ACS Engineering Au最新文献

{"title":"Tuning Reinforcement Learning Parameters for Cluster Selection to Enhance Evolutionary Algorithms","authors":"Nathan Villavicencio,&nbsp; and ,&nbsp;Michael N. Groves*,&nbsp;","doi":"10.1021/acsengineeringau.3c0006810.1021/acsengineeringau.3c00068","DOIUrl":"https://doi.org/10.1021/acsengineeringau.3c00068https://doi.org/10.1021/acsengineeringau.3c00068","url":null,"abstract":"<p >The ability to find optimal molecular structures with desired properties is a popular challenge, with applications in areas such as drug discovery. Genetic algorithms are a common approach to global minima molecular searches due to their ability to search large regions of the energy landscape and decrease computational time via parallelization. In order to decrease the amount of unstable intermediate structures being produced and increase the overall efficiency of an evolutionary algorithm, clustering was introduced in multiple instances. However, there is little literature detailing the effects of differentiating the selection frequencies between clusters. In order to find a balance between exploration and exploitation in our genetic algorithm, we propose a system of clustering the starting population and choosing clusters for an evolutionary algorithm run via a dynamic probability that is dependent on the fitness of molecules generated by each cluster. We define four parameters, MFavOvrAll-A, MFavClus-B, NoNewFavClus-C, and Select-D, that correspond to a reward for producing the best structure overall, a reward for producing the best structure in its own cluster, a penalty for not producing the best structure, and a penalty based on the selection ratio of the cluster, respectively. A reward increases the probability of a cluster’s future selection, while a penalty decreases it. In order to optimize these four parameters, we used a Gaussian distribution to approximate the evolutionary algorithm performance of each cluster and performed a grid search for different parameter combinations. Results show parameter MFavOvrAll-A (rewarding clusters for producing the best structure overall) and parameter Select-D (appearance penalty) have a significantly larger effect than parameters MFavClus-B and NoNewFavClus-C. In order to produce the most successful models, a balance between MFavOvrAll-A and Select-D must be made that reflects the exploitation vs exploration trade-off often seen in reinforcement learning algorithms. Results show that our reinforcement-learning-based method for selecting clusters outperforms an unclustered evolutionary algorithm for quinoline-like structure searches.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 4","pages":"381–393 381–393"},"PeriodicalIF":4.3,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142010443","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":"Sustainable Energy and Decarbonization: Challenges and Opportunities","authors":"Rajnish Kumar*,&nbsp;Matteo Maestri* and Vivek Ranade*,&nbsp;","doi":"10.1021/acsengineeringau.4c00013","DOIUrl":"10.1021/acsengineeringau.4c00013","url":null,"abstract":"","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"290–292"},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591880","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":"Hydrogen Loading and Release Potential of the LOHC System Benzyltoluene/Perhydro Benzyltoluene over S–Pt/TiO2 Catalyst","authors":"Barbara Bong,&nbsp;Chalachew Mebrahtu,&nbsp;Daniela Jurado,&nbsp;Andreas Bösmann,&nbsp;Peter Wasserscheid and Regina Palkovits*,&nbsp;","doi":"10.1021/acsengineeringau.4c00003","DOIUrl":"10.1021/acsengineeringau.4c00003","url":null,"abstract":"<p >Platinum on oxide catalysts are established for the loading and unloading of liquid organic hydrogen carriers (LOHCs). These catalysts have been optimized so far to provide high reaction rates and consequently high power densities in the loading and unloading reactor units. However, high temperatures are required for catalytic dehydrogenation (hydrogen release), which can result in low energy efficiency. Another challenge is to avoid the formation of the undesired side product methylfluorene. In this work, the optimized S–Pt/TiO₂ catalyst was successfully applied in the hydrogenation and dehydrogenation of the commercially attractive LOHC system benzyltoluene/perhydro benzyltoluene (H0-BT/H12-BT). Methylfluorene was not detected using S–Pt/TiO₂, while utilizing the S–Pt/Al₂O₃ state-of-the-art catalyst caused methylfluorene formation. The S–Pt/TiO₂ catalyst combines the prevention of this side reaction with a competitive hydrogen release rate. Hence, the application of S–Pt/TiO₂ in the LOHC cycle was further studied. It was shown that the catalytic hydrogen release can be accelerated by increasing the temperature, but low reaction temperatures are desired to increase the energy efficiency of the process by enabling heat integration between the hydrogen release and waste heat generation from energetic hydrogen use cases. Accordingly, the potential for low-temperature hydrogen release at reduced pressure was demonstrated by a systematic investigation of pressure influence. With pressure reduction, the hydrogen release productivity continuously increased. Finally, the hydrogenation and dehydrogenation productivity obtained in this work was compared to results reported in the literature to demonstrate the implementation potential of the optimized S–Pt/TiO₂ catalyst.