This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and alu...This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and aluminum(Al)electrodes.Thisdevice yielded a very high ROFF:RON of~104(ION:IOFF of~105)with an excellent activation slope of 10 mV/dec,low set voltage ofVSET~1.14 V and good repeatability.This paper physically explained the conduction mechanism in the layered SnO_(2)nanofiber-basedmemristor.The conductive network was composed of nanofibersthat play a vital role in the memristive action,since more conductive paths could facilitate the hopping of electron carriers.Energyband structures experimentally extracted with the adoption of ultraviolet photoelectron spectroscopy strongly support the claimsreported in this paper.An machine learning(ML)–assisted,datadriven model of the fabricated memristor was also developedemploying different popular algorithms such as polynomialregression,support vector regression,k nearest neighbors,andartificial neural network(ANN)to model the data of the fabricateddevice.We have proposed two types of ANN models(type I andtype II)algorithms,illustrated with a detailed flowchart,to modelthe fabricated memristor.Benchmarking with standard ML techniques shows that the type II ANN algorithm provides the bestmean absolute percentage error of 0.0175 with a 98%R^(2)score.The proposed data-driven model was further validated with the characterization results of similar new memristors fabricated adoptingthe same fabrication recipe,which gave satisfactory predictions.Lastly,the ANN type II model was applied to design and implementsimple AND&OR logic functionalities adopting the fabricatedmemristors with expected,near-ideal characteristics.展开更多
Environmental pollution,energy consumption,and greenhouse gas emissions are critical global issues.To address these challenges,optimizing skimmer coatings is a major step in commercializing cleaning oil stains.This re...Environmental pollution,energy consumption,and greenhouse gas emissions are critical global issues.To address these challenges,optimizing skimmer coatings is a major step in commercializing cleaning oil stains.This research presents a novel approach to creating and refining oil absorbent coatings,introducing a unique oil spill removal skimmer enhanced with a super hydrophobic polyaniline(PANI)nanofiber coating.The goal of this study was to improve oil absorption performance,increase the contact angle,lower drag,reduce energy consumption,achieve high desirability,and lower production costs.PANI treated with hydrochloric acid was a key focus as it resulted in higher porosity and smaller pore diameters,providing a larger surface area,which are crucial factors for boosting oil absorption and minimizing drag.To optimize optimal nanofiber morphology,PANI synthesized with methanesulfonic acid was first dedoped and then redoped with hydrochloric acid.After optimization,the most effective skimmer coating was achieved using a formulation consisting of 0.1%PANI,an ammonium persulfate/aniline ratio of 0.4,and an acid/aniline ratio of 9.689,along with redoped PANI nanofibers.The optimized skimmer exhibited a remarkable contact angle of 177.477°.The coating achieved drag reduction of 32%,oil absorption of 88.725%,a cost of$1.710,and a desirability rating of 78.5%.In this study,an optimized skimmer coat containing super hydrophobic coat-PANI nanofibers was fabricated.By enhancing contact angle and reducing drag,these coatings increased the skimmer performance by improving oil absorption and reducing fuel consumption.展开更多
文摘This paper demonstrated the fabrication,characterization,datadriven modeling,and practical application of a 1D SnO_(2)nanofiber-based memristor,in which a 1D SnO_(2)active layer wassandwiched between silver(Ag)and aluminum(Al)electrodes.Thisdevice yielded a very high ROFF:RON of~104(ION:IOFF of~105)with an excellent activation slope of 10 mV/dec,low set voltage ofVSET~1.14 V and good repeatability.This paper physically explained the conduction mechanism in the layered SnO_(2)nanofiber-basedmemristor.The conductive network was composed of nanofibersthat play a vital role in the memristive action,since more conductive paths could facilitate the hopping of electron carriers.Energyband structures experimentally extracted with the adoption of ultraviolet photoelectron spectroscopy strongly support the claimsreported in this paper.An machine learning(ML)–assisted,datadriven model of the fabricated memristor was also developedemploying different popular algorithms such as polynomialregression,support vector regression,k nearest neighbors,andartificial neural network(ANN)to model the data of the fabricateddevice.We have proposed two types of ANN models(type I andtype II)algorithms,illustrated with a detailed flowchart,to modelthe fabricated memristor.Benchmarking with standard ML techniques shows that the type II ANN algorithm provides the bestmean absolute percentage error of 0.0175 with a 98%R^(2)score.The proposed data-driven model was further validated with the characterization results of similar new memristors fabricated adoptingthe same fabrication recipe,which gave satisfactory predictions.Lastly,the ANN type II model was applied to design and implementsimple AND&OR logic functionalities adopting the fabricatedmemristors with expected,near-ideal characteristics.
文摘Environmental pollution,energy consumption,and greenhouse gas emissions are critical global issues.To address these challenges,optimizing skimmer coatings is a major step in commercializing cleaning oil stains.This research presents a novel approach to creating and refining oil absorbent coatings,introducing a unique oil spill removal skimmer enhanced with a super hydrophobic polyaniline(PANI)nanofiber coating.The goal of this study was to improve oil absorption performance,increase the contact angle,lower drag,reduce energy consumption,achieve high desirability,and lower production costs.PANI treated with hydrochloric acid was a key focus as it resulted in higher porosity and smaller pore diameters,providing a larger surface area,which are crucial factors for boosting oil absorption and minimizing drag.To optimize optimal nanofiber morphology,PANI synthesized with methanesulfonic acid was first dedoped and then redoped with hydrochloric acid.After optimization,the most effective skimmer coating was achieved using a formulation consisting of 0.1%PANI,an ammonium persulfate/aniline ratio of 0.4,and an acid/aniline ratio of 9.689,along with redoped PANI nanofibers.The optimized skimmer exhibited a remarkable contact angle of 177.477°.The coating achieved drag reduction of 32%,oil absorption of 88.725%,a cost of$1.710,and a desirability rating of 78.5%.In this study,an optimized skimmer coat containing super hydrophobic coat-PANI nanofibers was fabricated.By enhancing contact angle and reducing drag,these coatings increased the skimmer performance by improving oil absorption and reducing fuel consumption.
