ACS Engineering Au最新文献

{"title":"High-Consistency Foam Pilot Process for Producing Fibrous Cushion Material","authors":"Elina Pääkkönen,&nbsp;Tuomas Turpeinen,&nbsp;Olli-Ville Laukkanen,&nbsp;Baranivignesh Prakash,&nbsp;Jouni Paltakari,&nbsp;Jukka A. Ketoja","doi":"10.1021/acsengineeringau.5c00120","DOIUrl":"https://doi.org/10.1021/acsengineeringau.5c00120","url":null,"abstract":"<p>High-consistency (HC) suspensions containing severalweight% offibers have been studied in the past but mainly in relation to water-laidweb-forming technology. The severe flocking problems deterioratingweb quality can be partly solved by using aqueous foam as a transfermedium instead of water. The processability of highly viscous HC foamand its potential to produce low-density fiber products are revealedonly in large-scale dynamic conditions with the proper flow propertiesof the foam. For this reason, a pilot-scale study was conducted at10–14% fiber consistency and a 3 m/min web speed using softwood,hardwood, and a 50/50 fiber mixture as raw materials. To better understandthe effects of additives on foam processability and the strength ofthe final product, the following additives were selected: guar gum(GG), carboxymethyl cellulose (CMC), citric acid, and a combinationof the latter two. These studies were supported by rheological measurementsand X-ray microtomography analysis of the product structures. In rheologicalmeasurements, the HC fiber foams turned out to have significant elasticitywith a high storage modulus. Interestingly, the highest consistencyin the pilot studies led to the smallest mean floc size and totalfloc volume in the corresponding samples. The best strength propertieswere gained with citric acid and CMC. Overall, the findings indicatethat HC foam demonstrates significant technological potential forproducing sustainable fiber products with efficient water usage.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"519–530"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clarification on the Influence of Reducing Agents on the Extraction Mechanism of Metals from NMC111","authors":"Chiara Canciani,&nbsp;Madhumitha Dhanasekaran,&nbsp;Shekhar Kulkarni,&nbsp;Nimer Wehbe,&nbsp;Bambar Davaasuren,&nbsp;Varaha P. Sarvothaman,&nbsp;William L. Roberts","doi":"10.1021/acsengineeringau.5c00119","DOIUrl":"https://doi.org/10.1021/acsengineeringau.5c00119","url":null,"abstract":"<p>The urgent requirement for battery materials to satisfytheir risingdemand due to electrification is straining limited mineral resources.Thus, recycling is becoming increasingly more important to reducereliance on mining and delocalize the supply chain of critical batterymetals. In this framework, the use of process-intensification techniquesto improve recycling yields is fundamental to ensuring scalabilityand economic viability. The extraction (leaching) of metals from spentbatteries is the core step of hydrometallurgical recycling, and itsintensification using acoustic cavitation has shown impressive results,enabling the use of milder organic acids. This work aims at investigatingthe quantitative effects of the addition of hydrogen peroxide as areducing agent during cavitation-assisted leaching, to pinpoint itseffect on the extraction. This results in a deeper understanding ofthe action of both reducing agents during the cavitation-intensifiedprocess.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"504–518"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Driven Discovery of Highly Sensitive Nanocolumnar NiO Electrochemical Glucose Sensors","authors":"MohammadAli Maleki Bigdeli,&nbsp;Jennifer Bruce,&nbsp;Abebaw B. Jemere,&nbsp;Kenneth D. Harris,&nbsp;Wylie Stroberg","doi":"10.1021/acsengineeringau.6c00026","DOIUrl":"https://doi.org/10.1021/acsengineeringau.6c00026","url":null,"abstract":"<p>Nanostructured NiO electrodes fabricated using glancingangle deposition(GLAD) are promising platforms for nonenzymatic electrochemical glucosesensing, owing to their high surface area and tunable morphology.With GLAD, adjusting the deposition angle and substrate rotation ratecan significantly affect electrochemical performance; however, identifyingoptimal GLAD structures for specific use cases is still largely experimental,relying on trial and error. Here, we develop a multiscale modelingframework that links the GLAD film growth process to glucose electro-oxidationperformance by combining on-lattice kinetic Monte Carlo (kMC) simulationswith morphology characterization and a coupled reaction–diffusionelectrochemical model. Key morphological features, including surfacearea, porosity, and directional tortuosities, are quantified fromkMC-generated structures across a wide range of GLAD geometries, suchas slanted posts, helical shapes, and vertical nanocolumns. Thesefeatures are then incorporated into a homogenized porous electrodemodel for glucose electro-oxidation on Ni-based catalysts. The modelclarifies how the trade-off between surface area and mass transportgoverns electrode sensitivity. We identify a slanted-post morphologydeposited at 72.5° as the optimal design for maximizing glucoseelectro-oxidation, and we find that physical electrodes formed withsimilar geometries were approximately 25% more sensitive to glucosethan those formed with the vertical post morphology previously consideredto be the optimum (i.e., 1.38 mA/mM·cm² vs 1.12 mA/mM·cm²). Beyond glucose, this modeling workflow provides generalguidelines for designing GLAD-fabricated electrodes for other biosensingtargets and for electrochemical applications, including energy conversionand hydrogen generation.