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Configuring a carbon substrate with low surface polarity seems very important and significant for accelerating the cathode electrochemical performances of the Lithium-sulfur batteries, which is widely regarded as one of the most promising candidates for the next-generation green energy suppliers. The corn starch-derived carbon with in-situ multi-elements doping, initially carbonized by 6 mol/L H 2 SO 4 and then calcined in nitrogen atmosphere, is employed to configure sulfur cathode for Lithium–Sulfur batteries in this study. As-received carbon with randomly distributed graphical domains serves as charge carriers diffusion channels during discharging/charging cycles, thus endowing the cathode considerable excellent performances. Specifically, the loading amount of sulfur in cathode is around 60.31 wt% and the effective utilization efficiency of active reagent sulfur in cathode is up to 60 %. On activating the cathode at 0.114 A g−1 at 0, 25 and 40 °C, the initial discharge capacities of the Lithium–Sulfur batteries with corn starch-derived carbon-based composite cathode (with ∼1.3 mg cm−2 sulfur) are 278.6, 1023.7 and 976.1 mAh∙g−1, respectively. Accordingly, more uniform, and thinner solid electrolyte interphase membrane formed under room temperature activation, leaving in the dramatically diminished R sur value, contributes to the comparable cycling stability and rate performances of as-designed carbon-based sulfur cathode for Lithium–Sulfur Batteries. [ABSTRACT FROM AUTHOR]

Global trade and travel have facilitated infectious disease transmission. In 2022, over a short time, cross-border Mpox (monkeypox) outbreaks were reported. Since, most countries are at risk of cross-border Mpox transmissions, in this study, we developed a real-time risk assessment model for the cross-border transmission of Mpox. This model includes priori indicators related to the source area before the Mpox outbreak and posterior indicators derived from the quantitative data evaluation afterward. Based on transportation, this model can also be used to assess the global import risk of Mpox for specific countries and cities. European risk values displayed high levels between May and July 2022 and gradually decreased after July. After September 2022, risk values elevated in most countries and regions in the Americas. As for China, high importation risk cities were highly exposed to the United States and moderately exposed to Australia and Germany. Some cities were exposed to the potential risks from only one source country. Dynamic surveillance of the cross-border spread of infectious diseases is essential. Importation risks vary widely across cities and regions, and developing risk prevention and control strategies specific to the traffic flow, medical care capabilities, and risk levels in the main source countries are essential. • We developed a real-time risk assessment model for cross-border transmission of Mpox. • The model integrated posteriori knowledge derived from epidemic data after outbreak. • We considered the impact of high-risk populations on Mpox transmission. • Based on flight data, it can assess import risk for specific countries/cities. • Import risks vary widely across regions/cities, and targeted strategies are needed. [ABSTRACT FROM AUTHOR]

• This paper presents the Survey of AI Methods for Renewable Energy Forecasting. • Taxonomy of AI for solar and wind renewable energy is presented. • Combinations of ML and metaheuristic methods for renewable energy are discussed. • Prospects of improved metaheuristic algorithms for renewable energy forecasting are presented. The efforts to revolutionize electric power generation and produce clean and sustainable electricity have led to the exploration of renewable energy systems (RES). This form of energy is replenished and cost-effective in terms of production and maintenance. However, RES, such as solar and wind energies, is intermittent; this is one of the drawbacks of its usage. In order to overcome this limitation, studies have been undertaken to forecast its availability and power output. The current trending method of forecasting availability and the power generated by the RES is the artificial intelligence (AI) method. However, with all its potential, traditional AI, such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and many more, does not have it all. Because of this, metaheuristic algorithms are being explored as optimization techniques to increase the performance accuracy of these AI forecasting methods and overcome some challenges of traditional AI models. This study presents an insightful survey of AI (traditional AI and metaheuristic) methods explored to forecast the availability of solar and wind renewable energy systems. A survey of the existing surveyed literature was presented. The taxonomy of the explored AI in RES was formulated, and the theoretical backgrounds of some of the traditional AI algorithms were presented. Also, the various forms of metaheuristic algorithms and the improved versions applied to optimize classical AI methods to forecast RES systems' availability and power output were surveyed. A conceptual framework of the hybrid AI application in RES was formulated. Finally, the survey discussion, insight, challenges of the existing models and future directions were presented. [ABSTRACT FROM AUTHOR]

