All-climate aqueous supercapacitor enabled by a deep eutectic solvent electrolyte based on salt hydrate

Aqueous supercapacitors(SCs)have received considerable attention owing to the utilization of low-cost,non-flammable,and low-toxicity aqueous electrolytes thus could eliminate the safety and cost concerns,but their wide temperature range applications have generally suffered from frozen of electrolyte and insufficient ionic conductivity at low temperatures.Herein,we demonstrate the feasibility of using an unconventional Deep Eutectic Solvent(DES)based on H2O-Mg(ClO4)2·6 H2O binary system as electrolyte to construct all-climate aqueous carbon-based SC.This unconventional class DES completely base on inorganic substances and achieving simply mix inexpensive salts and water together at the right proportions.Attributed to the attractive feature of extremely low freeze temperature of-69℃,this electrolyte can enable the 1.8 V carbon-based SC to fully work at-40℃with outstanding cycling stability.This DES electrolyte comprising of a single salt and a single solvent without any additive will open up an avenue for developing simple and green electrolytes to construct all-climate SC.

Particle breakage of sand subjected to friction and collision in drum tests

This paper presents a laboratory experimental study on particle breakage of sand subjected to friction and collision,by a number of drum tests on granular materials(silica sand No.3 and ceramic balls)to investigate the characteristics of particle breakage and its effect on the characteristics of grain size distribution of sand.Particle breakage increased in up convexity with increasing duration of drum tests,but increased linearly with increasing number of balls.Particle breakage showed an increase,followed by a decrease while increasing the amount of sand.There may be existence of a characteristic amount of sand causing a maximum particle breakage.Friction tests caused much less particle breakage than collision tests did.Friction and collision resulted in different mechanisms of particle breakage,mainly by abrasion for friction and by splitting for collision.The fines content increased with increasing relative breakage.Particle breakage in the friction tests(abrasion)resulted in a sharper increase but with a smaller total amount of fines content in comparison with that in the collision tests(splitting).For the collision tests,the fines content showed a decrease followed by an increase as the amount of sand increased,whereas it increased in up convexity with increasing number of balls.The characteristic grain sizes D_(10) and D_(30) decreased in down convexity with increasing relative breakage,which could be described by a natural exponential function.However,the characteristic grain sizes D50 and D60 decreased linearly while increasing the relative breakage.In addition,the coefficients of uniformity and curvature of sand showed an increase followed by a decrease while increasing the relative breakage.

Virtual screening,molecular docking and identification of umami peptides derived from Oncorhynchus mykiss

Oncorhynchus mykiss is delicious and contains abundant flavor substances.However,few studies focused on umami peptides of O.mykiss.In the current work,umami peptides derived from O.mykiss were identified using virtual screening,molecular docking,and electronic tongue analysis.First,the O.mykiss protein was hydrolyzed using the PeptideCutter online enzymolysis program.Subsequently,water-soluble and toxicity screening were performed by Innovagen and ToxinPred software,respectively.The potential peptides were docked with umami receptor T1R1/T1R3.Furthermore,taste properties of potential peptides were validated by electronic tongue.Docking results suggested that the three tetrapeptide EANK,EEAK,and EMQK could enter the binding pocket in the T1R1 cavity,wherein Arg151,Asp147,Gln52,and Arg277 may play key roles in the production of umami taste.Electronic tongue results showed that the umami value of EANK,EEAK,and EMQK were stronger than monosodium glutamate.This work provides a new insight for the screening of umami peptides in O.mykiss.

Insights into some large-scale landslides in southeastern margin of Qinghai-Tibet Plateau

The southeastern margin of Qinghai-Tibet Plateau(SMQTP)is of a typical large landslide-prone area due to intense tectonic activity,deeply incised valleys,high geostress and frequent earthquakes.To gain insights into large landslides in southeastern margin of Qinghai-Tibet Plateau,an area covering 3.34×105 km2 that extends 80e150 km on both sides of the Sichuan-Tibet traffic corridors(G318)was used to examine the spatial distribution and corresponding characteristics of landslides.The results showed that the study area contains at least 629 large landslides that are mainly concentrated on 7 zones(zones IeVII).Zones IeVII are in the southern section of the Longmenshan fault zone(with no large river)and sections with Dadu River,Jinsha River,Lancang River,Nujiang River and Yarlung Zangbo River.There are more landslides in the Jinsha River section(totaling 186 landslides)than the other sections.According to the updated Varnes classification,408 large landslides(64.9%)were recognized and divided into 4 major types,i.e.flows(275 cases),slides(58 cases),topples(44 cases)and slope deformations(31 cases).Flows,which consist of rock avalanches and iceerock avalanches,are the most common landslide type.Large landslide triggers(178 events,28.3%)are also recognized,and earthquakes may be the most common trigger.Due to the limited data,these landslide type classifications and landslide triggers are perhaps immature,and further systematic analysis is needed.

