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Exploring nitrogen reduction reaction mechanisms in electrocatalytic ammonia synthesis:A comprehensive review

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Journal of Energy Chemistry 2024年第5期92卷 681-697页

作者： Abhishek Umesh Shetty ravi Sankannavar School of Chemical and Materials Science Indian Institute of Technology GoaFarmagudiPonda 403401GoaIndia Department of Chemical Engineering M.S.Ramaiah Institute of TechnologyMSR NagarMSRIT PostBengaluru 560054KarnatakaIndia

The electrochemical nitrogen reduction reaction(eNRR)holds significant promise as a sustainable alternative to the conventional large-scale Haber Bosch process,offering a carbon footprint-free approach for ammonia synthesis.While the process is thermodynamically feasible at ambient temperature and pressure,challenges such as the competing hydrogen evolution reaction,low nitrogen solubility in electrolytes,and the activation of inert dinitrogen(N_(2))gas adversely affect the performance of ammonia production.These hurdles result in low Faradaic efficiency and low ammonia production rate,which pose obstacles to the commercialisation of the process.Researchers have been actively designing and proposing various electrocatalysts to address these issues,but challenges still need to be resolved.A key strategy in electrocatalyst design lies in understanding the underlying mechanisms that govern the success or failure of the electrocatalyst in driving the electrochemical reaction.Through mechanistic studies,we gain valuable insights into the factors affecting the reaction,enabling us to propose optimised designs to overcome the barriers.This review aims to provide a comprehensive understanding of the various mechanisms involved in eNRR on the electrocatalyst surface.It delves into the various mechanisms such as dissociative,associative,Mars-van Krevelen,lithium-mediated nitrogen reduction and surface hydrogenation mechanisms of nitrogen reduction.By unravelling the intricacies of eNRR mechanisms and exploring promising avenues,we can pave the way for more efficient and commercially viable ammonia synthesis through this sustainable electrochemical process by designing an efficient electrocatalyst.

关键词： Green ammonia synthesis Electrolysis Electrocatalysis Nitrogen reductionreaction Electrochemical reaction pathways Reactionmechanism

Unsupervised intrusion detection system for in-vehicle communication networks

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Journal of Safety Science and Resilience 2024年第2期5卷 119-129页

作者： Kabilan N Vinayakumar ravi V Sowmya Center for Computational Engineering and Networking(CEN) Amrita School of Artificial InteligenceAmrita Vishwa VidyapeethamCoimbatoreIndia Center for Artificial Intlligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia

In-vehicle communication has been optimized day to day to keep updated of the technologies.Control area network(CAN)is used as a standard communication method because of its efficient and reliable connection.However,CAN is prone to several network level attacks because of its lack in security mechanisms.Various methods have been introduced to incorporate this in CAN.We proposed an unsupervised method of intrusion detection for in-vehicle communication networks by combining the optimal feature extracting ability of autoencoders and more precise clustering using fuzzy C-means(FCM).The proposed method is light weight and requires less computation time.We performed an extensive experiment and achieved an accuracy of 75.51%with the ML35o in-vehicle intrusion dataset.By experimental result,the proposed method also works better for other intrusion detection problems like wireless intrusion detection datasets such as WNS-DS with accuracy of 84.05%and network intrusion detection datasets such as KDDCup with accuracy 60.63%,UNSW_NB15 with accuracy 73.62%and Information Security Center of Excellence(Iscx)with accuracy 74.83%.Overall,the proposed method outperforms the existing methods and avoids labeled datasets when training an in-vehicle intrusion detection model.The results of the experiment of our proposed method performed on various intru-sion detection datasets indicate that the proposed approach is generalized and robust in detecting intrusions and can be effectively deployed in real time to monitor CAN traffic in vehicles and proactively alert during attacks.