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"567–577"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable Recovery and Stabilization of Coconut Residues (Cocos nucifera L.) Phytochemicals via Hydrothermal Extraction and Chitosan–Alginate Encapsulation","authors":"Vanessa Cosme Ferreira,&nbsp;Luiz Eduardo Nochi Castro,&nbsp;Tiago Linhares Cruz Tabosa Barroso,&nbsp;Leda Maria Saragiotto Colpini,&nbsp;Tânia Forster-Carneiro","doi":"10.1021/acsengineeringau.6c00025","DOIUrl":"https://doi.org/10.1021/acsengineeringau.6c00025","url":null,"abstract":"<p>This study aimed to evaluate pressurized hydrothermalextractionas a sustainable strategy for recovering bioactive compounds fromcoconut residues. The methodology involved a continuous-flow systemat varying temperatures (60, 90, and 120 °C) to optimize phytochemicalrecovery, followed by stabilization via chitosan–alginate encapsulation,and a comprehensive sustainability assessment using EcoScale and Path2Greenmetrics. The study demonstrated that pressurized hydrothermal extractionat 120 °C is the most effective condition for recovering bioactivecompounds from coconut residues, yielding the highest levels of totalphenolic content (41.57 mg GAE g^–1), total flavonoidcontent (57.52 mg CE g^–1), and total tannin content(15.37 mg TAE g^–1), along with the maximum antioxidantactivity (69.74 μmol TEAC g^–1). The encapsulationprocess using chitosan–alginate matrices achieved encapsulationefficiencies of up to 65.47%, with dry microcapsules showing enhancedphenolic retention (26.73 mg GAE g^–1 capsules) comparedto wet capsules (24.41 mg GAE g^–1 capsules). Therelease kinetics of phenolic compounds followed a diffusion-controlledmechanism, with lyophilized microcapsules exhibiting a higher initialrelease (45% within 15 min) and greater long-term stability, retaining86.79% of phenolic content after 30 days of refrigerated storage.The environmental assessment revealed favorable sustainability metrics,with an EcoScale score of 88.10 and a Path2Green global score of 0.320,highlighting the process’s alignment with green chemistry principlesand its potential for industrial applications in food, cosmetics,and pharmaceuticals.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"550–566"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow of Non-Newtonian Fluids through a Vortex-Based Hydrodynamic Cavitation Device","authors":"Mukesh Upadhyay,&nbsp;Jai Rathod,&nbsp;Vivek V. Ranade","doi":"10.1021/acsengineeringau.5c00121","DOIUrl":"https://doi.org/10.1021/acsengineeringau.5c00121","url":null,"abstract":"<p>Hydrodynamic cavitation(HC) is being increasingly used for a varietyof industrially relevant processes such as biomass pretreatment, emulsions,and crystallization. Many of these processes involve non-Newtonianfluids. However, most of the previous studies on characterizing flowin cavitating devices focus on low-viscosity, Newtonian fluids. Inthis study, we investigate the influence of non-Newtonian, particularlyshear-thinning behavior of fluids on the flow characteristics andcavitation inception in a vortex-based hydrodynamic cavitation device(VD) using both experiments and computational fluid dynamics (CFD)simulations. Primary digestate from an anaerobic digester was consideredas a model non-Newtonian fluid, considering increasing applicationsof HC devices for biomass pretreatment. The non-Newtonian behaviorwas represented using the Carreau rheological model. The parametersof the model were obtained via rheological measurements over a shearrate range of 10 to 1300 s^–1 of two digestate slurriescontaining 50% (v/v) and 77% (v/v) with water. The case of water wasused as the reference case. A three-dimensional (3D) CFD simulationof flow in VD was performed by using the Eulerian mixture model. TheSST <em>k–</em>ω turbulence model and the Singhalcavitation model were used. Simulations were validated by comparingthe simulated pressure drop across VD with the experimental measurements.Simulation results show that the 50% (v/v) and 77% (v/v) digestateslurries exhibit a reduction in swirl intensity in the vortex chamberand a delayed cavitation inception compared with the reference caseof water. The results were analyzed to bring out the influence ofhigher effective viscosity and non-Newtonian behavior on the flowcharacteristics of VD. The presented results will be useful for designingVD for high-viscosity applications in waste valorization.