ACS Engineering Au最新文献

{"title":"Effect of SO2 and SO3 Exposure to Cu-CHA on Surface Nitrate and N2O Formation for NH3–SCR","authors":"Joonsoo Han, Joachim D. Bjerregaard, Henrik Grönbeck, Derek Creaser, Louise Olsson","doi":"10.1021/acsengineeringau.4c00004","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00004","url":null,"abstract":"We report effects of SO₂ and SO₃ exposure on ammonium nitrate (AN) and N₂O formation in Cu-CHA used for NH₃–SCR. First-principles calculations and several characterizations (ICP, BET, XRD, UV–vis–DRS) were applied to characterize the Cu-CHA material and speciation of sulfur species. The first-principles calculations demonstrate that the SO₂ exposure results in both (bi)sulfite and (bi)sulfate whereas the SO₃ exposure yields only (bi)sulfate. Furthermore, SOx adsorption on framework-bound dicopper species is shown to be favored with respect to adsorption onto framework-bound monocopper species. Temperature-programmed reduction with H₂ shows two clear reduction states and larger sulfur uptake for the SO₃-exposed Cu-CHA compared to the SO₂-exposed counterpart. Temperature-programmed desorption of formed ammonium nitrate (AN) highlights a significant decrease in nitrate storage due to sulfur species interacting with copper sites in the form of ammonium/copper (bi)bisulfite/sulfate. Especially, highly stable sulfur species from SO₃ exposure influence the NO₂–SCR chemistry by decreasing the N₂O selectivity during NH₃–SCR whereas an increased N₂O selectivity was observed for the SO₂-exposed Cu-CHA sample. This study provides fundamental insights into how SO₂ and SO₃ affect the N₂O formation during ammonium nitrate decomposition in NH₃–SCR applications, which is a very important topic for practical applications.","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141190474","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":"Chemical Aspect of Ocean Liming for CO2 Removal: Dissolution Kinetics of Calcium Hydroxide in Seawater","authors":"Selene Varliero,&nbsp;Annamaria Buono,&nbsp;Stefano Caserini,&nbsp;Guido Raos* and Piero Macchi*,&nbsp;","doi":"10.1021/acsengineeringau.4c0000810.1021/acsengineeringau.4c00008","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00008https://doi.org/10.1021/acsengineeringau.4c00008","url":null,"abstract":"<p >Ocean liming is attracting ever-increasing attention as one of the most suitable and convenient ways of removing carbon dioxide from the atmosphere and combating global warming and the acidification of the oceans at the same time. However, the short-term consequences of Ca(OH)₂ [slaked lime] dissolution in seawater have been scarcely studied. In this work, we investigate in detail what happens in the initial stages after the dissolution of slaked lime, analyzing the kinetics of the process and the effects on the physicochemical parameters of seawater. A series of experiments, carried out by varying the seawater conditions (like temperature and salinity) or the liming conditions (like the dispersion in the form of slurry or powder and the concentration) allow us to draw conclusions on the ideal conditions for a more efficient and environmentally friendly liming process.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142010493","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":"Chemical Aspect of Ocean Liming for CO2 Removal: Dissolution Kinetics of Calcium Hydroxide in Seawater","authors":"Selene Varliero, Annamaria Buono, S. Caserini, Guido Raos, Piero Macchi","doi":"10.1021/acsengineeringau.4c00008","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00008","url":null,"abstract":"","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973739","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":"Nozzle Innovations That Improve Capacity and Capabilities of Multimaterial Additive Manufacturing","authors":"Patrick J. McCauley, Alexandra V. Bayles","doi":"10.1021/acsengineeringau.4c00001","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00001","url":null,"abstract":"Multimaterial additive manufacturing incorporates multiple species within a single 3D-printed object to enhance its material properties and functionality. This technology could play a key role in distributed manufacturing. However, conventional layer-by-layer construction methods must operate at low volumetric throughputs to maintain fine feature resolution. One approach to overcome this challenge and increase production capacity is to structure multimaterial components in the printhead prior to deposition. Here we survey four classes of multimaterial nozzle innovations, nozzle arrays, coextruders, static mixers, and advective assemblers, designed for this purpose. Additionally, each design offers unique capabilities that provide benefits associated with accessible architectures, interfacial adhesion, material properties, and even living-cell viability. Accessing these benefits requires trade-offs, which may be mitigated with future investigation. Leveraging decades of research and development of multiphase extrusion equipment can help us engineer the next generation of 3D-printing nozzles and expand the capabilities and practical reach of multimaterial additive manufacturing.","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140928151","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":"Nozzle Innovations That Improve Capacity and Capabilities of Multimaterial Additive Manufacturing","authors":"Patrick J. McCauley,&nbsp; and ,&nbsp;Alexandra V. Bayles*,&nbsp;","doi":"10.1021/acsengineeringau.4c0000110.1021/acsengineeringau.4c00001","DOIUrl":"https://doi.org/10.1021/acsengineeringau.4c00001https://doi.org/10.1021/acsengineeringau.4c00001","url":null,"abstract":"<p >Multimaterial additive manufacturing incorporates multiple species within a single 3D-printed object to enhance its material properties and functionality. This technology could play a key role in distributed manufacturing. However, conventional layer-by-layer construction methods must operate at low volumetric throughputs to maintain fine feature resolution. One approach to overcome this challenge and increase production capacity is to structure multimaterial components in the printhead prior to deposition. Here we survey four classes of multimaterial nozzle innovations, nozzle arrays, coextruders, static mixers, and advective assemblers, designed for this purpose. Additionally, each design offers unique capabilities that provide benefits associated with accessible architectures, interfacial adhesion, material properties, and even living-cell viability. Accessing these benefits requires trade-offs, which may be mitigated with future investigation. Leveraging decades of research and development of multiphase extrusion equipment can help us engineer the next generation of 3D-printing nozzles and expand the capabilities and practical reach of multimaterial additive manufacturing.</p>","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142010492","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":"Materials Design: The Next Paradigm in Chemistry and Engineering","authors":"Steven G. Arturo*,&nbsp;Linda J. Broadbelt*,&nbsp;Paul J. Dauenhauer* and Ananth Govind Rajan*,&nbsp;","doi":"10.1021/acsengineeringau.4c00014","DOIUrl":"10.1021/acsengineeringau.4c00014","url":null,"abstract":"","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsengineeringau.4c00014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140611640","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":"Tuning Reinforcement Learning Parameters for Cluster Selection to Enhance Evolutionary Algorithms","authors":"Nathan Villavicencio, Michael N. Groves","doi":"10.1021/acsengineeringau.3c00068","DOIUrl":"https://doi.org/10.1021/acsengineeringau.3c00068","url":null,"abstract":"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.","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591987","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":"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}