Combined Insights from Leachate Structure and Microstructure Characteristics for Eating Quality of Convenience Rice Processed by Super-Heated and Pressurized Steam Technologies

Convenience rice has become widely popular due to its easy availability for cooking. This study investigated the starch structure and composition of leachate and the microstructure of reheated convenience rice using novel processing technologies: super-heated steaming(SHS), auto-electric cooking(AEC), and pressurized-steam cooking(PSC). Additionally, the effect of two different target water contents(58% and 63%) was also evaluated. The PSC_63% sample had the highest total solids and amylopectin amount in the leachate. The amylopectin amount in the leachate differed significantly based on the targeted water content. Morphological characterization revealed that the swelling of starch and the coated layer on the surface of rice grains were most pronounced in the PSC_63% sample due to the pressure processing. The textural hardness of the AEC_58% sample was much higher than that of the other samples. The PSC_63% sample had the highest textural adhesiveness value, which can be attributed to the highest amylopectin amount in the leachate. Sensory characterization showed that the PSC_63% sample had the highest glossiness, whiteness, moistness, and overall acceptability. The principal component analysis score plots presented substantial differences in the leachate and textural and sensory characteristics of reheated convenience rice among the different processing technologies.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

Green‑Solvent Processed Blade‑Coating Organic Solar Cells with an Efficiency Approaching 19%Enabled by Alkyl‑Tailored Acceptors

Power-conversion-efficiencies(PCEs)of organic solar cells(OSCs)in laboratory,normally processed by spin-coating technology with toxic halogenated solvents,have reached over 19%.However,there is usually a marked PCE drop when the bladecoating and/or green-solvents toward large-scale printing are used instead,which hampers the practical development of OSCs.Here,a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused endgroup.Thanks to the N-alkyl engineering,NIR-absorbing YR-SeNF series show different crystallinity,packing patterns,and miscibility with polymeric donor.The studies exhibit that the molecular packing,crystallinity,and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains,providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YRSeNF-based OSCs.As a result,a record-high PCE approaching 19%is achieved in the blade-coating OSCs fabricated from a greensolvent o-xylene with high-boiling point.Notably,ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep>80%of the initial PCEs for even over 400 h.Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs,which paves a way for industrial development.

Influence of layer thickness on formation quality,microstructure,mechanical properties,and corrosion resistance of WE43 magnesium alloy fabricated by laser powder bed fusion

Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.

Mechanism of microarc oxidation on AZ91D Mg alloy induced byβ-Mg_(17)Al_(12) phase

This work proposed a strategy of indirectly inducing uniform microarc discharge by controlling the content and distribution ofβ-Mg_(17)Al_(12)phase in AZ91D Mg alloy.Two kinds of nano-particles(ZrO_(2)and TiO_(2))were designed to be added into the substrate of Mg alloy by friction stir processing(FSP).Then,Mg alloy sample designed with different precipitated morphology ofβ-Mg_(17)Al_(12)phase was treated by microarc oxidation(MAO)in Na_(3)PO_(4)/Na2SiO3electrolyte.The characteristics and performance of the MAO coating was analyzed using scanning electron microscopy(SEM),energy dispersive spectrometer(EDS),X-ray diffraction(XRD),X-ray photoelectron spectroscopy(XPS),contact angle meter,and potentiodynamic polarization.It was found that the coarseα-Mg grains in extruded AZ91D Mg alloy were refined by FSP,and theβ-Mg_(17)Al_(12)phase with reticular structure was broken and dispersed.The nano-ZrO_(2)particles were pinned at the grain boundary by FSP,which refined theα-Mg grain and promoted the precipitation ofβ-Mg_(17)Al_(12)phase in grains.It effectively inhibited the“cascade”phenomenon of microarcs,which induced the uniform distribution of discharge pores.The MAO coating on Zr-FSP sample had good wettability and corrosion resistance.However,TiO_(2)particles were hardly detected in the coating on TiFSP sample.

Enhancement of liquid-liquid micromixing performance in curved capillary microreactor by generation of Dean vortices

Micromixing efficiency is an important parameter for evaluating the multiphase mass transfer performance and reaction efficiency of microreactors.In this work,the novel curved capillary reactor with different shapes was designed to generate Dean flow,which was used to enhance the liquid-liquid micromixing performance.The Villermaux-Dushman probe reaction was employed to characterize the micromixing performance in different curved capillary microreactors.The effects of experiment parameters such as liquid flow rate,inner diameter,tube length,and curve diameter on micromixing performance were systematically investigated.Under the optimal conditions,the minimum value of the segmentation factor XS was 0.008.It was worth noting that at the low Reynolds number(Re<30),the change of curved shape on the capillary microreactor can significantly improve the micromixing performance with XS reduced by 37.5%.Further,the correlations of segment index XS with dimensionless factor such as Reynolds number or Dean number were developed,which can be used to predict the liquid-liquid micromixing performance in capillary microreactors.

