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Full-Text Articles in Entire DC Network
20 Years Of Neutrosophic Statistics: A Bibliometric Analysis, Hammad Khalid, Arshad Hameed
20 Years Of Neutrosophic Statistics: A Bibliometric Analysis, Hammad Khalid, Arshad Hameed
Neutrosophic Systems with Applications
Florentin Smarandache introduced neutrosophic statistics (NS), a formalism for representing uncertainty and indeterminacy in observations, parameters and statistics in an extension to classical and interval statistics. Although widespread in various contexts, such as statistical quality control, hypothesis testing, medical diagnosis, and decision science, and increasingly used and developed, the scientific evolution and conceptual framework of the science of decision making remain largely unexamined. To fill this gap, the present study has been conducted with a comprehensive bibliometric analysis of NS research articles published between 2003 to 2025 from Scopus which has been conducted following the SPAR-4-SLR protocol. In all, 501 …
The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban
The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban
Faculty Publications
Nondestructive evaluation (NDE) methods are powerful tools for detecting and characterizing flaws in structural components, but their reliability must be evaluated before they can be used in critical applications. For more than 50 years, probabilistic and statistical methods have been used effectively to estimate reliability by describing an NDE system’s Probability of Detection (POD) for flaws of realistic sizes. The POD methods used by the USAF and NASA, like Hit/Miss, Signal-Response (â vs. a), and Point Estimate method (PEM, a.k.a. 29/29) have evolved, alongside newer approaches like Limited Sample POD (LS-POD) method, and Model Assisted Probability of Detection …
Monitoring System In The Georeactor Area During The Underground Coal Gasification Process, Aleksandra Tokarz, Jacek Grabowski, Krzysztof Korczak
Monitoring System In The Georeactor Area During The Underground Coal Gasification Process, Aleksandra Tokarz, Jacek Grabowski, Krzysztof Korczak
Journal of Sustainable Mining
Safety control of the underground coal gasification (UCG) process involves ensuring that the process runs smoothly, monitoring changes occurring on the surface and in the rock mass, and counteracting the negative environmental impact of the process. The article presents the application of a monitoring system implemented in Poland, both in pilot tests conducted in shallow coal seams at the Barbara Experimental Mine and in deep coal seams at the Wieczorek mine, where a full-scale gasification process was tested. The analysis of the monitoring results carried out during the gasification experiment in an operating mine allowed for the identification of key …
Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos
Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos
Undergraduate Scholarship and Creative Works
Physics-informed neural networks solve the Helmholtz equation without labeled data, but a low residual alone does not confirm that a solution preserves the physical distinction a downstream task depends on. We trained a four-layer SIREN with physics-based residuals, a Sommerfeld condition, Adam, and L-BFGS, modeling a Gaussian source and a plane wave scattering from a small dielectric inclusion. Fine-tuning from four base models produced 600 complex fields spanning omega = 4 to 20. A compact CNN, three ResNet-18 variants, and a frozen OpenCLIP encoder classified these fields under five random seeds. The CNN achieved (95.65 +/- 0.77)% accuracy, outperforming OpenCLIP …
Edge Computing-Enabled Secure Federated Learning For Anomaly Detection In Industrial Iot Sensor Streams, Wijdan Noaman Marzoog Al Mukhtar
Edge Computing-Enabled Secure Federated Learning For Anomaly Detection In Industrial Iot Sensor Streams, Wijdan Noaman Marzoog Al Mukhtar
AUIQ Technical Engineering Science
The rise of the Industrial IoT (IIoT) will result in a surge of IIoT devices with high-velocity data streams requiring rapid, real-time analysis of these data streams to power predictive maintenance and assure cybersecurity. Centralized cloud-based approaches to anomaly detection are hindered by their inherent latency and privacy issues while independent or stand-alone approaches to edge-based anomaly detection do not have enough data to effectively detect anomalies. This paper presents a federated learning framework to collaboratively develop an anomaly detection model from multiple edge nodes, without sharing the raw sensor data, so that data sovereignty is preserved. Two major contributions …