关键词： Controlarea network Intrusiondetection Unsupervised learning Autoencoders Fuzzy C-means

Dynamics of some new solutions to the coupled DSW equations traveling horizontally on the seabed

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Journal of Ocean Engineering and Science 2024年第2期9卷 154-163页

作者： Raj Kumar ravi Shankar Verma Department of Mathematics Faculty of Engineering&TechnologyVeer Bahadur Singh Purvanchal UniversityJaunpur 222003India

The system of(1+1)-coupled Drinfel’d-Sokolov-Wilson equations describes the surface gravity waves travelling horizontally on the seabed.The objective of the present research is to construct a new variety of analytical solutions for the system.The invariants are derived with the aid of Killing form by using the optimal algebra classification via Lie symmetry approach.The invariant solutions involve time,space variables,and arbitrary constants.Imposing adequate constraints on arbitrary constants,solutions are represented graphically to make them more applicable in designing sea models.The behavior of solutions shows asymptotic,bell-shaped,bright and dark soliton,bright soliton,parabolic,bright and kink,kink,and periodic nature.The constructed results are novel as the reported results[26,28,29,30,33,38,42,49]can be deduced from the results derived in this study.The remaining solutions derived in this study,are absolutely different from the earlier findings.In this study,the physical character of analytical solutions of the system could aid coastal engineers in creating models of beaches and ports.

关键词： Coupled Drinfel’d-Sokolov-Wilson model Invariants Killing form Optimal sub algebra Lie symmetry reductions

Nasogastric tube syndrome:A Meta-summary of case reports

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World Journal of Clinical Cases 2024年第1期12卷 119-129页

作者： Deven Juneja Prashant Nasa Gunjan Chanchalani ravi Jain Department of Critical Care Medicine Max Super Speciality HospitalNew Delhi 110017India Department of Critical Care Medicine NMC Specialty HospitalDubai 7832United Arab Emirates Department of Critical Care Medicine Karamshibhai Jethabhai Somaiya Hospital and Research CentreMumbai 400022India Department of Critical Care Medicine Mahatma Gandhi Medical College and HospitalJaipur 302022RajasthanIndia

BACKGROUND Since its description in 1790 by Hunter,the nasogastric tube(NGT)is commonly used in any healthcare setting for alleviating gastrointestinal symptoms or enteral feeding.However,the risks associated with its placement are often underes-timated.Upper airway obstruction with a NGT is an uncommon but potentially life-threatening complication.NGT syndrome is characterized by the presence of an NGT,throat pain and vocal cord(VC)paralysis,usually bilateral.It is poten-tially life–threatening,and early diagnosis is the key to the prevention of fatal upper airway obstruction.However,fewer cases may have been reported than might have occurred,primarily due to the clinicians'unawareness.The lack of specific signs and symptoms and the inability to prove temporal relation with NGT insertion has made diagnosing the syndrome quite challenging.AIM To review and collate the data from the published case reports and case series to understand the possible risk factors,early warning signs and symptoms for timely detection to prevent the manifestation of the complete syndrome with life-threatening airway obstruction.METHODS We conducted a systematic search for this meta-summary from the database of PubMed,EMBASE,Reference Citation Analysis(https://***/)and Google scholar,from all the past studies till August 2023.The search terms included major MESH terms"Nasogastric tube","Intubation,Gastrointestinal","Vocal Cord Paralysis",and“Syndrome”.All the case reports and case series were evaluated,and the data were extracted for patient demographics,clinical symptomatology,diagnostic and therapeutic interventions,clinical course and outcomes.A datasheet for evaluation was further prepared.RESULTS Twenty-seven cases,from five case series and 13 case reports,of NGT syndrome were retrieved from our search.There was male predominance(17,62.96%),and age at presentation ranged from 28 to 86 years.Ten patients had diabetes mellitus(37.04%),and nine were hypertensive(33.33%).Only three(11.11%)patients were reported to be immunocompromised.

