ACS Engineering Au最新文献

{"title":"Decarbonization in Australia and India: Bilateral Opportunities and Challenges for the Net Zero Transformation","authors":"Marcello B. Solomon,&nbsp;Swapna S. Rabha,&nbsp;Gustavo Fimbres-Weihs,&nbsp;Himanshu Goyal,&nbsp;Firouzeh R. Taghikhah,&nbsp;Jithin J. Varghese,&nbsp;Samuel R. Wenger,&nbsp;Weibin Liang,&nbsp;Eleanor R. Kearns,&nbsp;Jun Huang,&nbsp;Niket S. Kaisare* and Deanna M. D’Alessandro*,&nbsp;","doi":"10.1021/acsengineeringau.3c00060","DOIUrl":"10.1021/acsengineeringau.3c00060","url":null,"abstract":"<p >The global Net Zero transformation is a vital response to the climate change crisis. Australia and India face similar challenges due to their reliance on fossil resources, growing energy demand, and agricultural emissions. However, differences exist in the population, industry, and development. This perspective explores these comparisons between Australia and India’s Net Zero aspirations and current sociopolitical and economic drivers. As part of the portfolio of options needed to address net zero goals, Carbon Capture, Utilization, and Storage (CCUS) and Carbon Dioxide Removal (CDR) solutions are specifically discussed. The perspective concludes with opportunities for the nations to engage in knowledge sharing and bilateral partnerships to help accelerate the world’s transformation to Net Zero.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"295–311"},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139560604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing Computational Efficiency of CFD Simulations of Reactive Flows at Catalyst Surfaces through Dynamic Load Balancing","authors":"Daniele Micale,&nbsp;Mauro Bracconi* and Matteo Maestri,&nbsp;","doi":"10.1021/acsengineeringau.3c00066","DOIUrl":"10.1021/acsengineeringau.3c00066","url":null,"abstract":"<p >We propose a numerical strategy based on dynamic load balancing (DLB) aimed at enhancing the computational efficiency of multiscale CFD simulation of reactive flows at catalyst surfaces. Our approach employs DLB combined with a hybrid parallelization technique, integrating both MPI and OpenMP protocols. This results in an optimized distribution of the computational load associated with the chemistry solution across processors, thereby minimizing computational overheads. Through assessments conducted on fixed and fluidized bed reactor simulations, we demonstrated a remarkable improvement of the parallel efficiency from 19 to 87% and from 19 to 91% for the fixed and fluidized bed, respectively. Owing to this improved parallel efficiency, we observe a significant computational speed-up of 1.9 and 2.1 in the fixed and fluidized bed reactor simulations, respectively, compared to simulations without DLB. All in all, the proposed approach is able to improve the computational efficiency of multiscale CFD simulations paving the way for a more efficient exploitation of high-performance computing resources and expanding the current boundaries of feasible simulations.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"312–324"},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139498438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative Retrieval-Augmented Ontologic Graph and Multiagent Strategies for Interpretive Large Language Model-Based Materials Design","authors":"Markus J. Buehler*,&nbsp;","doi":"10.1021/acsengineeringau.3c00058","DOIUrl":"10.1021/acsengineeringau.3c00058","url":null,"abstract":"<p >Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design, and manufacturing, including their capacity to work effectively with human language, symbols, code, and numerical data. Here, we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths. Moreover, when used as sets of AI agents with specific features, capabilities, and instructions, LLMs can provide powerful problem-solution strategies for applications in analysis and design problems. Our experiments focus on using a fine-tuned model, MechGPT, developed based on training data in the mechanics of materials domain. We first affirm how fine-tuning endows LLMs with a reasonable understanding of subject area knowledge. However, when queried outside the context of learned matter, LLMs can have difficulty recalling correct information and may hallucinate. We show how this can be addressed using retrieval-augmented Ontological Knowledge Graph strategies. The graph-based strategy helps us not only to discern how the model understands what concepts are important but also how they are related, which significantly improves generative performance and also naturally allows for injection of new and augmented data sources into generative AI algorithms. We find that the additional feature of relatedness provides advantages over regular retrieval augmentation approaches and not only improves LLM performance but also provides mechanistic insights for exploration of a material design process. Illustrated for a use case of relating distinct areas of knowledge, here, music and proteins, such strategies can also provide an interpretable graph structure with rich information at the node, edge, and subgraph level that provides specific insights into mechanisms and relationships. We discuss other approaches to improve generative qualities, including nonlinear sampling strategies and agent-based modeling that offer enhancements over single-shot generations, whereby LLMs are used to both generate content and assess content against an objective target. Examples provided include complex question answering, code generation, and execution in the context of automated force-field development from actively learned density functional theory (DFT) modeling and data analysis.