In this study, high-temperature solid-phase techniques are used to prepare pristine and Mg-modified LiNiO 2 cathode materials. Various characterizations are performed to analyze the morphology, structure, and electrical state of the two materials. Electrochemical tests show that Mg doping effectively improves the electrochemical properties of the materials. In particular, the modified sample exhibits a higher specific discharge capacity of 244.5 mA h g−1 than the pristine sample. Moreover, its maximum capacity retention after 304 cycles at 1 C is 54.1%. In situ X-ray powder diffraction imaging reveals that the modified material has better phase-transition reversibility than the pristine material. Density functional theory calculations indicate that Mg-doped Li sites can accelerate Li+ transport. Atomic force microscopy results demonstrate that Mg-doped Li sites act as supportive skeletons that enhance the mechanical properties of the material. Therefore, the proposed strategy for the Mg doping of Li sites can improve the architecture of LiNiO 2 cathode materials. [ABSTRACT FROM AUTHOR]

Success-History-Based Parameter Adaptation Multi-Objective Differential Evolution (SHAMODE) has shown excellent performance recently compared to other multi-objective evolutionary algorithms (MOEAs) and therefore caught the interest of researchers lately. The SHAMODE framework employs historical memory of control parameters, which stores set values of control parameters that have performed well in the past generation and produces new set values of the parameter by directly sampling the parameter space close to one of these stored pairs. Since the algorithm's performance depends on the problem to be optimized, this paper proposes an enhanced version of SHAMODE that is compatible with optimizing the multi-objective wave energy converter problem. The improved version of SHAMODE is achieved by incorporating competing machine learning algorithms, Particle Swarm Optimization, and a modified bubble-net attacking method formula of the Whale optimization algorithm from its original form. Simulations and comparisons are used to verify the proposed method's performance based on some famous multi-objective problem (MOP) benchmark functions. The results reveal that the proposed algorithm performs better than other algorithms that have been recently developed. In addition, the suggested technique is used to optimize the multi-objective wave energy converter model in order to maximize the annual production of electric energy while minimizing the per-unit energy cost. • Machine Learning and PSO based Success-History Based Parameter Adaptation Multi-Objective Differential Evolution algorithm was proposed. • The Improved version of SHAMODE optimized the WEC system to maximize the annual power generated at a minimum Levelized cost of energy. • The Improved version of SHAMODE was applied to optimize the multi-objective wave energy converter model to maximize the annual generated power and minimize the per unit energy cost. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes an improved enhanced differential evolution algorithm for implementing demand response between aggregator and consumer. The proposed algorithm utilizes a secondary population archive, which contains unfit solutions that are discarded by the primary archive of the earlier proposed enhanced differential evolution algorithm. The secondary archive initializes, mutates and recombines candidates in order to improve their fitness and then passes them back to the primary archive for possible selection. The capability of this proposed algorithm is confirmed by comparing its performance with three other well-performing evolutionary algorithms: enhanced differential evolution, multiobjective evolutionary algorithm based on dominance and decomposition, and non-dominated sorting genetic algorithm III. This is achieved by testing the algorithms' ability to optimize a multi-objective optimization problem representing a smart home with demand response aggregator. Shiftable and non-shiftable loads are considered for the smart home which model energy usage profile for a typical household in Johannesburg, South Africa. In this study, renewable sources include battery bank and rooftop photovoltaic panels. Simulation results show that the proposed algorithm is able to optimize energy usage by balancing load scheduling and contribution of renewable sources, while maximizing user comfort and minimizing peak-to-average ratio. Highlights • Evolutionary algorithms play significant role in demand response implementation. • Aggregator-consumer matching via evolutionary algorithms improves mutual benefits. • Two-archive strategy improves mutation and crossover speed in differential evolution. [ABSTRACT FROM AUTHOR]