关键词： Nasogastric tube Nasogastric tube syndrome Ryle’s tube Sofferman syndrome Vocal cord paralysis

Methyl-salicylate:A surveillance system fortriggering immunity in neighboring plants

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Journal of Integrative Plant Biology 2024年第2期66卷 163-165页

作者： Saumya Jaiswal Durgesh Kumar Tripathi ravi Gupta JingHe Zhong-Hua Chen Vijay Pratap Singh Plant Physiology Laboratory Department of Botany C.M.P.Degree CollegeA Constituent Post Graduate College ofUniversity of AllahabadPrayagraj 211002India Crop Nanobiology and Molecular Stress Physiology LabAmity Institute of Organic Agriculture Amity University UttarPradeshNoida 201313India College of General Education Kookmin UniversitySeoul 02707South Korea School of Science Western Sydney UniversitySydney 2751New South WalesAustralia Hawkesbury Institute for the Environment Western SydneyUniversitySydney 2751New South WalesAustralia

Plant behavioral actions have been one of the major topicsof research in plant biology and agriculture.These actionsfrom plants are determined by their instant structural andphysical reactions to the circumstances(Bouwmeester et al.,2019).Upon sensing abiotic factors such as salinity,flooding,high temperature,drought,plants make suitable changes intheir physiology and behavior to survive such harsh conditions.

关键词： immunity neighboring salinity

E-voting system using cloud-based hybrid blockchain technology

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Journal of Safety Science and Resilience 2024年第1期5卷 102-109页

作者： Beulah Jayakumari S Lilly Sheeba Maya Eapen Jani Anbarasi Vinayakumar ravi A.Suganya Malathy Jawahar Department of Information Technology Tagore Engineering College Chennai India School of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram ChennaiIndia Department of Information Technology Jerusalem College of Engineering ChennaiIndia School of Computer Science and Engineering Vellore Institute of Technology Chennai India Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia Leather Process Technology Division CSIR-Central Leather Research Institute ChennaiIndia

With the invention of Internet-enabled devices,cloud and blockchain-based technologies,an online voting system can smoothly carry out election processes.During pandemic situations,citizens tend to develop panic about mass gatherings,which may influence the decrease in the number of votes.This urges a reliable,flexible,transparent,secure,and cost-effective voting system.The proposed online voting system using cloud-based hybrid blockchain technology eradicates the flaws that persist in the existing voting system,and it is carried out in three phases:the registration phase,vote casting phase and vote counting phase.A timestamp-based authentication protocol with digital signature validates voters and candidates during the registration and vote casting phases.Using smart contracts,third-party interventions are eliminated,and the transactions are secured in the blockchain network.Finally,to provide accurate voting results,the practical Byzantine fault tolerance(PBFT)consensus mechanism is adopted to ensure that the vote has not been modified or corrupted.Hence,the overall performance of the proposed system is significantly better than that of the existing system.Further performance was analyzed based on authentication delay,vote alteration,response time,and latency.

关键词： E-voting Cloud Blockchain Smart contract Consensus mechanism

A functional gel polymer electrolyte based on PVDF-HFP/gelatin toward dendrite-free lithium metal batteries

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Nano Research 2024年第4期17卷 2790-2799页

作者： Xiaoyi Hu Kangli Liu Shijie Zhang Guosheng Shao S.ravi P.Silva Peng Zhang State Center for International Cooperation on Designer Low-carbon and Environmental Materials(CDLCEM) School of Materials Science and EngineeringZhengzhou UniversityZhengzhou 450001China Zhengzhou Materials Genome Institute(ZMGI) ZhongyuanzhiguXingyang 450100China Nanoelectronics Center Advanced Technology InstituteUniversity of SurreyGuildfordGU27XHUK

