Cleaner Chemical Engineering最新文献

{"title":"Valorization of tannery-derived FAMEs into bio-based epoxides via chemo-enzymatic synthesis","authors":"Víctor Deroncelé ,&nbsp;Ismael Tahmaz ,&nbsp;Sílvia Sorolla ,&nbsp;Anna Bacardit","doi":"10.1016/j.clce.2025.100195","DOIUrl":"10.1016/j.clce.2025.100195","url":null,"abstract":"<div><div>The urgent transition toward low-carbon chemical manufacturing has prompted the development of renewable alternatives to fossil-based epoxy intermediates. This study presents an integrated and resource-efficient chemo-enzymatic route for the synthesis of epoxidized methyl oleate (EMO) from fatty acid methyl esters (FAMEs) derived from tannery waste—a lipid-rich but underutilized industrial residue. A single-step urea complexation achieved 86.7 ± 0.6 % methyl oleate purity with a 38.1 ± 0.9 % recovery yield, while the saturated-rich co-product (∼40 %) exhibited physicochemical properties suitable for biodiesel or lubricant applications.</div><div>Subsequent epoxidation was carried out using immobilized <em>Candida antarctica</em> lipase B (Novozym® 435) and in situ generated performic acid, yielding an oxirane oxygen content of 6.42 ± 0.14 %, corresponding to &gt;90 % conversion of double bonds under mild conditions. The enzyme retained 72 % of its initial activity after ten reuse cycles, significantly enhancing process circularity and reducing catalytic costs.</div><div>Green chemistry metrics were favorable: atom economy reached 86 %, solvent recovery exceeded 85 %, and the E-factor remained as low as 0.86 kg waste/kg EMO. A cradle-to-gate life cycle assessment (LCA) estimated a global warming potential (GWP) of 1.92 kg CO₂-eq/kg EMO—representing a 63 % reduction compared to petrochemical benchmarks. Economic analysis at the 1000 t/year scale yielded a production cost of €1.57/kg with an internal rate of return (IRR) of 15 %.</div><div>Overall, this work demonstrates how lipid-rich industrial residues can be converted into high-value bio-based epoxides through a scalable and environmentally sound chemo-enzymatic route, aligning with circular economy principles and green chemistry targets.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723823","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":"Bioremediation of heavy metals in aquatic environment: A review","authors":"Olubukola Oziegbe ,&nbsp;Ehitua  Julius Oziegbe ,&nbsp;Olusola Ojo-Omoniyi","doi":"10.1016/j.clce.2025.100193","DOIUrl":"10.1016/j.clce.2025.100193","url":null,"abstract":"<div><div>The pursuit of critical minerals such as lithium (Li), nickel (Ni), cobalt (Co), and rare earth elements (REE) has intensified mining, producing heavy metal waste that contaminates water bodies. Pollution from human activities and improper disposal of high-tech products containing heavy metals like Hg, Cd, Ni, Cu, Pb, and Cr has degraded surface and groundwater. These metals enter the human body via bioaccumulation in the food chain or direct consumption of contaminated water, posing health risks. There is an urgent need for cost-effective, eco-friendly methods to decontaminate water without generating additional pollutants. Conventional remediation technologies are costly and produce hazardous waste requiring disposal. In contrast, biological materials—such as bacteria, cyanobacteria, fungi, lichens, algae, and plants—offer affordable, sustainable solutions for water decontamination. Moreover, metal-rich biomass from bioremediation processes, like cyanoremediation, can be converted into valuable products, such as metal nanoparticles for pharmaceutical and industrial use, creating a closed-loop system that generates wealth instead of waste. Genetic engineering can further enhance biosorbent organisms and plants to improve heavy metal binding and accumulation. This review examines the environmental and health impacts of heavy metals, the limitations of conventional remediation methods, various bioremediation techniques, and future research directions.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749648","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":"Biodegradable waste-derived cellulose/nylon-6-coated iron-oxide nanocomposite encapsulated with chitosan for enhanced wastewater treatment","authors":"Evans Suter ,&nbsp;H.L Rutto ,&nbsp;I.G Mkhize","doi":"10.1016/j.clce.2025.100190","DOIUrl":"10.1016/j.clce.2025.100190","url":null,"abstract":"<div><div>The growing threats of water scarcity, climate change, and waste accumulation necessitate innovative solutions, including the transformation of solid waste into sustainable new materials through recycling technologies. This study prepared a low-cost, superior and biodegradable polymeric material made of cellulose nanocrystals from waste paper and pulp sludge, nylon-6 waste, magnetic iron oxide nanoparticles, and chitosan. The nanocomposite membrane presented saturation magnetization of 26.90 emu/g, significantly lower than magnetic saturation (Ms) of magnetic iron oxide nanoparticles (Fe₃O₄). This resulted from the addition of cellulose nanocrystals (CNCs), nylon 6 (N6), and Chitosan (CT), as confirmed by Fourier Transform Infrared (FTIR). Scanning electron microscopy (SEM) revealed that the ultra-permeable membrane had highly porous surfaces. Brunauer Emmet Teller (BET) demonstrated that the addition of chitosan and Fe₃O₄ boosted nitrogen adsorption. The isoelectric point (IEP) pH at zero point charge (pHPZC) of magnetized cellulose nanocrystals/nylon 6 nanocomposite membrane encapsulated with chitosan (CNCs/N6@Fe₃O_4<img>CT) was 7.9 due to the hydroxyl groups on the amphoteric surface that react with bases or acids to create a pHPZC that is extremely near to neutral. The nanocomposite presented a larger swelling ratio of 168.24 g/g than precursor materials. The membrane demonstrated excellent rejection efficiency, initiating at approximately 98 %. The resulting nanocomposite membrane's remarkable water permeability, porosity, good rejection, and flux, even at low pressure, offers a potential for water treatment and air filtration applications.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655412","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":"Synthesis and application of copper-based cholesteryl chloroformate gelator for oil spill remediation","authors":"Raymond T. Iorhemen,&nbsp;Abdulmumin A. Nuhu,&nbsp;Israel K. Omoniyi,&nbsp;Abubakar B. Aliyu","doi":"10.1016/j.clce.2025.100192","DOIUrl":"10.1016/j.clce.2025.100192","url":null,"abstract":"<div><div>Oil spill impact negatively on the environment. Its remediation has been very challenging, and researchers have developed high efficient methods in handling this anomaly, but end up introducing secondary pollutants to the environment. The aim of this study is to synthesise a copper-based organometallogelator with cholesteryl chloroformate and apply it for oil spill remediation in water. In the methodology, the aromatic linker coded CuAL (copper aromatic linker) was first synthesised from a reaction of copper complex (coper reacting with hydrazine) with isophthaloyl chloride, then cholesteryl chloroformate was added to produce a gelator coded CuGe (copper gelator) with the A(LS)₂ (aromatic, linker and steroid) network, which were subsequently characterised. MS results for CuAL and CuGe showed fragments corresponding to the proposed structures, and were both highly crystalline, especially CuGe. Aliphatic primary amines, aromatic rings, aromatic overtones, and conjugated ketones were present in both CuAL and CuGe, with slight variation in peak positions, and the average particle diameter were 5.9 μm (CuAL), and 47.0 μm (CuGe), respectively. The synthesised compounds were thermally stable up to 338 °C (60.1 %) for CuAL and 469.9 °C (74.1 %) for CuGe. Heating-cooling gelation test was positive for methanol, petroleum motor spirit (PMS), kerosene (KSE), and crude oil (COL), with the longest time being 9 min. The highest gelation time and temperature (Tgel) at 2 mg were 3 min (for PMS), and 60 °C for COL respectively. Sorption capacities were 3.0 ± 0.3, 2.0 ± 0.1, and 3.7 ± 0.3 3.0, for PMS, KSE, and COL respectively. The removal efficiency CuGe was 95 % for COL, 89 % for PMS, and 80 % for KSE and is recyclable. In conclusion, a thermally stable, crystalline, eco-friendly, and recyclable copper-cholesteryl chloroformate-based metallogelator has been successfully synthesised. The gelator, CuGe, was successfully applied in the gelation of KSE, PMS, and COL from water with good efficiencies.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100192"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680038","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":"In-line product separation in a continuous oscillatory flow bioreactor as process intensification and product inhibition mitigation strategy","authors":"Judith Buchmaier ,&nbsp;Theresa Plesch ,&nbsp;Philipp Petermeier ,&nbsp;Michael Egermeier ,&nbsp;Bettina Muster-Slawitsch","doi":"10.1016/j.clce.2025.100191","DOIUrl":"10.1016/j.clce.2025.100191","url":null,"abstract":"<div><div>A Continuous Oscillatory Flow Bioreactor (COFB) was developed to enable the processing of lignocellulosic biomass at high solid loadings of up to 23 % and to allow for in-line product separation. The enzymatic saccharification conducted in the COFB yielded glucose concentrations of up to 50 g/L at a residence time of 3 h, corresponding to a yield of 0.2 g_glucose/g_substrate and an enzymatic productivity of 10 g_glucose/g_enzyme. The system incorporated precise quantification of the minimal energy input for oscillatory mixing, resulting in a specific energy demand of 6 Wh/kg_glucose. Notably, the integration of in-line product separation enhanced enzymatic productivity by up to 40 %. Compared to conventional shaking flask experiments, process intensification in the COFB led to a 1.7-fold increase in volumetric productivity and a 1.6-fold reduction in residence time. These findings underscore the potential of the COFB as a scalable and energy-efficient platform for biorefinery applications.