Shallow Convection Dataset Simulated by Three Different Large Eddy Models

Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes,yet its parameterization in numerical models remains a great challenge,partly due to the lack of high-resolution observations.This study describes a large eddy simulation(LES)dataset for four shallow convection cases that differ primarily in inversion strength,which can be used as a surrogate for real data.To reduce the uncertainty in LES modeling,three different large eddy models were used,including SAM(System for Atmospheric Modeling),WRF(Weather Research and Forecasting model),and UCLA-LES.Results show that the different models generally exhibit similar behavior for each shallow convection case,despite some differences in the details of the convective structure.In addition to grid-averaged fields,conditionally sampled variables,such as in-cloud moisture and vertical velocity,are also provided,which are indispensable for calculation of the entrainment/detrainment rate.Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection,the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.

THE EXTREMES OF DEPENDENT CHI-PROCESSES ATTRACTED BY THE BROWN-RESNICK PROCESS

Motivated by some recent works on the topic of the Brown-Resnick process, we study the functional limit theorem for normalized pointwise maxima of dependent chi-processes. It is proven that the properly normalized pointwise maxima of those processes are attracted by the Brown-Resnick process.

Reliable calculations of nuclear binding energies by the Gaussian process of machine learning

Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the nuclear binding energies are modeled directly using a machine-learning method called the Gaussian process. First, the binding energies for 2238 nuclei with Z > 20 and N > 20 are calculated using the Gaussian process in a physically motivated feature space, yielding an average deviation of 0.046 MeV and a standard deviation of 0.066 MeV. The results show the good learning ability of the Gaussian process in the studies of binding energies. Then, the predictive power of the Gaussian process is studied by calculating the binding energies for 108 nuclei newly included in AME2020. The theoretical results are in good agreement with the experimental data, reflecting the good predictive power of the Gaussian process. Moreover, the α-decay energies for 1169 nuclei with 50 ≤ Z ≤ 110 are derived from the theoretical binding energies calculated using the Gaussian process. The average deviation and the standard deviation are, respectively, 0.047 MeV and 0.070 MeV. Noticeably, the calculated α-decay energies for the two new isotopes ^ (204 )Ac(Huang et al. Phys Lett B 834, 137484(2022)) and ^ (207) Th(Yang et al. Phys Rev C 105, L051302(2022)) agree well with the latest experimental data. These results demonstrate that the Gaussian process is reliable for the calculations of nuclear binding energies. Finally, the α-decay properties of some unknown actinide nuclei are predicted using the Gaussian process. The predicted results can be useful guides for future research on binding energies and α-decay properties.

Industrial utilization of arsenic-containing gold dressing tailings as pellet prepared by straight grate process

The utilization of arsenic-containing gold dressing tailings is an urgent issue faced by gold production companies worldwide.The thermodynamic analysis results indicate that ferrous arsenate(FeAsO_(4)),pyrite(FeS_(2))and sodium cyanide(NaCN)in the arsenic-containing gold metallurgical tailings can be effectively removed using straight grate process,and the removal of pyrite and sodium cyanide is basically completed during the preheating stage,while the removal of ferrous arsenate requires the roasting stage.The pellets undergo a transformation from magnetite to hematite during the preheating process,and are solidified through micro-crystalline bonding and high-temperature recrystallization of hematite(Fe_(2)O_(3))during the roasting process.Ultimately,pellets with removal rates of 80.77% for arsenic,88.78% for sulfur,and 99.88% for cyanide are obtained,as well as the iron content is 61.1% and the compressive strength is 3071 N,meeting the requirements for blast furnace burden.This study provides an industrially feasible method for treating arsenic-containing gold smelting tailings,benefiting gold production enterprises.