The leakage of liquid electrolyte and the formation of lithium dendrites pose challenges to safety and stability of lithium metal batteries(LMBs).The appearance of gel polymer electrolyte(GPE)has obviously improved the safety of traditional LMBs.However,the limited inhibition of GPE on lithium dendrites is detrimental to the safety of LMBs.Herein,a kind of poly(vinylidene fluoride-co-hexafluoropropylene)(PVDF-HFP)/gelatin(GN)GPE with high ionic conductivity,high-temperature resistance,and flame-retardancy,was prepared by electrospinning and soaking method.Utilizing the electrospinning network of PVDF-HFP,its affinity to liquid electrolytes,makes this GPE more beneficial to ions transport and the formation of gel.And,the GN with sol–gel properties,enhances the mechanical property(13.5 MPa)of HFP-GN GPE.Meanwhile,X-ray photoelectron spectroscopy(XPS)and density functional theory(DFT)suggest that the attraction of polar groups of GN to Li+can regulate the distribution of Li+and protect Li anodes.Consequently,the application of HFP-GN GPEs to LMBs with cathodes of LiFePO_(4) and LiCoO_(2) deliver excellent electrochemical performances:after 300 cycles,the LiFePO_(4)/HFP-GN GPE/Li battery keeps a low capacity decay rate of 0.09%at 5 C;after 400 cycles at 2 C,the LiCoO_(2)/HFP-GN GPE/Li cell retains a high capacity retention of 74%.This GPE is demonstrated for the application prospect of safe LMBs.

关键词： poly(vinylidene fluoride-co-hexafluoropropylene)(PVDF-HFP) gelatin polar groups lithium metal battery lithium dendrite

Deep Learning-Based Classification of Rotten Fruits and Identification of Shelf Life

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Computers, Materials & Continua 2024年第1期78卷 781-794页

作者： S.Sofana Reka Ankita Bagelikar Prakash Venugopal V.ravi Harimurugan Devarajan Centre for Smart Grid Technologies School of Electronics EngineeringVellore Institute of TechnologyChennai600127India School of Electronics Engineering Vellore Institute of TechnologyChennai600127India Department of Electrical Engineering Dr.B R Ambedkar National Institute of TechnologyJalandharPunjab144008India

The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional value.The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers.The impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the consumers.The overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf life.The agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf life.Hence,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten fruits.The proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and guavas.Similarly,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf life.The results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best model.In comparison to other pre-trained models,the visual geometry group16(VGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf life.By developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated produce.Thereby,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.

关键词： Rotten fruit detection shelf life deep learning convolutional neural network machine learning gaussian naïve bayes random forest visual geometry group16

Secure and resilient improved image steganography using hybrid fuzzy neural network with fuzzy logic

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Journal of Safety Science and Resilience 2024年第1期5卷 91-101页

作者： Sachin Dhawan Hemanta Kumar Bhuyan Subhendu Kumar Pani Vinayakumar ravi Rashmi Gupta Arun Rana Alanoud Al Mazroa Dorset College King George BlvdSurreyBritish ColumbiaCanada Department of Information Technology Vignan’s Foundation for ScienceTechnology and Research(Deemed to be University)Andhra PradeshIndia Krupajal Computer Academy Biju Patnaik University of Technology(BPUT)Rourkela 751002India Center for Artificial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia NSUT East Campus(Formerly AIACTRDelhi 110031India(Affiliated to Guru Gobind Singh Inderaprastha University))Dwarka 110078India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida 201310Uttar PradeshIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)P.O.Box 84428Riyadh 11671Saudi Arabia

The exponential growth in communication networks,data technology,advanced libraries,and mainly World Wide Web services has played a pivotal role in facilitating the retrieval of various types of information as needed.However,this progress has also led to security concerns related to the transmission of confidential data.Nevertheless,safeguarding these data during communication through insecure channels is crucial for obvious reasons.The emergence of steganography offers a robust approach to concealing confidential information,such as images,audio tracks,text files,and video files,in suitable media carriers.A novel technique is envisioned based on back-propagation learning.According to the proposed method,a hybrid fuzzy neural network(HFNN)is applied to the output obtained from the least significant bit substitution of secret data using pixel value dif-ferences and exploiting the modification direction.Through simulation and test results,it has been observed that the proposed methodology achieves secure steganography and superior visual quality.During the experiments,we observed that for the secret image of the cameraman,the PSNR&MSE values of the proposed technique are 61.963895 and 0.041361,respectively.

关键词： Image enhancement Image processing Steganography Deep learning Fuzzy neural combination