Economic Risk Assessment of Future Debris Flows by Machine Learning Method

A reliable economic risk map is critical for effective debris-flow mitigation.However,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its application.To estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability map.We selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every year.The debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual susceptibility.We employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate susceptibilities.Simultaneously,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical results.Additionally,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and farmland.The economic loss of elements at risk was calculated based on physical vulnerabilities and their economic values.Therefore,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow channels.In this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on buildings.The results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire risk.These findings can provide a scientific support for the effective mitigation of future debris flows.

Effective iron-molybdenum-disulfide counter electrodes for use in platinum-free dye-sensitized solar cells

Nanocomposites of iron disulfide（FeS2） and molybdenum disulfide（MoS2） with nanosheets structure were successfully grown on the flexible titanium foils through a facile one-step hydrothermal process, and then worked as counter electrodes（CEs） in the dye-sensitized solar cells（DSSCs）. X-ray diffraction, scanning electron microscopy,transmission electron microscopy, and energy dispersive spectrometer were employed to characterize the microstructure and composition of the FeS2/MoS2. Cyclic voltammogram reveals that the catalytic activity of FeS2/MoS2 CE is higher than that of FeS2, MoS2, and platinum（Pt） CEs towards triiodide/iodide（I3^–/I^–） redox electrolyte, owing to the superior carrier transfer properties of vertical array structure and abundant catalytic active sites of FeS2/MoS2 nanosheets.Moreover, the FeS2/MoS2 CE maintains its activity after 500 cycles, exhibiting excellent electrochemical stability. Furthermore, the power conversion efficiency（PCE） of FeS2/MoS2 CE reaches 8.67%, which is higher than that of the FeS2（7.20%）,MoS2（7.38%） and Pt（8.16%） CEs.

Regional growth model for summer maize based on a logistic model:Case study in China

The growing degree days(GDD)is an important factor for crop growth because it affects dry matter formation and crop yield.In this study,the universal logistic models were established employing GDD and the relative GDD(RGDD)as the main parameters to characterize summer maize growth indices such as plant height(H),leaf area index(LAI),and dry matter accumulation(DMA).The relationships were analyzed between the growth indices,harvest index(HI),water consumption,and yield in maize.By considering China as an example,the results showed that the logistic model performed well at simulating the changes in the summer maize growth indices in different regions and the universal model parameters were within specific ranges.Furthermore,the logistic model with RGDD as the independent variable was more suitable for modeling summer maize growth in large areas than GDD.The relationship between the maximum LAI and HI was described by a quadratic polynomial function.HI was optimal(0.53)when the maximum LAI was about 5.13.The maximum LAI,maximum H,and maximum DMA could be described by a quadratic polynomial function of water consumption during the growing season.The summer maize yield could be predicted with a binary quadratic equation using the maximum GDD and water consumption.This study confirmed that a logistic model can be used to establish a universal growth model for summer maize in large areas.Reasonable ranges of parameters were recommended for the logistic model,as well as the reasonable water consumption and each growth index value for summer maize.These results will be helpful for predicting the growth and yield of summer maize.

Risk Assessment of Debris Flows Along the Karakoram Highway (Kashgar‑Khunjerab Section) in the Context of Climate Change

The Karakoram highway(KKH)is renowned for its complex natural environment and geological conditions.The climate changes drastically and directly infuences the frequency and magnitude of debris fows in this region,resulting in signifcant casualties and economic losses.However,the risk assessment of debris fows along the KKH in the context of climate change has been rarely explored.Therefore,in this study we used the debris fow data,historical meteorological data and future climate prediction data to assess the debris fow risk of the study region during the baseline period(2009–2018),2025s(2021–2030),2035s(2031–2040)and 2045s(2041–2050)under the Representative Concentration Pathway 8.5 scenario.The results show that the risk of debris fows increases with climate change,with the highest risk level in the 2025s.Among diferent parts of this highway,the upper reaches of the Ghez River and the second half of Tashkorgan-Khunjerab are the sections with the highest risk.These fndings are helpful for debris fow prevention and can ofer coping strategies for the existing line of the KKH.They also provide some reference for the renovation,improvement,operation,and maintenance of the KKH.