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"531–541"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Atomistic Construction and Interface Stabilization of Fe3O4@Au Core–Shell Nanostructures via Machine Learning","authors":"Seda Aygul Akyuz,&nbsp;Zeliha Cansu Canbek Ozdil","doi":"10.1021/acsengineeringau.6c00010","DOIUrl":"https://doi.org/10.1021/acsengineeringau.6c00010","url":null,"abstract":"<p>The structural stability of metal oxide-metal core-shellnanoparticlesat the nanoscale is governed by atomistic interface effects that arenot captured by conventional continuum approximations. In this work,we introduce an automated “virtual synthesis” frameworkfor the deterministic construction, relaxation, and validation ofFe₃O₄@Au core–shell nanoparticles usinga machine-learning interatomic potential (CHGNet). The pipeline integratesgeometric assembly based on crystallographic symmetry and Wulff construction,CHGNet-assisted energetic relaxation, and postrelaxation quality controlto ensure chemically and structurally consistent interfaces. Systematicparametric analysis reveals strict structural viability thresholdsinherent to nanoscale heterostructures. Specifically, core diametersbelow D &lt; 7.0 Å fail to preserve spinel coordination, whileAu shell thicknesses below T &lt; 0.8 Å do not yield a percolatedmetallic network for a 20 Å particle, to generate a continuousshell. Radial distribution analysis confirms the formation of polycrystallineFCC Au shells anchored by strong Au–O interactions (≈2.20Å), alongside a measurable lattice compression of ∼4%,indicative of curvature-induced surface stress. Together, these resultsestablish quantitative lower bounds for structural feasibility inmagneto-plasmonic core–shell systems and demonstrate the capabilityof graph neural network-based interatomic potentials to bridge thegap between continuum design and atomistic realism.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 4","pages":"542–549"},"PeriodicalIF":9.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrodialysis for the Recovery of Acetate from Microbial Electrosynthesis Effluents","authors":"Santiago Martínez Sosa,&nbsp;Qingdian Shu,&nbsp;Michele Tedesco,&nbsp;Hubertus V.M. Hamelers,&nbsp;Pau Farràs,&nbsp;Paolo Dessì","doi":"10.1021/acsengineeringau.5c00110","DOIUrl":"10.1021/acsengineeringau.5c00110","url":null,"abstract":"<p>Microbial electrosynthesis (MES) is a promising bioelectrochemicaltechnology for converting CO₂ into value-added products.However, downstream processing remains a major constraint for itsapplication at larger scales. There is limited understanding of whichseparation technologies can be effectively integrated with MES effluents,and how key operating conditions impact on the product recovery andenergy efficiency. This study assesses the use of electrodialysis(ED) as a solvent-free downstream separation process for acetate recoveryfrom a multicomponent simulated MES effluent. The effects of operatingpH (3, 5.5, and 7.5), applied current density (1.9, 3.8, 9.5, and15.0 mA cm^–2), and operation mode (continuous orfed-batch) were investigated. The highest acetate titer (13.73 ±1.65) in the concentrate stream was reached at pH 5.5, a current densityof 1.9 mA cm^–2, and under fed-batch operation. Ioncompetition was identified as the primary limiting factor, with preferentialCl^– transport, which reduced the Coulombic efficiencyof acetate transport to 34.97 ± 0.63%. Under these conditions,the ED system recovered 1.12 ± 0.03 kg of acetate per kWh, correspondingto approximately 5% of the total energy demand associated with MESproduction. Overall, this study provides quantitative guidance onthe optimization of electrodialysis as a recovery technology froma simulated MES effluent as a low-energy downstream solution for MESsystems, helping to address key bottlenecks faced by this technology.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 3","pages":"404–414"},"PeriodicalIF":9.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148624398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic Interactions During Co-Hydrothermal Liquefaction of Food Waste and Biomass Model Compounds for Increased Sustainable Aviation Fuel Production","authors":"Skyler B. Kauffman,&nbsp;Heather O. LeClerc,&nbsp;Alex R. Maag,&nbsp;Geoffrey A. Tompsett,&nbsp;Jeffrey R. Page,&nbsp;Julia A. Valla,&nbsp;Andrew R. Teixeira,&nbsp;Michael T. Timko","doi":"10.1021/acsengineeringau.6c00009","DOIUrl":"10.1021/acsengineeringau.6c00009","url":null,"abstract":"<p>Hydrothermal liquefaction (HTL) of lignocellulosic biomassis plaguedwith low biocrude yields owing to the tendency of highly reactiveoxygenated intermediates to condense to form biochars. By contrast,the high protein content in food waste is comprised of substantialnitrogen species, which are known to interact strongly with oxygenatesthrough Maillard, amide, and peptide bond formation reactions. Co-feedingfood waste and lignocellulose opens new reaction pathways for biocrudeformation but is currently poorly understood. This work evaluatedthe molecular level interactions between food waste and lignocellulosemodel compounds and the corresponding effect on product yields andquality. Food waste–cellulose and food waste–xylan feedstockblends achieved maximum biocrude carbon yield improvements of 12.2%and 10.1%, respectively, relative to a simple linear model that interpolatesbetween the yields