In recent years, the fate and transport of graphene oxide (GO) has received considerable attention owing to its inevitable release into the natural ecosystem during production and applications, wherein mineral particles and radionuclides are generally co-presented. This paper aimed to clarify the sorption and co-sorption of Eu(III) and GO onto Mg/Al layered double hydroxides (LDH) using batch and extended X-ray absorption fine structure (EXAFS) studies. The results showed that Eu(III) and GO displayed interactively enhancement roles in their co-sorption on LDH. Eu(III) enhanced GO co-sorption on LDH which was mainly due to the formation of “LDH-Eu(III)-GO” ternary surface complexes (i.e., Eu(III)-bridging). While, GO increased Eu(III) co-sorption on LDH which was primarily due to the formation of “LDH-GO-Eu(III)” ternary surface complexes (i.e., GO-bridging). EXAFS fitting results exhibited that the presence of GO could suppress the formation of outer-sphere complexes of Eu(III) on LDH at low pH values, while inhibit the formation of surface precipitates of Eu(III) on LDH at high pH values. The enhanced co-sorption of Eu(III) and GO on LDH as they co-presented might decrease their mobility in the natural environment. These new findings are important to understand the environmental behavior and impact of GO in real ecosystem, and the natural purification of radionuclides in ecological environments. [ABSTRACT FROM AUTHOR]

This study aimed to explore the 1-year temporal change in prevalence, variety, and potential risk factors of long COVID symptoms and to further predict the prognostic trends of long COVID. We searched electronic databases for related studies published from January 2020 to February 2022 and conducted 1-group meta-analysis and locally weighted regression to explore the monthly temporal change in the prevalence of each long COVID symptom in 1-year follow-up period. A total of 137 studies were included in meta-analysis, including 134 093 participants. The temporal change of any long COVID symptom showed a steep decrease initially (from 92% at acute phase to 55% at 1-month follow-up), followed by stabilization at approximately 50% during 1-year follow-up. Six months or more after the acute phase, the odds ratio of population characteristic–related factors increased, such as female (from 1.62 to 1.82), whereas the odds ratio value of acute phase–related factors (severe or critical cases and hospitalization) decreased. As for specific symptoms, approximately two-thirds of the symptoms did not significantly reduce during the 1-year follow-up, and the neuropsychiatric symptoms showed a higher long-term prevalence (approximately 25%) and longer persistence than physical symptoms. The temporal changes in the prevalence and characteristics speculate that long COVID may persist longer than expected. In particular, we should pay more attention to neuropsychiatric symptoms and other symptoms for which there is no significant downward trend in prevalence. The influence of acute phase–related factors for long COVID gradually decreases over time, whereas the influence of population characteristic–related factors gradually increases. [ABSTRACT FROM AUTHOR]

Lithium-rich manganese-based oxides are included in high-capacity cathodes. Herein we introduce a certain amount of Mg and Na into lithium-rich manganese-based oxide microspheres to overcome the weak cycling performance and poor rate capacity. This work uses the hydrothermal method combined with the high-temperature solid-phase method and CH 3 COONa and C 4 H 14 MgO 8 as dopants. Transmission electron microscopy (TEM), X-ray diffraction (XRD), focused ion beam scanning electron microscopy (FIB-SEM), energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and electrochemical characterization are performed to systematically assess the effect of Na and Mg element doping on the morphology, structure and electrochemical characteristics of Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2. The results show that the material has excellent electrochemical performance. These improvements could be related to the presence of Na in Li layers and Mg in TM layers, which can speed up Li-ion diffusion kinetics and improve ionic and electronic conductivity. DFT calculations demonstrate that the injection of Na and Mg reduces the lithium-ion migration barrier energy. This dual-doped modification technique may help researchers better understand how to build high-capacity and stable cathode materials for LIBs. [ABSTRACT FROM AUTHOR]