“Water in salt/ionic liquid”electrolyte for 2.8 V aqueous lithium-ion capacitor

Development of high-voltage electrolytes with non-flammability is significantly important for future energy storage devices.Aqueous electrolytes are inherently non-flammable,easy to handle,and their electrochemical stability windows(ESWs)can be considerably expanded by increasing electrolyte concentrations.However,further breakthroughs of their ESWs encounter bottlenecks because of the limited salt solubility,leading to that most of the high-energy anode materials can hardly function reversibly in aqueous electrolytes.Here,by introducing a non-flammable ionic liquid as co-solvent in a lithium salt/water system,we develop a"water in salt/ionic liquid"(WiSIL)electrolyte with extremely low water content.In such WiSIL electrolyte,commercial niobium pentoxide(Nb2O5)material can operate at a low potential(-1.6 V versus Ag/AgCl)and contribute its full capacity.Consequently,the resultant Nb2O5-based aqueous lithium-ion capacitor is able to operate at a high voltage of 2.8 V along with long cycling stability over 3000 cycles,and displays comparable energy and power performance(51.9 Wh kg^-1 at 0.37 kW kg^-1 and 16.4 Wh kg^-1 at 4.9 kW kg^-1)to those using non-aqueous electrolytes but with improved safety performance and manufacturing efficiency.

Synergetic ternary metal oxide nanodots-graphene cathode for high performance zinc energy storage

Zinc-based electrochemistry ene rgy sto rage with high safety and high theoretical capacity is considered to be a competitive candidate to replace lithium-ion batteries.In electrochemical energy storage,multimetal oxide cathode materials can generally provide a wider electrochemical stability window and a higher capacity compared with single metal oxides cathode.Here,a new type of cathode material,MnFe2Co3O8 nanodots/functional graphene sheets,is designed and used for aqueous hybrid Zn-based energy storage.Coupling with a hybrid electrolyte based on zinc sulfate and potassium hydroxide,the asfabricated battery was able to work with a wide electrochemical window of 0.1~1.8 V,showed a high specific capacity of 660 mAh/g,delivered an ultra high energy density of 1135 Wh/kg and a scalable power density of 5754 W/kg(calculated based on the cathode),and displayed a long cycling life of 1000 cycles.These are mainly attributed to the valence charge density distribution in MnFe2Co3O8 nanodots,the good structural strengthening as well as high conductivity of the cathode,and the right electrolyte.Such cathode material also exhibited high electrocatalytic activity for oxygen evolution reaction and thus could be used for constructing a Zn-air battery with an ultrahigh reversible capacity of 9556 mAh/g.

An AI‑Based Method for Estimating the Potential Runout Distance of Post‑Seismic Debris Flows

The widely distributed sediments following an earthquake presents a continuous threat to local residential areas and infrastructure. These materials become more easily mobilized due to reduced rainfall thresholds. Before establishing an effective management plan for debris flow hazards, it is crucial to determine the potential reach of these sediments. In this study, a deep learning-based method-Dual Attention Network(DAN)-was developed to predict the runout distance of potential debris flows after the 2022 Luding Earthquake, taking into account the topography and precipitation conditions. Given that the availability of reliable precipitation data remains a challenge, attributable to the scarcity of rain gauge stations and the relatively coarse resolution of satellite-based observations, our approach involved three key steps. First, we employed the DAN model to refine the Global Precipitation Measurement(GPM) data, enhancing its spatial and temporal resolution. This refinement was achieved by leveraging the correlation between precipitation and regional environment factors(REVs) at a seasonal scale. Second, the downscaled GPM underwent calibration using observations from rain gauge stations. Third,mean absolute error(MAE), mean square error(MSE), and root mean square error(RMSE) were employed to evaluate the performance of both the downscaling and calibration processes. Then the calibrated precipitation, catchment area, channel length, average channel gradient, and sediment volume were selected to develop a prediction model based on debris flows following the Wenchuan Earthquake. This model was applied to estimate the runout distance of potential debris flows after the Luding Earthquake. The results show that:(1) The calibrated GPM achieves an average MAE of 1.56 mm, surpassing the MAEs of original GPM(4.25 mm) and downscaled GPM(3.83 mm);(2) The developed prediction model reduces the prediction error by 40 m in comparison to an empirical equation;(3) The potential runout distance of debris flows after the Luding Earthquake reaches 0.77 km when intraday rainfall is 100 mm, while the minimum distance value is only 0.06 km.Overall, the developed model offers a scientific support for decision makers in taking reasonable measurements for loss reduction caused by post-seismic debris flows.