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"241–277"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139459242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emissions from Hydrogen Peroxide Disinfection and Their Interaction with Mask Surfaces","authors":"Pearl Abue,&nbsp;Nirvan Bhattacharyya,&nbsp;Mengjia Tang,&nbsp;Leif G. Jahn,&nbsp;Daniel Blomdahl,&nbsp;David T. Allen,&nbsp;Richard L. Corsi,&nbsp;Atila Novoselac,&nbsp;Pawel K. Mistzal and Lea Hildebrandt Ruiz*,&nbsp;","doi":"10.1021/acsengineeringau.3c00036","DOIUrl":"10.1021/acsengineeringau.3c00036","url":null,"abstract":"<p >A rise in the disinfection of spaces occurred as a result of the COVID-19 pandemic as well as an increase in people wearing facial coverings. Hydrogen peroxide was among the recommended disinfectants for use against the virus. Previous studies have investigated the emissions of hydrogen peroxide associated with the disinfection of spaces and masks; however, those studies did not focus on the emitted byproducts from these processes. Here, we simulate the disinfection of an indoor space with H₂O₂ while a person wearing a face mask is present in the space by using an environmental chamber with a thermal manikin wearing a face mask over its breathing zone. We injected hydrogen peroxide to disinfect the space and utilized a chemical ionization mass spectrometer (CIMS) to measure the primary disinfectant (H₂O₂) and a Vocus proton transfer reaction time-of-flight mass spectrometer (Vocus PTR-ToF-MS) to measure the byproducts from disinfection, comparing concentrations inside the chamber and behind the mask. Concentrations of the primary disinfectant and the byproducts inside the chamber and behind the mask remained elevated above background levels for 2–4 h after disinfection, indicating the possibility of extended exposure, especially when continuing to wear the mask. Overall, our results point toward the time-dependent impact of masks on concentrations of disinfectants and their byproducts and a need for regular mask change following exposure to high concentrations of chemical compounds.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"204–212"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139412753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of Shear Flows over Superhydrophobic Surfaces: From Newtonian to Non-Newtonian Fluids","authors":"Hossein Rahmani,&nbsp;Faïçal Larachi and Seyed Mohammad Taghavi*,&nbsp;","doi":"10.1021/acsengineeringau.3c00048","DOIUrl":"10.1021/acsengineeringau.3c00048","url":null,"abstract":"<p >The design and use of superhydrophobic surfaces have gained special attentions due to their superior performances and advantages in many flow systems, e.g., in achieving specific goals including drag reduction and flow/droplet handling and manipulation. In this work, we conduct a brief review of shear flows over superhydrophobic surfaces, covering the classic and recent studies/trends for both Newtonian and non-Newtonian fluids. The aim is to mainly review the relevant mathematical and numerical modeling approaches developed during the past 20 years. Considering the wide ranges of applications of superhydrophobic surfaces in Newtonian fluid flows, we attempt to show how the developed studies for the Newtonian shear flows over superhydrophobic surfaces have been evolved, through highlighting the major breakthroughs. Despite the fact that, in many practical applications, flows over superhydrophobic surfaces may show complex non-Newtonian rheology, interactions between the non-Newtonian rheology and superhydrophobicity have not yet been well understood. Therefore, in this Review, we also highlight emerging recent studies addressing the shear flows of shear-thinning and yield stress fluids in superhydrophobic channels. We focus on reviewing the models developed to handle the intricate interaction between the formed liquid/air interface on superhydrophobic surfaces and the overlying flow. Such an intricate interaction will be more complex when the overlying flow shows nonlinear non-Newtonian rheology. We conclude that, although our understanding on the Newtonian shear flows over superhydrophobic surfaces has been well expanded via analyzing various aspects of such flows, the non-Newtonian counterpart is in its early stages. This could be associated with either the early applications mainly concerning Newtonian fluids or new complexities added to an already complex problem by the nonlinear non-Newtonian rheology. Finally, we discuss the possible directions for development of models that can address complex non-Newtonian shear flows over superhydrophobic surfaces.