Carbonation of Dicalcium Silicate Enhanced by Ammonia Bicarbonate and Its Mechanism

The strength development law of γ-type dicalcium silicate (γ-C_(2)S) under different carbonation processes was investigated,and the carbonation mechanism of γ-C_(2)S under the action of NH_(4)HCO_(3) was clarified by using a wide range of test methods,including XRD and SEM.A method of saturated NH_(4)HCO_(3) solution as a curing agent was identified to improve the carbonation efficiency and enhance the carbonation degree of γ-C_(2)S,and then a high-strength carbonated specimen was obtained.Microhardness analysis and SEM morphology analysis were conducted on the carbonised specimens obtained under atmospheric pressure carbonisation conditions using the curing agent.It was found that γ-C_(2)S could perform carbonisation well under atmospheric pressure,which promoted the carbonisation efficiency and decreased the carbonisation cost simultaneously.Therefore,a new carbonisation process solution was proposed for the rapid carbonisation of γ-C_(2)S.

Simultaneous Degradation, Dehalogenation, and Detoxification of Halogenated Antibiotics by Carbon Dioxide Radical Anions

Despite the extensive application of advanced oxidation processes(AOPs)in water treatment,the efficiency of AOPs in eliminating various emerging contaminants such as halogenated antibiotics is constrained by a number of factors.Halogen moieties exhibit strong resistance to oxidative radicals,affecting the dehalogenation and detoxification efficiencies.To address these limitations of AOPs,advanced reduction processes(ARPs)have been proposed.Herein,a novel nucleophilic reductant—namely,the carbon dioxide radical anion(CO_(2)^(·-))—is introduced for the simultaneous degradation,dehalogenation,and detoxification of florfenicol(FF),a typical halogenated antibiotic.The results demonstrate that FF is completely eliminated by CO_(2)^(·-),with approximately 100%of Cland 46%of Freleased after 120 min of treatment.Simultaneous detoxification is observed,which exhibits a linear response to the release of free inorganic halogen ions(R2=0.97,p<0.01).The formation of halogen-free products is the primary reason for the superior detoxification performance of this method,in comparison with conventional hydroxyl-radical-based AOPs.Products identification and density functional theory(DFT)calculations reveal the underlying dehalogenation mechanism,in which the chlorine moiety of FF is more susceptible than other moieties to nucleophilic attack by CO_(2)^(·-).Moreover,CO_(2)^(·-)-based ARPs exhibit superior dehalogenation efficiencies(>75%)in degrading a series of halogenated antibiotics,including chloramphenicol(CAP),thiamphenicol(THA),diclofenac(DLF),triclosan(TCS),and ciprofloxacin(CIP).The system shows high tolerance to the pH of the solution and the presence of natural water constituents,and demonstrates an excellent degradation performance in actual groundwater,indicating the strong application potential of CO_(2)^(·-)-based ARPs in real life.Overall,this study elucidates the feasibility of CO_(2)^(·-)for the simultaneous degradation,dehalogenation,and detoxification of halogenated antibiotics and provides a promising method for their regulation during water or wastewater treatment.

Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors.The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency.The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations.It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.The informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other descriptions.The developed method determines the relevance of the full description of the recognized object with the reduced description of the etalons.Several practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are considered.The results of the experimental modeling of the proposed methods for a database including images of museum jewelry are presented.The test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of view.The practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been researched.Modeling has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification accuracy.Reducing the descriptions by twenty times in the experiment leads to slightly decreased accuracy.The speed of the analysis increases in proportion to the degree of reduction.The use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent level of accuracy.

Suppression of current-induced membrane discharge of bipolar membranes by regulating ion crossover transport

Bipolar membranes(BPMs)exhibit the unique capability to regulate the operating environment of electrochemical system through the water dissociation-combination processes.However,the industrial utilization of BPMs is limited by instability and serious energy consumption.The current-induced membrane discharge(CIMD)at high-current conditions has a negative influence on the performance of anion-exchange membranes,but the underlying ion transport mechanisms in the BPMs remain unclear.Here,the CIMD-coupled Poisson-Nernst-Planck(PNP)equations are used to explore the ion transport mechanisms in the BPMs for both reverse bias and forward bias at neutral and acid-base conditions.It is demonstrated that the CIMD effect in the reverse-bias mode can be suppressed by enhancing the diffusive transport of salt counter-ions(Na^(+)and Cl^(−))into the BPMs,and that in the forward-bias mode with acid-base electrolytes can be suppressed by matching the transport rate of water counter-ions(H_(3)O^(+)and OH^(−)).Suppressing the CIMD can promote the water dissociation in the reverse-bias mode,as well as overcome the plateau of limiting current density and reduce the interfacial blockage of salt co-ions(Cl^(−))in the anion-exchange layer in the forward-bias mode with acid-base electrolytes.Our work highlights the importance of regulating ion crossover transport on improving the performance of BPMs.

