reduction reaction (ORR) catalysts for fuel cells due to their typically higher activity and durability compared to disordered alloys. However, the preparation of intermetallic catalysts often requires high-temperature annealing, which unfortunately leads to adverse sintering of the metal nanoparticles. Herein, we develop a scalable site-selective sulfur anchoring strategy that effectively suppresses alloy sintering, ensuring the formation of efficient intermetallic electrocatalysts with small sizes and high ordering degrees. The alloy-support interactions are precisely modulated by selectively modifying the alloy-support interfaces with oxidized sulfur species, thus simultaneously blocking both the nanoparticle migration and Oswald ripening pathways for sintering. Using this strategy, sub-5 nm PtCo intermetallic electrocatalysts enclosed by two atomic layers of Pt shells have been successfully prepared even at a metal loading higher than 30 wt%. The intermetallic catalysts exhibit excellent ORR performances in both rotating disk electrode and membrane electrode assembly conditions with a mass activity of 1.28 A mgPt-1 at 0.9 V (vs. RHE) and a power density of 1.0 W cm-2 at a current density of 1.5 A cm-2. The improved performances result from the enhanced Pt-Co electronic interactions and compressive surface strain generated by the highly ordering structure, while the atomic Pt shells prevent the dissolution of Co under highly acidic conditions. This work provides new insights to inhibit the sintering of nanoalloys and would promote the scalable synthesis and applications of platinum-based intermetallic catalysts.

Interaction between RNF4 and SART3 is associated with the risk of schizophrenia.

The pathogenesis of schizophrenia (SCZ) is heavily influenced by genetic factors. Ring finger protein 4 (RNF4) and squamous cell carcinoma antigen recognized by T cells 3 (SART3) are thought to be involved in nervous system growth and development via oxidative stress pathways. Moreover, they have previously been linked to SCZ. Yet the role of RNF4 and SART3 in SCZ remains unclear. Here, we investigated how these two genes are involved in SCZ by studying their variants observed in patients. We first observed significantly elevated mRNA levels of RNF4 and SART3 in the peripheral blood in both first-episode (n = 30) and chronic (n = 30) SCZ patients compared to controls (n = 60). Next, we targeted-sequenced three single nucleotide polymorphisms (SNPs) in SART3 and six SNPs in RNF4 for association with SCZ using the genomic DNA extracted from peripheral blood leukocytes from SCZ participants (n = 392) and controls (n = 572). We observed a combination of SNPs that included rs1203860, rs2282765 (both in RNF4), and rs2287550 (in SART3) was associated with increased risk of SCZ, suggesting common pathogenic mechanisms between these two genes. We then conducted experiments in HEK293T cells to better understand the interaction between RNF4 and SART3. We observed that SART3 lowered the expression of RNF4 through ubiquitination and downregulated the expression of nuclear factor E2-related factor 2 (NRF2), a downstream factor of RNF4, implicating the existence of a possible shared regulatory mechanism for RNF4 and SART3. In conclusion, our study provides evidence that the interaction between RNF4 and SART3 contributes to the risk of SCZ. The findings shed light on the underlying molecular mechanisms of SCZ and may lead to the development of new therapies and interventions for this disorder.

Quantitative health risk assessment of microbial hazards from water sources for community and self-supply drinking water systems.

In low and medium income countries (LMIC) drinking water sources (wells and boreholes) often contain a high number of pathogenic microorganisms, that can pose significant human and environmental health risks. In this study, a quantitative microbial risk assessment approach based on existing literature was conducted to evaluate and compare the quantitative health risks associated with different age groups using various drinking water supply systems. Results showed that both community-supply and self-supply modes exhibit similar levels of risk. However, the self-supply water source consistently showed higher risks compared to the community-supply one. Borehole water was found to be a more suitable option than well water, consistently showing between 5 and 8 lower health risks for E. coli and fecal coliform levels, respectively. The sensitivity analysis further showed the importance of prioritizing the reduction of E. coli concentration in well water and fecal coliform concentration in borehole water. This study offers a fresh perception on quantifying the impact of exposure concentration and age groups, shedding light on how they affect environmental health risks. These findings provide valuable insights for stakeholders involved in the management and protection of water sources.