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"359–367"},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140324870","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":"Process Operability Analysis of Membrane-Based Direct Air Capture for Low-Purity CO2 Production","authors":"Vitor Gama,&nbsp;Beatriz Dantas,&nbsp;Oishi Sanyal* and Fernando V. Lima*,&nbsp;","doi":"10.1021/acsengineeringau.3c0006910.1021/acsengineeringau.3c00069","DOIUrl":"https://doi.org/10.1021/acsengineeringau.3c00069https://doi.org/10.1021/acsengineeringau.3c00069","url":null,"abstract":"<p >Addressing climate change constitutes one of the major scientific challenges of this century, and it is widely acknowledged that anthropogenic CO₂ emissions largely contribute to this issue. To achieve the “net-zero” target and keep the rise in global average temperature below 1.5 °C, negative emission technologies must be developed and deployed at a large scale. This study investigates the feasibility of using membranes as direct air capture (DAC) technology to extract CO₂ from atmospheric air to produce low-purity CO₂. In this work, a two-stage hollow fiber membrane module process is designed and modeled using the AVEVA Process Simulation platform to produce a low-purity (≈5%) CO₂ permeate stream. Such low-purity CO₂ streams could have several possible applications such as algae growth, catalytic oxidation, and enhanced oil recovery. An operability analysis is performed by mapping a feasible range of input parameters, which include membrane surface area and membrane performance metrics, to an output set, which consists of CO₂ purity, recovery, and net energy consumption. The base case for this simulation study is generated considering a facilitated transport membrane with high CO₂/N₂ separation performance (CO₂ permeance = 2100 GPU and CO₂/N₂ selectivity = 1100), when tested under DAC conditions. With a constant membrane area, both membranes’ intrinsic performances are found to have a considerable impact on the purity, recovery, and energy consumption. The area of the first module plays a dominant role in determining the recovery, purity, and energy demands, and in fact, increasing the area of the second membrane has a negative impact on the overall energy consumption, without improving the overall purities. The CO₂ capture capacity of DAC units is important for implementation and scale-up. In this context, the performed analysis showed that the m-DAC process could be appropriate as a small-capacity system (0.1–1 Mt/year of air), with reasonable recoveries and overall purity. Finally, a preliminary CO₂ emissions analysis is carried out for the membrane-based DAC process, which leads to the conclusion that the overall energy grid must be powered by renewable sources for the technology to qualify within the negative emissions category.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 4","pages":"394–404 394–404"},"PeriodicalIF":4.3,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142010491","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":"Process Operability Analysis of Membrane-Based Direct Air Capture for Low-Purity CO2 Production","authors":"Vitor Gama, Beatriz Dantas, Oishi Sanyal, Fernando V. Lima","doi":"10.1021/acsengineeringau.3c00069","DOIUrl":"https://doi.org/10.1021/acsengineeringau.3c00069","url":null,"abstract":"Addressing climate change constitutes one of the major scientific challenges of this century, and it is widely acknowledged that anthropogenic CO₂ emissions largely contribute to this issue. To achieve the “net-zero” target and keep the rise in global average temperature below 1.5 °C, negative emission technologies must be developed and deployed at a large scale. This study investigates the feasibility of using membranes as direct air capture (DAC) technology to extract CO₂ from atmospheric air to produce low-purity CO₂. In this work, a two-stage hollow fiber membrane module process is designed and modeled using the AVEVA Process Simulation platform to produce a low-purity (≈5%) CO₂ permeate stream. Such low-purity CO₂ streams could have several possible applications such as algae growth, catalytic oxidation, and enhanced oil recovery. An operability analysis is performed by mapping a feasible range of input parameters, which include membrane surface area and membrane performance metrics, to an output set, which consists of CO₂ purity, recovery, and net energy consumption. The base case for this simulation study is generated considering a facilitated transport membrane with high CO₂/N₂ separation performance (CO₂ permeance = 2100 GPU and CO₂/N₂ selectivity = 1100), when tested under DAC conditions. With a constant membrane area, both membranes’ intrinsic performances are found to have a considerable impact on the purity, recovery, and energy consumption. The area of the first module