Literature classification and its applications in condensed matter physics and materials science by natural language processing

The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.

Comparative metabolomics analysis in the clean label ingredient of NFC spine grape juice processed by mild heating vs high pressure processing

Not from concentrate(NFC)fruit juice is the crucial clean label ingredient for new-style tea-making due to its pleasant color and fresh aroma.Here,we compared the effects of mild heating(MH)and high pressure processing(HPP)on physicochemical characters and phytochemicals in NFC spine grape juice based on metabolomics analysis.Similar compound profiles were observed between HPP-treated and fresh juices.The richer phytochemical compounds comprised malvidin-3-O-glucoside,malvidin-3,5-di-O-glucoside,quercetin-3-O-rhamnoside,quercetin-3-Oglucuronide,catechin,caffeic acid,ferulic acid,procyanidin B1,procyanidin B2 were obtained after MH treatment.Nine marker phenolics and two marker tripeptides(i.e.,Glu-Val-Phe and Leu-Leu-Tyr)were identified to differentiate MH from HPP treatment,of which higher contents occurred in the MH group.Storage time experiments showed that the Glu-Val-Phe could serve as potential markers for monitoring storage of spine grape juice.These results provide new insights into the effects of processing on individual phytochemical changes and the guide for commercial application of production of spine grape NFC juice.

Colorectal cancer’s burden attributable to a diet high in processed meat in the Belt and Road Initiative countries

BACKGROUND Colorectal cancer(CRC)plays a significant role in morbidity,mortality,and economic cost in the Belt and Road Initiative(“B and R”)countries.In addition,these countries have a substantial consumption of processed meat.However,the burden and trend of CRC in relation to the consumption of a diet high in processed meat(DHPM-CRC)in these“B and R”countries remain unknown.AIM To analyze the burden and trend of DHPM-CRC in the“B and R”countries from 1990 to 2019.METHODS We used the 2019 Global Burden of Disease Study to collate information regarding the burden of DHPM-CRC.Numbers and age-standardized rates(ASRs)of deaths along with the disability-adjusted life years(DALYs)were determined among the“B and R”countries in 1990 and 2019.Using joinpoint regression analysis,the average annual percent change(AAPC)was used to analyze the temporal trends of age-standardized DALYs rate(ASDALR)from 1990 to 2019 and in the final decade(2010–2019).RESULTS We found geographical differences in the burden of DHPM-CRC among“B and R”countries,with the three highest-ranking countries being the Russian Federation,China,and Ukraine in 1990,and China,the Russian Federation,and Poland in 2019.The burden of DHPM-CRC generally increased in most member countries from 1990 to 2019(all P<0.05).The absolute number of deaths and DALYs in DHPM-CRC were 3151.15[95%uncertainty interval(UI)665.74-5696.64]and 83249.31(95%UI 15628.64-151956.31)in China in 2019.However,the number of deaths(2627.57-2528.51)and DALYs(65867.39-55378.65)for DHPM-CRC in the Russian Federation has declined.The fastest increase in ASDALR for DHPM-CRC was observed in Vietnam,Southeast Asia,with an AAPC value of 3.90%[95%confidence interval(CI):3.63%-4.16%],whereas the fastest decline was observed in Kyrgyzstan,Central Asia,with an AAPC value of-2.05%(95%CI:-2.37%to-1.73%).A substantial upward trend in ASR of mortality,years lived with disability,years of life lost,and DALYs from DHPM-CRC changes in 1990-2019 and the final decade(2010-2019)for most Maritime Silk Route members in East Asia,South Asia,Southeast Asia,North Africa,and the Middle East,as well as Central Europe,while those of the most Land Silk Route members in Central Asia and Eastern Europe have decreased markedly(all P<0.05).The ASDALR for DHPM-CRC increased more in males than in females(all P<0.05).For those aged 50-74 years,the ASDALR for DHPM-CRC in 40 members exhibited an increasing trend,except for 20 members,including 7 members in Central Asia,Maldives,and 12 high or high-middle social development index(SDI)members in other regions(all P<0.05).CONCLUSION The burden of DHPM-CRC varies substantially across“B and R”countries and threatens public health.Relevant evidence-based policies and interventions tailored to the different trends of countries in SDIs or Silk Routes should be adopted to reduce the future burden of CRC in“B and R”countries via extensive collaboration.