Ultrafast Dual-Shock Chemistry Synthesis of Ordered/Disordered Hybrid Carbon Anodes: High-Rate Performance of Li-Ion Batteries.

Graphite exhibits crystal anisotropy, which impedes the mass transfer of ion intercalation and extraction processes in Li-ion batteries. Herein, a dual-shock chemical strategy has been developed to synthesize the carbon anode. This approach comprised two key phases: (1) a thermal shock utilizing ultrahigh temperature (3228 K) can thermodynamically facilitate graphitization; (2) a mechanical shock (21.64 MPa) disrupting the π-π interactions in the aromatic chains of carbon can result in hybrid-structured carbon composed of crystalline and amorphous carbon. The optimized carbon (DSC-200-0.3) demonstrates a capacity of 208.61 mAh/g at a 10C rate, with a significant enhancement comparing with 15 mAh/g of the original graphite. Impressively, it maintains 81.06% capacity even after 3000 charge-discharge cycles. Dynamic process analysis reveals that this superior rate performance is attributed to a larger interlayer spacing facilitating ion transport comparing with the original graphite, disordered amorphous carbon for additional lithium storage sites, and crystallized carbon for enhanced charge transfer. The dual-shock chemical approach offers a cost-effective and efficient method to rapidly produce hybrid-structured carbon anodes, enabling 10C fast charging capabilities in lithium-ion batteries.

Simultaneously Boosting Thermoelectric and Mechanical Properties of n-Type Mg3Sb1.5Bi0.5-Based Zintls through Energy-Band and Defect Engineering.

Incorporating donor doping into Mg3Sb1.5Bi0.5 to achieve n-type conductivity is one of the crucial strategies for performance enhancement. In pursuit of higher thermoelectric performance, we herein report co-doping with Te and Y to optimize the thermoelectric properties of Mg3Sb1.5Bi0.5, achieving a peak ZT exceeding 1.7 at 703 K in Y0.01Mg3.19Sb1.5Bi0.47Te0.03. Guided by first-principles calculations for compositional design, we find that Te-doping shifts the Fermi level into the conduction band, resulting in n-type semiconductor behavior, while Y-doping further shifts the Fermi level into the conduction band and reduces the bandgap, leading to enhanced thermoelectric performance with a power factor as high as >20 µW cm-1 K-2. Additionally, through detailed micro/nanostructure characterizations, we discover that Te and Y co-doping induces dense crystal and lattice defects, including local lattice distortions and strains caused by point defects, and densely distributed grain boundaries between nanocrystalline domains. These defects efficiently scatter phonons of various wavelengths, resulting in a low thermal conductivity of 0.83 W m-1 K-1 and ultimately achieving a high ZT. Furthermore, the dense lattice defects induced by co-doping can further strengthen the mechanical performance, which is crucial for its service in devices. This work provides guidance for the composition and structure design of thermoelectric materials.

Approaching Ultimate Synthesis Reaction Rate of Ni-Rich Layered Cathodes for Lithium-Ion Batteries.

Nickel-rich layered oxide LiNixCoyMnzO2 (NCM, x + y + z = 1) is the most promising cathode material for high-energy lithium-ion batteries. However, conventional synthesis methods are limited by the slow heating rate, sluggish reaction dynamics, high energy consumption, and long reaction time. To overcome these challenges, we first employed a high-temperature shock (HTS) strategy for fast synthesis of the NCM, and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time. In the HTS process, ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li- containing oxides is 66.7 (% s-1), that is, taking only 1.5 s. An ultrahigh heating rate leads to fast reaction kinetics, which induces the rapid phase transition of NCM cathodes. The HTS-synthesized nickel-rich layered oxides perform good cycling performances (94% for NCM523, 94% for NCM622, and 80% for NCM811 after 200 cycles at 4.3 V). These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.