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"166–192"},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139373962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biocompatible Cs2PtX6 (X = Cl, Br, I) Vacancy Ordered Perovskites and Shewanella oneidensis MR-1 Bacteria Hybrid for Potential Photocatalytic Solar Fuel Production","authors":"Shweta Shinde,&nbsp;Muhammed Hamdan,&nbsp;Prerna Bhalla and Aravind Kumar Chandiran*,&nbsp;","doi":"10.1021/acsengineeringau.3c00061","DOIUrl":"10.1021/acsengineeringau.3c00061","url":null,"abstract":"<p >Semiconductor-bacterial hybrid systems have been shown to be effective for photochemical conversion. The combination of two systems delineates the light absorption from the catalytic ability, wherein a semiconductor absorbs light, generating an electron–hole pair, followed by the transfer of photogenerated charges to catalytically active bacteria that assume the roles of carrying out redox reactions. The halide perovskite materials possess excellent optoelectronic properties and, if they exhibit biocompatibility with microorganisms, shall provide an opportunity to carry out environmentally important redox reactions including carbon dioxide conversion to value added products. In this work, we report the biocompatibility of panchromatic visible light absorption and stable vacancy ordered halide perovskite (VOP), Cs₂PtX₆ (X = halide) with <i>Shewanella oneidensis</i> MR-1 nonphotosynthetic bacterium. This microbe is shown to grow in culture media containing VOP, and the growth rate is found to be unaffected by the presence of semiconductor media. Although <i>Shewanella oneidensis</i> MR-1 is a well-known metal-reducing bacteria, in this work, we find that the vacancy ordered perovskite materials remain intact with this bacterium. With constraint-based metabolic modeling, we report that this biohybrid system shall potentially be used for solar energy conversion of water and carbon dioxide to hydrogen and formate, respectively.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"224–230"},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139052474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Active Learning for the Computational Design of Polymer Molecular Weight Distributions","authors":"Haifan Zhou,&nbsp;Yue Fang and Hanyu Gao*,&nbsp;","doi":"10.1021/acsengineeringau.3c00056","DOIUrl":"10.1021/acsengineeringau.3c00056","url":null,"abstract":"<p >The design of the reaction conditions is essential for controlling polymerization to synthesize polymers with desired properties. However, the experimental screening of the reaction conditions can be time-consuming and costly. Computational methods such as kinetic Monte Carlo (KMC) simulations have been developed to assist with the design of experiments. Nevertheless, when the dimensions of the reaction conditions to be explored are large, the simulation models might still not be able to meet the demand for efficient screening and design. Active learning can be used to tackle this problem by designing data acquisition strategies that can minimize the labeling required to construct a good surrogate model in the design space. In this work, we combined a cluster-maximum model change (CMMC) model with KMC simulations, which can precisely design polymerization conditions at the lowest computational cost for the desired molecular weight distributions. The case study results show that the CMMC model only uses 50 KMC simulations to construct a predictive model with a 10% relative error for a system with 4 design parameters, which greatly reduces the computational cost while maintaining accuracy.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"231–240"},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139052379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tailored Platinum Group Metal/Spinel Oxide Catalysts for Dynamically Enhanced Methane Oxidation","authors":"Pak Wing Chen,&nbsp;Debtanu Maiti,&nbsp;Ru-Fen Liu,&nbsp;Lars C. Grabow* and Michael P. Harold*,&nbsp;","doi":"10.1021/acsengineeringau.3c00053","DOIUrl":"10.1021/acsengineeringau.3c00053","url":null,"abstract":"<p >A combined experimental and molecular modeling study identifies a family of spinel oxides that in combination with PGM (platinum group metals) provide enhanced methane oxidation activity. With a reduction in greenhouse gas (GHG) emissions urgently needed, there is renewed interest in the use of natural gas vehicles (NGVs) and engines (NGEs) for transportation, commerce, and industrial applications. NGVs and NGEs emit less CO₂ than their petroleum-derived counterparts but may emit uncombusted methane, an even more potent GHG. For stoichiometric engines, methane oxidation catalysts containing PGM and spinel oxide in layered architectures offer increased methane oxidation activity and lower light-off temperatures (<i>T</i>₅₀). The reducible spinel oxide has direct and indirect roles that are effectively described by the bulk oxygen vacancy formation energy (<i>E</i>_vac). We apply density functional theory (DFT) to identify several earth-abundant, cobalt-rich spinel oxides with favorable <i>E</i>_vac, shown to correlate with dynamic oxygen storage capacity (DOSC) and CO and H₂ oxidation activity. We experimentally rank-order the DFT-identified spinel oxides in combination with Pt+Pd for their methane oxidation activity measurements, under both time-invariant and modulated feed conditions. We show good agreement between the activity and the DFT-computed reducibility of the spinel oxide. The findings suggest spinel reducibility is a key factor in achieving enhanced low-temperature methane conversion, enabled through a balance of methane activation on the PGM sites and subsequent oxidation of the intermediates and byproducts on spinel oxides. In agreement with its computationally predicted <i>E</i>_vac, NiCo₂O₄ was confirmed to have the highest DOSC and lowest <i>T</i>₅₀ among the tested spinel samples.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"193–203"},"PeriodicalIF":0.0,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139029134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Energy Efficiency of a Twin-Screw Granulation Process in Real-Time Using a Long Short-Term Memory (LSTM) Network","authors":"Chaitanya Sampat,&nbsp; and ,&nbsp;Rohit Ramachandran*,&nbsp;","doi":"10.1021/acsengineeringau.3c00038","DOIUrl":"10.1021/acsengineeringau.3c00038","url":null,"abstract":"<p >Traditional pharmaceutical manufacturing processes for solid oral dosage forms can be inefficient and have been known to produce a large amount of undesired product. With the progressing trend of achieving carbon neutrality, there is an impetus to increase the energy efficiency of these manufacturing processes while maintaining the critical quality attributes of the product. One of the important steps in downstream pharmaceutical manufacturing is wet granulation, and within that, twin screw granulation (TSG) is a popular continuous manufacturing technique. In this study, the energy efficiency of the TSG process was maximized by combining a long-term memory (LSTM) model with an optimization algorithm. The LSTM model was trained on time-series process data obtained from the TSG experimental runs. The optimization process, with the objective of maximizing energy efficiency, was performed using a stochastic optimization algorithm, and constraints were enforced on the process parameter design space. Experimental runs at the optimal process parameters were conducted on the TSG equipment with updates occurring at predefined intervals depending on the optimization scenarios. The purpose of these experimental runs was to validate the capability of increasing the overall process energy efficiency when operating at the optimized process parameters. A maximum increase of 27% was obtained between two tested optimization scenarios while maintaining the yield of the granules at the end of the twin-screw granulation process.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"278–289"},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138950400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaling Up 3D-Printed Porous Reactors for the Continuous Synthesis of 2,5-Diformylfuran","authors":"Dionysia Koufou,&nbsp; and ,&nbsp;Simon Kuhn*,&nbsp;","doi":"10.1021/acsengineeringau.3c00064","DOIUrl":"10.1021/acsengineeringau.3c00064","url":null,"abstract":"<p >The present study investigates the potential for scaling up 3D-printed porous reactors at the millimeter scale by integrating different reactor configurations in series. These reactor configurations, ranging from a single reactor (<i>N</i> = 1) to six reactors in series (<i>N</i> = 6), were evaluated for their performance in terms of axial dispersion in a gas–liquid system, with a focus on identifying potential dead zones. The scaled-up reactor systems exhibited a reduced deviation from plug flow behavior, mainly attributed to improved radial mixing maintained throughout the entire length of the porous structures. Among the various configurations tested, the scaled-up system featuring six reactors displayed the highest coefficient of variation (CoV) at approximately 24% for residence times exceeding 100 s. In all cases, the presence of stagnant zones influenced the shape of the residence time distribution (RTD) curves, although in the scaled-up system these stagnant zones did not significantly impact the overall performance or the yield of 2,5-diformylfuran (DFF). This was due to the narrow RTD and effective mass transfer between the stagnant and active flow compartments. Notably, the selectivity remained at 100%, and the highest yield of DFF (approximately 81%) was achieved for a residence time of 6.61 min in the scaled-up system. Despite introducing mass transfer limitations when operating at the millimeter scale, the scaled-up system achieved DFF productivity levels comparable to microreaction systems at significantly lower energy dissipation.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 2","pages":"213–223"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138818502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}