SIL1 improves cognitive impairment in APP23/PS45 mice by regulating amyloid precursor protein processing and Aβ generation

SIL1,an endoplasmic reticulum(ER)-resident protein,is reported to play a protective role in Alzheimer’s disease(AD).However,the effect of SIL1 on amyloid precursor protein(APP)processing remains unclear.In this study,the role of SIL1 in APP processing was explored both in vitro and in vivo.In the in vitro experiment,SIL1 was either overexpressed or knocked down in cells stably expressing the human Swedish mutant APP695.In the in vivo experiment,AAV-SIL1-EGFP or AAV-EGFP was microinjected into APP23/PS45 mice and their wild-type littermates.Western blotting(WB),immunohistochemistry,RNA sequencing(RNA-seq),and behavioral experiments were performed to evaluate the relevant parameters.Results indicated that SIL1 expression decreased in APP23/PS45 mice.Overexpression of SIL1 significantly decreased the protein levels of APP,presenilin-1(PS1),and C-terminal fragments(CTFs)of APP in vivo and in vitro.Conversely,knockdown of SIL1 increased the protein levels of APP,β-site APP cleavage enzyme 1(BACE1),PS1,and CTFs,as well as APP mRNA expression in 2EB2 cells.Furthermore,SIL1 overexpression reduced the number of senile plaques in APP23/PS45 mice.Importantly,Y-maze and Morris Water maze tests demonstrated that SIL1 overexpression improved cognitive impairment in APP23/PS45 mice.These findings indicate that SIL1 improves cognitive impairment in APP23/PS45 mice by inhibiting APP amyloidogenic processing and suggest that SIL1 is a potential therapeutic target for AD by modulating APP processing.

A thermodynamic view on the in-situ carbon dioxide reduction by biomass-derived hydrogen during calcium carbonate decomposition

In the carbonate industry,deep decarbonization strategies are necessary to effectively remediate CO_(2).These strategies mainly include both sustainable energy supplies and the conversion of CO_(2)in downstream processes.This study developed a coupled process of biomass chemical looping H2 production and reductive calcination of CaCO_(3).Firstly,a mass and energy balance of the coupled process was established in Aspen Plus.Following this,process optimization and energy integration were implemented to provide optimized operation conditions.Lastly,a life cycle assessment was carried out to assess the carbon footprint of the coupled process.Results reveal that the decomposition temperature of CaCO_(3)in an H_(2)atmosphere can be reduced to 780℃(generally around 900℃),and the conversion of CO_(2)from CaCO_(3)decomposition reached 81.33%with an H2:CO ratio of 2.49 in gaseous products.By optimizing systemic energy through heat integration,an energy efficiency of 86.30%was achieved.Additionally,the carbon footprint analysis revealed that the process with energy integration had a low global warming potential(GWP)of-2.624 kg·kg^(-1)(CO_(2)/CaO).Conclusively,this work performed a systematic analysis of introducing biomass-derived H_(2)into CaCO_(3)calcination and demonstrated the positive role of reductive calcination using green H_(2)in mitigating CO_(2)emissions within the carbonate industry.

High energy density in ultra-thick and flexible electrodes enabled by designed conductive agent/binder composite

Thick electrodes can increase incorporation of active electrode materials by diminishing the proportion of inactive constituents,improving the overall energy density of batteries.However,thick electrodes fabricated using the conventional slurry casting approach frequently exhibit an exacerbated accumulation of carbon additives and binders on their surfaces,invariably leading to compromised electrochemical properties.In this study,we introduce a designed conductive agent/binder composite synthesized from carbon nanotube and polytetrafluoroethylene.This agent/binder composite facilitates production of dry-process-prepared ultra-thick electrodes endowed with a three-dimensional and uniformly distributed percolative architecture,ensuring superior electronic conductivity and remarkable mechanical resilience.Using this approach,ultra-thick LiCoO_(2)(LCO) electrodes demonstrated superior cycling performance and rate capabilities,registering an impressive loading capacity of up to 101.4 mg/cm^(2),signifying a 242% increase in battery energy density.In another analytical endeavor,time-of-flight secondary ion mass spectroscopy was used to clarify the distribution of cathode electrolyte interphase(CEI) in cycled LCO electrodes.The results provide unprecedented evidence explaining the intricate correlation between CEI generation and carbon distribution,highlighting the intrinsic advantages of the proposed dry-process approach in fine-tu ning the CEI,with excellent cycling performance in batteries equipped with ultra-thick electrodes.