plays a dominant role in determining the recovery, purity, and energy demands, and in fact, increasing the area of the second membrane has a negative impact on the overall energy consumption, without improving the overall purities. The CO₂ capture capacity of DAC units is important for implementation and scale-up. In this context, the performed analysis showed that the m-DAC process could be appropriate as a small-capacity system (0.1–1 Mt/year of air), with reasonable recoveries and overall purity. Finally, a preliminary CO₂ emissions analysis is carried out for the membrane-based DAC process, which leads to the conclusion that the overall energy grid must be powered by renewable sources for the technology to qualify within the negative emissions category.","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"118 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140325124","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":"Interplay of Spatial and Topological Defects in Polymer Networks","authors":"B. Ruşen Argun,&nbsp; and ,&nbsp;Antonia Statt*,&nbsp;","doi":"10.1021/acsengineeringau.3c00072","DOIUrl":"10.1021/acsengineeringau.3c00072","url":null,"abstract":"<p >Polymer networks are widely used in applications, and the formation of a network and its gel point can be predicted. However, the effects of spatial and topological heterogeneity on the resulting network structure and ultimately the mechanical properties, are less understood. To address this challenge, we generate in silico random networks of cross-linked polymer chains with controlled spatial and topological defects. While all fully reacted networks investigated in this study have the same number of end-functionalized polymer strands and cross-linkers, we vary the degree of spatial and topological heterogeneities systematically. We find that spatially heterogeneous cross-linker distributions result in a reduction in the network’s primary loops with increased spatial heterogeneity, the opposite trend as observed in homogeneous networks. By performing molecular dynamics simulations, we investigated the mechanical properties of the networks. Even though spatially heterogeneous networks have more elastically active strands and cross-linkers, they break at lower extensions than the homogeneous networks and sustain slightly lower maximum stresses. Their shear moduli are higher, i.e., stiffer, than theoretically predicted, and higher than their homogeneous gel counterparts. Our results highlight that topological loop defects and spatial heterogeneities result in significantly different network structures and, ultimately, different mechanical properties.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"351–358"},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140010556","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":"Removal of Anthropogenic Toxic Gaseous Compounds from Indoor using Biomass-based Graphene Aerogels","authors":"Gouri Sankar Das,&nbsp;K. Sandeep Raju,&nbsp;Nisha Dhiman and Kumud Malika Tripathi*,&nbsp;","doi":"10.1021/acsengineeringau.3c00071","DOIUrl":"10.1021/acsengineeringau.3c00071","url":null,"abstract":"<p >The efficient capture of HCHO, tobacco smoke, and anthropogenic toxic pollutants is of paramount importance to mitigate indoor air pollution and protect the general population. Ultralight N-doped graphene aerogel (N-GA) with a three-dimensional (3D) honeycomb-like coarse-pore structure is synthesized from biomass (pear). By taking advantage of the micrometer-sized honeycomb pores, 3D interconnected porous structure, hierarchical pores, large pore volume (0.81 cm³ g^–1), highly accessible surface area (1582 m² g^–1), and heteroatom-enriched (1.89% of N and 9.88% of O) nature, the N-GA offered high adsorption of the toxic gaseous compounds (TGCs). The as-synthesized N-GA without any further chemical/physical treatment exhibits an excellent adsorption-based capture of TGCs such as HCHO (996.7 mg g^–1), ethanol (611 mg g^–1), tobacco smoke (523.8 mg g^–1), benzene (482.3 mg g^–1), toluene (392 mg g^–1), and carbon dioxide (365.3 mg g^–1). Moreover, N-GA, as a low-cost and renewable adsorbent, exhibits high recyclability and long-term adsorption efficiency. These results demonstrate the potential of N-GA as an unprecedented candidate to design high-performance adsorbents for TGCs, suggesting a great application potential in air filters to control both indoor and outdoor air pollution.