Understanding how the morphology and microstructure of secondary particles are affected by pH is essential to design spherical and dense hydroxide aggregates as precursors of high-performance cathode materials for lithium-ion batteries. To investigate the interplay between thermodynamic reaction conditions and the physicochemical properties of precursors, a chemical equilibrium model is used to describe the evolution of metal ammonia complexes. Furthermore, the formation and growth of aggregates are studied by monitoring the changes in surface morphologies and crystal structures of precursors at different reaction times. As the pH value varied, two notable phenomena occurred during crystal growth: the fast growth of grains in the early stage as the pH decreased and the layered growth of grains in the later stage with increased pH values. Such findings could be explained from the following two perspectives. First, the decrease in pH causes a significant increase in the complex ion concentration, thereby facilitating the growth of crystals along the [010] direction. Second, an increase in pH generally accelerates deprotonation of the crystal surface, thus strengthening the adsorption of complex ions on the crystal surface and promoting layer-by-layer growth of primary grains along the [001] direction. [Display omitted] • The effect of pH on crystal growth is investigated by modeling and experimental. • The weak hydrogen bonding dominates the adsorption of complexes on (001) facet. • The deprotonation strengthens the adsorption of complexes on crystal surface. [ABSTRACT FROM AUTHOR]

Tartary buckwheat (Fagopyrum tataricum Garetn.), a dicotyledonous herbaceous crop, has good adaptation to low nitrogen (LN) condition. The plasticity of roots drives the adaption of Tartary buckwheat under LN, but the detailed mechanism behind the response of TB roots to LN remains unclear. In this study, the molecular mechanism of two Tartary buckwheat genotypes' roots with contrasting sensitivity in response to LN was investigated by integrating physiological, transcriptome and whole-genome re-sequencing analysis. LN improved primary and lateral root growth of LN-sensitive genotype, whereas the roots of LN-insensitive genotype showed no response to LN. 2, 661 LN-responsive differentially expressed genes (DEGs) were identified by transcriptome analysis. Of these genes, 17 N transport and assimilation-related and 29 hormone biosynthesis and signaling genes showed response to LN, and they may play important role in Tartary buckwheat root development under LN. The flavonoid biosynthetic genes' expression was improved by LN, and their transcriptional regulations mediated by MYB and bHLH were analyzed. 78 transcription factors, 124 small secreted peptides and 38 receptor-like protein kinases encoding genes involved in LN response. 438 genes were differentially expressed between LN-sensitive and LN-insensitive genotypes by comparing their transcriptome, including 176 LN-responsive DEGs. Furthermore, nine key LN-responsive genes with sequence variation were identified, including FtNRT2.4 , FtNPF2.6 and FtMYB1R1. This paper provided useful information on the response and adaptation of Tartary buckwheat root to LN, and the candidate genes for breeding Tartary buckwheat with high N use efficiency were identified. • Nitrogen deficiency improved root growth of low nitrogen (LN)-sensitive genotype. • Flavonoid biosynthetic genes' expression was improved by LN, and their transcriptional regulations were analyzed. • Nine key LN-responsive genes with sequence variation were identified, such as FtNRT2.4 , FtNPF2.6 and FtMYB1R1. [ABSTRACT FROM AUTHOR]