Microwave Thermal Pre-Treatment To Improve Nickel Extraction From Lateritic Ore, Johana Borda, Daniel Sosa, Robinson Torres
Microwave Thermal Pre-Treatment To Improve Nickel Extraction From Lateritic Ore, Johana Borda, Daniel Sosa, Robinson Torres
Journal of Sustainable Mining
Two heat treatment processes for a nickeliferous laterite sample are presented, one by the conventional muffle route and the other by microwave. The heating was carried out in order to improve the dissolution of nickel in an acid medium. The study describes the changes observed in the mineral for the increase in temperature as a consequence of radiation in the microwave and in the muffle. The changes in the mineral crystalline phases were analyzed by X-ray diffraction. The leaching media consisted of a 1 M sulfuric acid solution at ambient conditions for 7 h. The interaction between the reagent and …
Ecofriendly Synthesis Of Silver Nanoparticles As Antimicrobial Active Agents From Its Cationic Precursors, Abdul Haris Watoni Watoni
Ecofriendly Synthesis Of Silver Nanoparticles As Antimicrobial Active Agents From Its Cationic Precursors, Abdul Haris Watoni Watoni
Chimica et Natura Acta
This review presents a comprehensive survey on the green synthesis of silver nanoparticles from silver nitrate precursor using plant extracts along with their characterization and antimicrobial activity assessment. The synthesis of silver nanoparticles through a green chemistry approach is increasingly in demand because it is environmentally friendly, easy to do, and efficient, especially for the purpose of antimicrobial active ingredients in disinfectant and antiseptic formulas. Green synthesis of silver nanoparticles can be carried out using silver nitrate as a silver precursor and plant extracts as a source of bioreductants and capping agents. The synthesis products are then characterized using UV-Vis …
The Baltic Bear Trap Wargame, Connor Crookham
The Baltic Bear Trap Wargame, Connor Crookham
Space and Defense
Modern military education increasingly relies on experiential tools that allow students to explore the complexity of contemporary conflict in ways that lectures and readings alone cannot achieve. Nowhere is this more evident than in the emerging emphasis on multi-domain operations, integrated deterrence, and the blurred boundaries between competition and armed conflict. The Baltic Bear Trap wargame was developed as a student design project to meet this instructional need, offering a structured environment in which players must think, plan, and act as operational-level decision makers confronting a deteriorating security situation in the Nordic–Baltic region. Built for use at the Swedish Defense …
Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu
Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu
Engineering Management and Systems Engineering Faculty Research & Creative Works
Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on large sample sizes and population-level analyses may overlook variants with lower minor allele frequencies or individual-specific relevance. Individualized Bayesian Inference (IBI) offers a promising method to complement GWAS by identifying and prioritizing candidate genetic markers at both the individual and patients-like-me subgroup levels. This study evaluates the application of IBI to PD genetics, using GWAS as a baseline for comparison. We analyzed genetic data from the Fox Insight online …
A Framework For Automated Quantity Extraction From .Ifc Models And Normalized Bid Comparison, Asmaa Mohamed Farouk
A Framework For Automated Quantity Extraction From .Ifc Models And Normalized Bid Comparison, Asmaa Mohamed Farouk
Theses and Dissertations
Accurate bid comparison remains a major challenge in construction tendering due to
differences in Bill of Quantities formats, item naming conventions, and pricing methods across
contractor submissions. These variations require time-consuming manual work and often lead to
subjective decisions. This research presents a computational framework that uses Building
Information Modeling through the .ifc file format, combined with text analysis techniques for
automated bid normalization.