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"325–332"},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139955962","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":"Celebrating ACS Engineering Au’s 2023 Rising Stars in Chemical Engineering","authors":"Vivek V. Ranade*,&nbsp; and ,&nbsp;Linda J. Broadbelt*,&nbsp;","doi":"10.1021/acsengineeringau.4c00002","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00002","url":null,"abstract":"","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 1","pages":"1–3"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139914422","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":"Upscaling Plasma-Based CO2 Conversion: Case Study of a Multi-Reactor Gliding Arc Plasmatron","authors":"Colin O’Modhrain,&nbsp;Georgi Trenchev,&nbsp;Yury Gorbanev* and Annemie Bogaerts,&nbsp;","doi":"10.1021/acsengineeringau.3c00067","DOIUrl":"10.1021/acsengineeringau.3c00067","url":null,"abstract":"<p >Atmospheric pressure plasmas have shifted in recent years from being a burgeoning research field in the academic setting to an actively investigated technology in the chemical, oil, and environmental industries. This is largely driven by the climate change mitigation efforts, as well as the evident pathways of value creation by converting greenhouse gases (such as CO₂) into useful chemical feedstock. Currently, most high technology readiness level (TRL) plasma-based technologies are based on volumetric and power-based scaling of thermal plasma systems, which results in large capital investment and regular maintenance costs. This work investigates bringing a quasi-thermal (so-called “warm”) plasma setup, namely, a gliding arc plasmatron, from a lab-scale to a pilot-scale capacity with an increase in throughput capacity by a factor of 10. The method of scaling is the parallelization of plasmatron reactors within a single housing, with the aim of maintaining a warm plasma regime while simultaneously improving build cost and efficiency (compared to separate reactors operating in parallel). Special attention is also given to the safety and control features implemented in the setup, a key component required for integration into industrial systems. The performance of the multi-reactor gliding arc plasmatron (MRGAP) reactor is investigated, focusing on the influence of flow rate and the number of active reactors. The location of active reactors was deemed to have a negligible effect on the monitored metrics of conversion, energy efficiency, and energy cost. The optimum operating conditions were found to be with the most active reactors (five) at the highest investigated flow rate (80 L/min). Analysis of results suggests that an optimum conversion (9%) and plug power-based energy efficiency (19%) can be maintained at a specific energy input (SEI) around 5.3 kJ/L (or 1 eV/molecule). The concept of parallelization of plasmatron reactors within a singular housing was demonstrated to be a viable method for scaling up from a lab-scale to a prototype-scale device, with performance analysis suggesting that increasing the power (through adding more reactor channels) and total flow rate, while maintaining an SEI around 5.3 or 4.2 kJ/L, i.e., 1.3 or 1 eV/molecule (based on plug power and plasma-deposited power, respectively), can result in increased conversion rate without sacrificing absolute conversion or energy efficiency.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"333–344"},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139771948","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":"Nonlinear Potentiodynamic Battery Charging Protocols for Fun, Education, and Application","authors":"Helge Sören Stein*,&nbsp;","doi":"10.1021/acsengineeringau.3c00047","DOIUrl":"10.1021/acsengineeringau.3c00047","url":null,"abstract":"<p >Most secondary batteries in academia are (dis)charged by applying a constant current (CC) followed by a constant voltage (CV), i.e., a CCCV procedure. The usual concept is then to condense data for interpretation into representations such as differential capacity, or d<i>Q</i>/d<i>V</i>, graphs. This is done to extract information related to phenomena such as the growth of the solid electrolyte interphase or, more broadly, degradation. Typically, these measurements take several months because measurements for differential capacity analysis need to be performed at relatively low C-rates. An alternate charging schedule to CCCV is pulsed charging, where CC sections are interrupted by an open-circuit measurement on a second time scale. These and similar partially constant current strategies primarily target diffusive effects during charging and broadly fall into a linear charging category, where the time derivative for the actuated property is mostly zero. Herein, the author explores nonlinear charging, i.e., the process of actively applying a potential with a nontrivial time derivate and a resulting nontrivial current time derivative, to engineer (dis)charge cycles with enhanced information density. This method of nonlinear charging is then used to charge a cell such that some potential ranges in the differential capacity diagram are omitted. This study is purely a simulative endeavor and not backed by experimentation owing mainly to the lack of facile implementation of arbitrary function inputs for battery cyclers and might point to limitations of the underlying theory. If found to be confirmed through an experiment, then this technique would, however, motivate a new roadmap to better understand secondary battery degradation inspired by electrocatalyst degradation.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":"4 3","pages":"345–350"},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.3c00047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139771755","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}