• Explore meteorological impacts based on Köppen-Geiger climate classification. • Examine the control measures for COVID-19 across 189 countries. • Estimate the association between meteorological factor and reproduction number. • Discuss flexible adjustment of China's control protocols. More than 30 months into the novel coronavirus 2019 (COVID-19) pandemic, efforts to bring this prevalence under control have achieved tentative achievements in China. However, the continuing increase in confirmed cases worldwide and the novel variants imply a severe risk of imported viruses. High-intensity non-pharmaceutical interventions (NPIs) are the mainly used measures of China's early response to COVID-19, which enabled effective control in the first wave of the epidemic. However, their efficiency is relatively low across China at the current stage. Therefore, this study focuses on whether measurable meteorological variables be found through global data to learn more about COVID-19 and explore flexible controls. This study first examines the control measures, such as NPIs and vaccination, on COVID-19 transmission across 189 countries, especially in China. Subsequently, we estimate the association between meteorological factors and time-varying reproduction numbers based on the global data by meta-population epidemic model, eliminating the aforementioned anthropogenic factors. According to this study, we find that the basic reproduction number of COVID-19 transmission varied wildly among Köppen-Geiger climate classifications, which is of great significance for the flexible adjustment of China's control protocols. We obtain that in southeast China, Köppen-Geiger climate sub-classifications, Cwb, Cfa, and Cfb, are more likely to spread COVID-19. In August, the R SIM of Cwb climate subclassification is about three times that of Dwc in April, which implies that the intensity of control efforts in different sub-regions may differ three times under the same imported risk. However, BSk and BWk, the most widely distributed in northwest China, have smaller basic reproduction numbers than Cfa, distributed in southeast coastal areas. It indicates that northwest China's control intensity could be appropriately weaker than southeast China under the same prevention objectives. [ABSTRACT FROM AUTHOR]

Enhancing the kinetic performance of thick electrodes is essential for improving the efficiency of lithium extraction processes. Biochar, known for its affordability and unique three-dimensional (3D) structure, is utilized across various applications. In this study, we developed a biochar-based, 3D-conductive network thick electrode (∼20 mg cm−2) by in-situ deposition of LiFePO 4 (LFP) onto watermelon peel biomass (WB). Utilizing Density Functional Theory (DFT) calculations complemented by experimental data, we confirmed that this The thick electrode exhibits outstanding kinetic properties and a high capacity for lithium intercalation in brines, even in environments where the Magnesia-lithium ratios are significantly high. The electrode showed an impressive intercalation capacity of 30.67 mg g−1 within 10 min in a pure lithium solution. It also maintained high intercalation performance (31.17 mg g−1) in simulated brines with high Magnesia-lithium ratios. Moreover, in actual brine, it demonstrated a significant extraction capacity (23.87 mg g−1), effectively lowering the Magnesia-lithium ratio from 65 to 0.50. This breakthrough in high-conductivity thick electrode design offers new perspectives for lithium extraction technologies. The watermelon peel serves as the substrate, simultaneously supporting the in-situ loading of LFP, thereby forming an LFP/WB thick electrode exhibits high lithium absorption capacity and excellent kinetic performance in high Mg2+/Li+ ratio brine. It achieved an impressive absorption rate of 30.67 mg g−1·min−1 in 10 min and an average lithium extraction of 23.87 mg g−1 from salt lake brine. This approach effectively reduced the Mg2+/Li+ ratio from 65 to 0.50, enabling efficient lithium separation and comprehensive biological resource utilization. [Display omitted] • The comprehensive utilization of biological resources is achieved. • The low efficiency of Li + extraction with thick electrode is effectively solved. • Effectively reducing the Mg2+/Li+ ratio in low-grade brine. [ABSTRACT FROM AUTHOR]

Students' actions in the classroom play a key role in their studying performance in class. This study focuses on the automatic recognition of students' spontaneous actions in a real classroom environment. A database of students' spontaneous actions is first established in this study. Our database consists of 4917 images of students' spontaneous actions, including the actions of students in 10 learning states. Based on the characteristics of students' actions in the classroom, we proposed a new 11-layer convolutional neural network algorithm based on an enhanced deep super resolution network. In this algorithm, a data augmentation method is introduced for data processing. The experimental results show that the proposed algorithm effectively improved the accuracy of action recognition on the database established in this paper. Such a spontaneous database proposed in this paper provides good data support for the study of students' actions in the classroom. [ABSTRACT FROM AUTHOR]