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100191"},"PeriodicalIF":0.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631698","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 integration of PCM-filled coil fins and smart water depth control in solar stills: A comprehensive energy, exergy, and environmental analysis","authors":"Lailatul Nehar ,&nbsp;Tanvir Rahman ,&nbsp;Md Shahiduzzaman Shahed ,&nbsp;Md Yeamin Prodhan ,&nbsp;Md Sazan Rahman ,&nbsp;S.S. Tuly","doi":"10.1016/j.clce.2025.100189","DOIUrl":"10.1016/j.clce.2025.100189","url":null,"abstract":"<div><div>Freshwater scarcity remains a critical global challenge, necessitating sustainable desalination solutions. This study investigates the performance enhancement of a double-slope solar still (SS) through the integration of hollow copper coil fins (HCCFs), phase change material (PCM), and an Arduino-based water depth control system. Three configurations were tested: conventional (Case I), fin-modified (Case II), and PCM-fin with smart control (Case III). Experimental results demonstrated that Case III achieved the highest productivity, yielding 1.81 L/m²/day, a 166 % improvement over the conventional still (0.68 L/m²/day) and 14 % higher than Case II (1.59 L/m²/day). Thermal analysis revealed peak energy and exergy efficiencies of 38.9 % and 4.31 %, respectively, for Case III, significantly surpassing Cases I (23.1 %, 1.45 %) and II (28.3 %, 3.45 %). The intelligent water depth modulation (20–35 mm) optimized heat transfer, while PCM extended post-sunset distillation. Economic and environmental assessments showed a payback period of 295 days and 4.8 tons of CO₂ mitigation over the system’s lifetime, with potential carbon credits of $190. This work establishes a novel, scalable approach for sustainable solar desalination.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580895","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":"Advanced biofuels research: A Scopus database-driven bibliometric evaluation and future directions forecast via machine learning and deep learning","authors":"Md. Saiful Islam ,&nbsp;Mridha Md. Nafis Fuad ,&nbsp;Sadit Bihongo Malitha ,&nbsp;Md. Zahangir Alam","doi":"10.1016/j.clce.2025.100188","DOIUrl":"10.1016/j.clce.2025.100188","url":null,"abstract":"<div><div>Renewable energy is a research hotspot in the present day to promote sustainability. Biofuel, an alternative to conventional fossil fuels, can contribute to environmental sustainability through being a renewable energy source and having a zero carbon footprint. However, traditional biofuels are generated from edible biomass, which raises questions about the use of traditional biofuels in the long run due to global food scarcity. Advanced biofuels are now being developed from non-edible biomass and waste sources, which are expected to be a colossal renewable energy source. This study conducted a complete bibliometric analysis to get an overview of research progress on advanced biofuels. A bibliographic dataset has been collected from the Scopus database. The dataset has been investigated based on articles, authors, journals, institutions, and countries to get a complete overview of current research trends on advanced biofuels. Burst keywords have also been analysed to identify the research hotspots. In addition to bibliometric analysis, machine learning and deep learning algorithms have been used to perform natural language processing (NLP), execute topic modelling, and carry out the research evolution forecast. This study will uncover the current research trend on advanced biofuels, identify the research gaps, and predict future research direction. The significance of the identified research gaps lies in their potential to guide future researchers towards areas that need further exploration, thereby contributing to advancing knowledge in this field.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100188"},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514168","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":"Interpretable SHAP-based machine learning-assisted design for selecting ultrafiltration membranes in protein-laden phosphate wastewater","authors":"Lukka Thuyavan Yogarathinam ,&nbsp;Sani I. Abba ,&nbsp;Jamilu Usman ,&nbsp;Muthumareeswaran Ramamoorthy ,&nbsp;Isam H. Aljundi","doi":"10.1016/j.clce.2025.100187","DOIUrl":"10.1016/j.clce.2025.100187","url":null,"abstract":"<div><div>Industrial wastewater contaminated with proteins and phosphates poses a significant challenge for producing clean water. This study innovatively employed regression-based machine learning (ML) algorithms to predict the separation performance of proteins with varying molecular weights from synthetic phosphate-laden wastewater using commercially available membranes with different pore sizes. The chosen ML tools are bi-layered neural network (BNN), linear regression (LR), least