The developed system uses a dual-component approach. Phase 1 extracts quantities from .ifc
model files using 3D geometric calculations, automated element classification. Phase 2 uses text
mining with a domain-specific dictionary of construction terms to interpret …
Mechatronics: Fundamentals, Design, Integration, And Validation, Guoming Zhu
Mechatronics: Fundamentals, Design, Integration, And Validation, Guoming Zhu
Mechatronics
This textbook is a product of Co-DREAM OER (Collaborative Development of Robotics, Mechatronics, and Advanced Manufacturing Open Educational Resources), an initiative funded by the U.S. Department of Education to develop open educational resource textbooks on robotics, mechatronics, and advanced manufacturing processes. The texts are written for students enrolled in 2-year associate’s, 4-year bachelor’s, and graduate-level courses. This specific text has been created by a team of scholars, students, support staff, and other professionals from across the country. It is intended for mechatronics courses for 4-year bachelor’s and graduate-level programs.
The Instability And Unsustainability Of Our Planned, Or Imagined Media Future, Thom Gencarelli
The Instability And Unsustainability Of Our Planned, Or Imagined Media Future, Thom Gencarelli
Proceedings of the New York State Communication Association
In the face of the growth and planned growth of industrial developments in artificial intelligence, embodied AI, immersive media/virtual reality, and the fintech industry and cryptocurrencies – and the energy requirements for each of these and all of them together – this paper examines the question of whether the plans for growth and future development in these areas is probable, possible, problematic, or impossible. Additionally, the examination is situated atop both state-based and criminal threats to use the Internet and mobile Internet to wreak havoc and instability.
Geometric And Operational Design Principles For Autonomous Haulage Systems In Open-Pit Mining: A Systematic Review, Justina Senam Lotsu, Samuel Frimpong, Muhammad Azeem Raza
Geometric And Operational Design Principles For Autonomous Haulage Systems In Open-Pit Mining: A Systematic Review, Justina Senam Lotsu, Samuel Frimpong, Muhammad Azeem Raza
Mining Engineering Faculty Research & Creative Works
The rapid deployment of autonomous haulage systems (AHSs) in open-pit mining has significantly altered haul road geometric design requirements, as autonomous trucks operate under strict kinematic constraints related to turning radius, gradient, and braking performance. Since haulage accounts for 50–60% of total mining costs, optimizing haul road geometry is critical for improving operational efficiency, energy consumption, and safety. This study presents a systematic review of 50 highly relevant studies selected from 81 candidate publications published between 2003 and 2025 through structured database searches and citation chaining. The review synthesizes current developments in haul road layout optimization, turning radius accommodation, gradient …
Metrological Characterization Of Pavement Friction Measurements For High-Friction Surface Treatments: Si Traceability, Uncertainty Evaluation, And Adhesion–Hysteresis Separation Via Water–Soap Bpt Protocol, Alireza Roshan, Magdy Abdelrahman
Metrological Characterization Of Pavement Friction Measurements For High-Friction Surface Treatments: Si Traceability, Uncertainty Evaluation, And Adhesion–Hysteresis Separation Via Water–Soap Bpt Protocol, Alireza Roshan, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Laboratory friction measurements are central to material screening for High-Friction Surface Treatments (HFST), yet metrological aspects including a proposed metrological traceability framework or uncertainty, and reproducibility are consistently underreported. This study applies a metrology-aligned framework to British Pendulum Tester (BPT) measurements performed in three states: dry, wet (water), and water–soap to assess operational adhesion and hysteresis components, document traceability to the International System of Units (SI), and report GUM-style uncertainty with covariance for the adhesion difference. Measurements were obtained for calcined bauxite (CB) and rhyolite (Rhy) in HFST and Coarse gradations across seven polishing protocols (baseline; LAA-1000/2000; MDA-105/180; PSV-10 h/20 …
Flexural Performance Of Deficient Rc Beams Repaired With Gfrp Composite, Zena Aljazaeri, Hayder Alghazali, Zuhair Al-Jaberi, John J. Myers
Flexural Performance Of Deficient Rc Beams Repaired With Gfrp Composite, Zena Aljazaeri, Hayder Alghazali, Zuhair Al-Jaberi, John J. Myers