Layered high-nickel LiNi 0.8 Co 0.1 Mn 0.1 O 2 is a promising candidate of the next generation cathode materials for lithium-ion batteries. However, severe cycling instability and fast capacity drop induced by anisotropic structured change restrict its wide application. To address these defects, the structure design of cathodes is conducted. Herein, a hierarchical layered LiNi 0.8 Co 0.1 Mn 0.1 O 2 cathode consisting of orderly stacking hexagonal nanosheets with exposed active {104} facets is successfully synthesized by an improved co-precipitation process and followed with a high temperature lithiation reaction. Benefiting from this unique texture, exposed active {104} facets with lower surface energy supply 3D barrier-free Li+ ion diffusion channels, significantly improving the efficiency of the Li+ diffusion. Moreover, the consistent arrangement of nanosheets in the manner of the {001} facets close attachment is beneficial to alleviate the stress caused by the anisotropic structured change. Thus, this cathode material presents both superior reversible capability (203.8 mAh g−1 at 0.1C, 184.5 mAh g−1 at 1 C, 173.0 mAh g−1 at 5 C and 161.3 mAh g−1 at 10 C) and stable cycling performance (capacity retention of 89.3% after 100 cycles at 1 C, 55.3% after 300 cycles at 5 C and 59.6% after 300 cycles at 10 C). Schematic of single crystal shape evolution of the cathode materials and the corresponding cycle performance of the NCM-3 sample at different rates. [Display omitted] • A hierarchical cathode material consisting of orderly stacking nanosheets with exposed active {104} facets was successfully synthesized. • The exposed active {104} facets with lower surface energy could supply barrier-free Li+ ion diffusion channels. • The consistent arrangement of nanosheets is beneficial to alleviate the stress and inhibit the pulverization of secondary particles. • The hierarchical cathode material presents both superior reversible capability and stable cycling performance. [ABSTRACT FROM AUTHOR]

Low-cost salt hydrate eutectic phase change materials (EPCMs) are attracting increasing attentions and have shown good application prospects for medium-temperature solar thermal energy storage. Water control during sample preparation, supercooling inhibition, and cycle stability are crucial to ensure the thermal reliability of salt hydrate PCM-based thermal energy storage systems. In this study, a "differential scanning calorimeter (DSC) monitoring system evolution process" is developed to prepare MgCl 2 ·6H 2 O and Mg-EPCM [MgCl 2 ·6H 2 O (43.0 wt%)-Mg(NO 3) 2 ·6H 2 O (57.0 wt%)], in which unpurified industrial bischofite is used as a precursor. Melting enthalpy of the prepared MgCl 2 ·6H 2 O can be raised from 125.6 to 164.2 J/g, which is higher than that of recrystallized MgCl 2 ·6H 2 O and comparable to those of guaranteed reagent (GR), 3 N (purity: 99.9%), and 4 N (purity: 99.99%) MgCl 2 ·6H 2 O. Furthermore, melting enthalpy of the prepared Mg-EPCM was improved by approximately 10%, from 126 to 140.1 J/g. The latent heat storage capacity is mainly affected by the preparation method, rather than by the small amounts of impurity elements arising from the precursor (impurity rate: ≤ 0.4%). Moreover, 0.5% Sr(OH) 2 ·8H 2 O has inhibited the supercooling degree of Mg-EPCM within 1.0 °C, with a melting enthalpy of 139.5 J/g. It is found that Sr(OH) 2 ·8H 2 O participates in eutectic formation and simultaneously nucleates the system to inhibit supercooling. Thermal cycle testing shows that there is almost no significant degradation after 500 thermal cycles. The low-cost Mg-EPCM developed here exhibits an excellent latent heat capacity and inhibits supercooling, showing great practical potential for latent heat storage systems. • A "DSC monitoring system evolution process" was proposed to prepare salt hydrate PCM. • Melting enthalpy of the prepared MgCl 2 ·6H 2 O was comparable to that of 4 N sample. • Latent heat storage capacity of the prepared Mg-EPCM was improved by ∼10%. • Melting enthalpy is affected by the preparation method, rather than by impurities. • Sr(OH) 2 ·8H 2 O participates in eutectic formation and simultaneously nucleates it. [ABSTRACT FROM AUTHOR]