squares support vector machine (LSSVM), and Gaussian process regression (GPR). Correlation was employed to select the most pertinent variables for constructing an effective model combination while safeguarding against data leakage within the frugal dataset. Among the ML tools, the BNN and GPR algorithms demonstrated effective predictive capabilities for protein rejection. The collaborative integration of all input variable combinations resulted in superior predictive accuracy (R²=0.99) for protein rejection, showcasing minimal error rates for both the BNN and GPR algorithms. Interpretable SHapley Additive exPlanations (SHAP) analysis indicated that the molecular weight cutoff (MWCO), protein molecular weight (PMw), and isoelectric point (IEP) were the most influential factors affecting protein separation performance, with mean SHAP values of approximately 25, 12, and 15, respectively. The ML tools revealed that the input variables of MWCO, PMw, and IEP exerted a more substantial impact compared to hydro-dynamic variables. This study provides insights into advancing the development of ML tools tailored to sparse datasets, particularly for accurately predicting protein separation from phosphate-laden wastewater.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279928","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":"Phyto-mediated synthesis of polymetallic nanoparticles (Cu/Ag/Ru/Gd/Te) using abutilon indicum filtrate: Antimicrobial, antioxidant, antidiabetic and photocatalytic potentials","authors":"R Rathika,&nbsp;S Srinivasan,&nbsp;M Sindhu Devi","doi":"10.1016/j.clce.2025.100185","DOIUrl":"10.1016/j.clce.2025.100185","url":null,"abstract":"<div><div>This research delves into the creation of polymetallic nanoparticles composed of Cu/Ag/Ru/Gd/Te (PNS), utilizing the seed filtrate from the medicinal plant <em>Abutilon indicum</em>. A variety of characterization techniques have demonstrated a robust surface plasmon resonance in the range of 200 to 400 nm. Furthermore, the study examined the morphology, shape, composition, oxidation states, particle size, and thermal properties of the nanoparticles through SEM, EDX, XPS, AFM, and DTA/TG methods. The crystalline sizes were found to be 18.3 nm for Cu, 17.2 nm for Ag, 17.9 nm for Ru, 18.1 nm for Gd, and 17.9 nm for Te. The study also explored antibacterial and photocatalytic properties, revealing significant in vitro antidiabetic activity, with IC₅₀ values of 326 µg/ml for the α-amylase inhibition assay and 303 µg/ml for α-glucosidase inhibition. Additionally, the antioxidant activity of PNS was measured, yielding an IC₅₀ value of 127 µg/ml and an R² value of 0.9172.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100185"},"PeriodicalIF":0.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365927","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":"Evaluation of methane emissions reduction methods in the oil and natural gas operations using a decision support system under quartic fuzzy DEAMEIM-MARCOS model","authors":"Abdolvahhab Fetanat ,&nbsp;Mohsen Tayebi ,&nbsp;Elham Gholampour","doi":"10.1016/j.clce.2025.100186","DOIUrl":"10.1016/j.clce.2025.100186","url":null,"abstract":"<div><div>Methane is an important greenhouse gas that has been linked to climate change impacts and the industry of oil and natural gas (O&amp;G) energy is a major source of methane emissions. These emissions arise from leaks and regular venting that occurs throughout O&amp;G operations. Mitigating these emissions from the operations of the studied industry has advantages for air quality and health. There are several policy options that are considered as solutions available to mitigate the emissions of methane from O&amp;G operations. Choosing the appropriate policy option is a complex multi-criteria decision-making (MCDM) problem that needs to use an intelligent and robust decision support system (DSS) to employ a smart and resilient model to decrease uncertainty in the decision-making process. The proposed DSS of this work incorporates the Delphi method and Method based on the Removal Effects of Criteria (MEREC) integration method (DEAMEIM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model under the quartic fuzzy set (QFS). Moreover, a hybrid criteria system, which involves 19 criteria has been used to evaluate policy options for methane emissions reduction. The criteria are selected according to the integration of 1) sustainability pillars and 2) health, safety, and environmental (HSE) aspects. The results of evaluations exhibit that the Regulation of methane leak detection and repair (LDAR) programs, is the most suitable scenario for methane emissions reduction from the operations. Computational analysis confirms the practicality and applicability of the DSS in determining the best possible scenario.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100186"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239768","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}