of the pure feedstocks. Increases in biocrude yieldwere balanced by corresponding decreases in char yield, indicatingsynergistic interactions between the feeds during HTL. Biocrude volatilityanalysis revealed that increased biocrude yield preferentially benefittedthe jet fuel fraction, which comprised up to 22.6% of the total carbonyield for food waste–cellulose blends. Biocrude and char wereanalyzed using GC–MS and FT-IR spectroscopy to investigatethe source of synergistic trends and provide greater mechanistic understanding.Key cofeeding effects included the promotion of retro-aldol condensationreactions and trans-esterification of fatty acids, sequestering carbonin the biocrude phase via the inhibition of char formation while increasingbiocrude volatility toward jet fuel-range compounds. These resultsindicate the potential for judicious selection of HTL cofeeds to increaseboth biocrude yield and selectivity to desired fuel precursors, includingsustainable aviation fuel.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 3","pages":"490–503"},"PeriodicalIF":9.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148296571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PPO-GPR: A Custom Proximal Policy Optimization Tool for Active Reinforcement Learning","authors":"Etinosa Osaro,&nbsp;Yamil J. Colón","doi":"10.1021/acsengineeringau.5c00122","DOIUrl":"10.1021/acsengineeringau.5c00122","url":null,"abstract":"<p>Efficient data selectionis critical in domains where data acquisitionis expensive and time-consuming, such as material science. In thiswork, we introduce a novel active learning framework that integratesproximal policy optimization (PPO) with Gaussian process regression(GPR) to strategically select informative data points and therebyenhance predictive modeling. Leveraging the inherent stability andsample efficiency of PPO, achieved through a clipped surrogate objective,the framework guides data acquisition via a custom-designed Gymnasiumenvironment tailored for GPR. In this environment, the PPO agent dynamicallychooses data points based on their potential to improve the GPR’sperformance, as measured by the <em>R</em>² score,while preventing redundancy through an action masking mechanism. Weapply the proposed methodology to predict the selectivity of methane(CH₄) over higher alkanes in metal–organic frameworks(MOFs), focusing on CuBTC and IRMOF-1. The framework is evaluatedusing both ternary and quaternary gas mixtures, where the performanceof the GPR is assessed through metrics such as <em>R</em>², mean absolute error (MAE), and root mean squared error (RMSE).Across CuBTC and IRMOF-1 in ternary and quaternary hydrocarbon mixtures,PPO-guided acquisition achieves 77–86% data savings relativeto full GCMC grids, typically querying only ∼14–23%of the candidate pool while the clipped-update PPO policy convergesstably by focusing selections in the pressure–temperature–compositionregions where selectivity changes most rapidly. This work shows thepotential of combining advanced reinforcement learning techniqueswith regression models to accelerate material discovery and optimizegas separation processes.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 3","pages":"446–462"},"PeriodicalIF":9.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148296222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow Modeling, Reactor Engineering, and Process Intensification: From Insight to Performance","authors":"Vivek V. Ranade","doi":"10.1021/acsengineeringau.6c00002","DOIUrl":"10.1021/acsengineeringau.6c00002","url":null,"abstract":"<p>Flow modeling, reactor engineering, and process intensification(PI) have played a major role in shaping modern chemical engineeringpractice. Early work in flow modeling focused on the use of computationalmodels to visualize flow fields and improve the design of processequipment. During this period, reactor engineering increasingly reliedon flow modeling to optimize reactor geometry and internals acrossscales. The growing emphasis on PI, through strategies such as transformingbatch operations into continuous ones, employing structured reactorsor alternative energy sources, and enhancing driving forces, furtheraccelerated the development and integration of these approaches. Inthis perspective, critical process metrics (CPMs) are presented asa useful framework for connecting flow modeling, reactor engineering,and PI and translating mechanistic insight into performance. Recentadvances in machine learning (ML) and hybrid physics–ML modelsprovide tools to address distributions, variability, and scale dependenceof CPMs, and to relate them to critical quality and performance attributes(CQAs and CPAs). Anchoring models to measurable fingerprints and embeddingthem within decision frameworks (that account for uncertainty) canenable the convergence of flow modeling, reactor engineering, andPI toward robust and scalable product and process excellence.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"6 3","pages":"372–387"},"PeriodicalIF":9.0,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148296752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}