• Commercial multi-walled carbon nanotubes (MWCNTs) were activated under ultrasonic treatment with nitric acid in one step. • The usage of only 700 ppm activated MWCNTs catalyst increases MEA-based CO 2 desorption amount by 48.49 % and desorption rate by as high as 338.50 %. • The activated MWCNTs catalyst and MEA solution show outstanding stabilities within 20 cyclic CO 2 sorption and desorption tests. Organic amine solution is currently the most commonly used chemical absorbent for carbon dioxide (CO 2) capture, but its drawback such as high energy consumption for regeneration of CO 2 loaded solution has seriously hindered its wide application in industry. Development of catalysts could reduce the regeneration energy consumption of the process. In this study, the catalytic effects of raw multi-walled carbon nanotubes (MWCNTs) and acid-treated MWCNTs in 30 wt% monoethanolamine solution on both absorption and desorption procedures were investigated. The results showed that the addition of raw MWCNTs and acid-treated MWCNTs as catalysts both promoted the CO 2 desorption rate and amount, among which the 700 ppm acid-treated MWCNTs increased the CO 2 desorption amount by 48.49 %. Furthermore, both MWCNTs shortened the desorption time of CO 2 as well. Stability of acid-treated MWCNTs has been examined by 20 cycles in the capture system. Characterization results indicate that the acid treatment increased the surface area of MWCNTs, and created more acid sites on their surfaces through the defected area. Both characteristics contribute to the enhanced CO 2 desorption performance. Therefore, acid-treated MWCNTs can be considered as promising catalysts for promoting CO 2 desorption and reducing energy consumption for CO 2 capture. [ABSTRACT FROM AUTHOR]

Carbon spheres, prepared by hydrothermally treating fresh potato starch, is employed as the sulfur host to configure a high-performance cathode substrate candidate for Li–S batteries. As confirmed by experimental results, both the improved the rate and cycle performances of Li–S batteries cathode with gradient sulfur immobilization, are mainly attributed to the confining, adsorption and conduction multi-functions of as-prepared carbon spheres toward polysulfides. Specifically, on starting the discharging/charging cycles, the active material α-S 8 is irreversibly converted to polysulfides and then transformed between β-S 8 and polysulfides during the next charge/discharge cycles. After initialization at 0.1C for 3 cycles, the initial reversible discharge capacities of the Li–S batteries cathode with optimized sulfur amount are 1072.5, 831.3, 780.4, 726.8, 714.3, 702.7 mAh g−1 sulfur at 0.1, 0.5, 1, 2, 3 and 4 C, which is superior to those of the most previously reported reports. Besides that, as-designed potato-derived carbon based composite cathodes exhibits remarkable rate performance and cycling stability even at wide temperature ranging from −40 to 60 °C, which evidently supports the dominant role of as-prepared 3D carbon spheres in boosting the cathode performance for Li–S batteries. [ABSTRACT FROM AUTHOR]

Abstract: Repeatable and accurate assembly of thin, foil optics is crucial to meeting performance goals in optical systems such as grazing-incidence X-ray telescopes and diffractive lithography tools. Our previous work in proving key technologies for assembly has been motivated by the need to meet spectral resolution goals for the NASA Constellation-X mission. We report a new generation of technology that makes strides towards simulating actual telescope assembly conditions. Our technology is based on the use of micromachined silicon tooling that we call microcombs. Theoretical error budgeting and analytical models were applied to a mechanical design with an isolated metrology frame and high-resolution actuation with feedback. Experimental testing has yielded assembly results with sub-micron repeatability and accuracy. For complete foil reassembly, placement errors are approximately 0.3  m over a 140 mm 100 mm 0.4 mm foil. Accuracy of assembly in pitch and yaw are 0.34 and 2.01  m, respectively. This performance meets the 1  m telescope assembly accuracy goal with the exception of yaw accuracy, which is under continued development. [Copyright &y& Elsevier]

Halohydrin dehalogenase from Agrobacterium radiobacter AD1 (HheC) is a key enzyme in preparing β-substituted alcohols and optically pure epoxides. However, the weak thermostability of HheC greatly limits its industrial application and needs to be improved. In this study, a combinatorial smart library was constructed and screened for enhancing the thermostability of HheC. Mutation sites Lys203 and Lys204 located at the protein surface were selected and simultaneously randomized with charged amino acids (Arg, Asp, Glu, Lys), resulting in a combinatorial smart library. After screening a total of only 48 clones, three positive variants CSL1 (Lys203Arg), CSL2 (Lys204Arg) and CSL3 (Lys203Arg/Lys204Arg) were obtained. Compared to the wild type HheC, variant CSL2 exhibited an increase in thermal stability with a nearly 6.9-fold improvement of half-life (τ 1/2, 55°C) at 55 °C without compromising catalytic activity. In addition, the double mutant CSL3 displayed approximately 3.4-fold higher τ 1/2, 55°C value and 1.8-fold higher k cat value toward 1,3-dicholoro-2-propanol (1,3-DCP) than that of the wild-type HheC. Homology modeling analysis highlights that the newly gained hydrogen bonds and optimizing charge-charge interactions at the protein surface might contribute to the overall conformational stabilization, leading to improving the thermostability of HheC. • A combinatorial smart library was constructed for improving thermostability of HheC. • After screening a total of only 48 clones, three positive variants were obtained. • CSL2 and CSL3 show 6.9- and 3.4-fold higher half-life values than that of HheC. • CSL1 and CSL3 exhibit 1.6- and 1.8-fold higher k cat values as compare to HheC. [ABSTRACT FROM AUTHOR]

Abstract In this study, we have successfully coated the CeO 2 nanoparticles (CeONPs) layer onto the surface of the Ni-rich layered LiNi 0.7 Co 0.2 Mn 0.1 O 2 cathode materials by a wet chemical method, which can effectively improve the structural stability of electrode. The X-ray powder diffraction (XRD), transmission electron microscope (TEM), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS) are used to determine the structure, morphology, elemental composition and electronic state of pristine and surface modified LiNi 0.7 Co 0.2 Mn 0.1 O 2. The electrochemical testing indicates that the 0.3 mol% CeO 2 -coated LiNi 0.7 Co 0.2 Mn 0.1 O 2 demonstrates excellent cycling capability and rate performance, the discharge specific capacity is 161.7 mA h g−1 with the capacity retention of 86.42% after 100 cycles at a current rate of 0.5 C, compared to 135.7 mA h g−1 and 70.64% for bare LiNi 0.7 Co 0.2 Mn 0.1 O 2 , respectively. Even at 5 C, the discharge specific capacity is still up to 137.1 mA h g−1 with the capacity retention of 69.0%, while the NCM only delivers 95.5 mA h g−1 with the capacity retention of 46.6%. The outstanding electrochemical performance is assigned to the excellent oxidation capacity of CeO 2 which can oxidize Ni2+ to Ni3+ and Mn3+ to Mn4+ with the result that suppress the occurrence of Li+/Ni2+ mixing and phase transmission. Furthermore, CeO 2 coating layer can protect the structure to avoid the occurrence of side reaction. The CeO 2 -coated composite with enhanced structural stability, cycling capability and rate performance is a promising cathode material candidate for lithium-ion battery. [ABSTRACT FROM AUTHOR]