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Fiber-reinforced polymer composite materials have been improved for use in repairing and strengthening existing infrastructure over the past few decades. This case study focuses on the effect of confinement with GFRP strips on the structural performance of out-of-service beams in bridge applications due to the impact of over-height vehicles or inadequate lap-spliced reinforcements. In this study, beams with inadequate lap splices in the tension zone were utilized to mimic the damaged area in out-of-service RC beams. The proposed repair technique is a glass fiber-reinforced polymer (GFRP) composite in the form of longitudinal sheets and U-wrapped strips. The experimental study determined …
Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu
Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Polymer gels are essential functional materials for subsurface energy operations, playing a critical role in conformance control, fluid diversion, hydraulic fracturing, and leakage mitigation. As reservoirs become increasingly complex and the demand for sustainable energy grows, continued innovation in gel technologies is crucial. This editorial introduces a Special Issue titled "Advances and Applications of Polymer Gels for Subsurface Energy and Storage," which compiles seven original research articles exploring recent developments in gel synthesis, characterization, and applications. The featured studies highlight the versatility of polymer gels, including nanoparticle-reinforced composites, foam–gel hybrids, recrosslinkable preformed particle gels, and advanced fracturing fluids. The contributions …
Optimal Procedure For Measuring The Parameters Of Optical Signals Considering Noise, Yuriy Gennadyevich Shipulin, Azimjon Mamadaliyevich Xusanov
Optimal Procedure For Measuring The Parameters Of Optical Signals Considering Noise, Yuriy Gennadyevich Shipulin, Azimjon Mamadaliyevich Xusanov
Chemical Technology, Control and Management
It has been shown that to achieve the required level of measurement accuracy and reliability, it is necessary to transition from quality control of finished products to quality management based on cost-effective methods during the stages when product properties are formed. It is shown that the complexity of measuring optical signal parameters during analysis or synthesis requires them to be considered as part of a general information processing system. Based on the nonlinear filtration method, an optimal procedure for measuring a variable position in time against a background of spatial noise was obtained. Structural diagrams of optimal measuring instruments for …
Determination Of The Content Of Water-Soluble Vitamins In The Composition Of Beet Beetroot Composition, Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, Muhammad Rasul Oglu Najafli, Doston Ishmuhammat Ugli Samandarov
Determination Of The Content Of Water-Soluble Vitamins In The Composition Of Beet Beetroot Composition, Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, Muhammad Rasul Oglu Najafli, Doston Ishmuhammat Ugli Samandarov
Chemical Technology, Control and Management
The aim of this study was to determine the content of water-soluble vitamins in various parts of beetroot (pulp, leaves and stems) that had been subjected to various drying methods in a bid to explore the effect of physical processes, i.e., the application of ultrasound, on micronutrient preservation. The experiments were performed at the Department of Service Technologies of Tashkent State Technical University, and chromatographic analysis was performed in the Institute of Bioorganic Chemistry of the Academy of Sciences of the Republic of Uzbekistan. Chromatography was performed on Agilent-1200 chromatograph with Exlipse XDB C18 column and diode array detector using …
Fast Algorithms For Combined Synthesis Of Dynamic Object Control Systems, Isomiddin Khakimovich Siddikov, Gulchexra Alimova
Fast Algorithms For Combined Synthesis Of Dynamic Object Control Systems, Isomiddin Khakimovich Siddikov, Gulchexra Alimova
Chemical Technology, Control and Management
The paper considers the issues of combined synthesis of a control system for a nonlinear dynamic object. The combined synthesis algorithms are based on the hybrid application of the theory of ordinary differential equations in the Cauchy form and the theory of automatic control. In this case, the dynamics of the control system are described in the input-output representation and by state-space equations. Algorithms for solving stabilization problems, finite control, and the inverse dynamics problem are presented in explicit form. These algorithms are based on the concept of reducibility of a general Cauchy-form system to the block-canonical Frobenius form. The …
Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi
Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi
Chemical Technology, Control and Management
Although classical fuzzy logic controllers are capable of modelling non-linear control systems, they fail to consider the reliability of linguistic information, sensor measurements, and expert knowledge. In this paper, an intelligent controller based on the use of Z-numbers is developed for steam-turbine throttle control. Linguistic information and its confidence degree are considered simultaneously in such a controller. The temperature and pressure values are taken as input variables, while the throttle rotation is selected as the controller output variable. At first, the Z-number representation system is constructed to include the credibility of linguistic measurements and control rules. Then, a Mamdani Type-1 …
The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique
The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique
Graduate Masters Theses
This thesis presents the Sliding Aperture Transform (SLAPt), a novel mathematical technique for extracting exponential argument and pre-factor from experimental data. The method transforms measured waveforms into an inverse-domain representation where exponential decay processes appear as distinct peaks, simplifying data analysis and reducing the effects of baseline offsets and noise. The technique is here applied to time dependent capacitance transients associated with irradiated and non-irradiated silicon pn junction diodes. The technique is further developed and applied to positive argument exponentials using an axillary function. This allows forward bias current-voltage measurements, and forward pulse-bias current transient measurements to be SLAP analyzed, …
Using Clustering Techniques And Mitre Att&Ck Threat Interpretation To Detect Anomalies In Modbus/Tcp For Industrial Control Systems, Shivanjali Khare, Tirthankar Ghosh, Jhansi Sreya Jagarapu, Atharva Haridas Sagare
Using Clustering Techniques And Mitre Att&Ck Threat Interpretation To Detect Anomalies In Modbus/Tcp For Industrial Control Systems, Shivanjali Khare, Tirthankar Ghosh, Jhansi Sreya Jagarapu, Atharva Haridas Sagare
Journal of Cybersecurity Education, Research and Practice
Recent attacks on America's critical infrastructure have drawn increased attention on securing industrial control systems and operational technology in power plants, utility companies, and other sectors providing public services. Attack detection and mitigation strategies on these systems have shown promising results using machine learning and other statistical baselining techniques, mostly using supervised learning and classification. Unsupervised learning using cluster analysis and other techniques remain mostly unexplored. In this paper, we propose multi-layered feature extraction and hybrid clustering framework to detect fine-grained nested attack patterns in Modbus-over-TCP traffic. Operating under the assumption of known number of distinct network categories, our approach …
Mathematical Models Of Magnetoelastic Acceleration Transducers Developed Based On The Theory Of Lumped Parameter Circuits, Amirov Fayzullayevich Sulton, Kamila Kamilovna Jurayeva, Shovkat Dilshodovich Turayev
Mathematical Models Of Magnetoelastic Acceleration Transducers Developed Based On The Theory Of Lumped Parameter Circuits, Amirov Fayzullayevich Sulton, Kamila Kamilovna Jurayeva, Shovkat Dilshodovich Turayev
Chemical Technology, Control and Management
In this article, based on the theory of lumped-parameter circuits, algebraic and differential equations describing the mechanical, electrical, and magnetic circuits of new magnetoelastic acceleration transducers, their analytical solutions, as well as mathematical models establishing the relationship between the electromotive forces at the outputs of the transducers and acceleration, which is the input quantity of the transducer, have been developed. Analysis of these mathematical models and the graphs constructed on their basis shows that under the influence of acceleration applied to the transducers, with an increase in the mechanical stresses arising in the magnetic circuit of the transducer, a redistribution …
Nonlinear System Identification Based On Fuzzy Radial Basis Neural Network With Multi-Connected Weight Connections, Kabul Khudaybergenov
Nonlinear System Identification Based On Fuzzy Radial Basis Neural Network With Multi-Connected Weight Connections, Kabul Khudaybergenov
Chemical Technology, Control and Management
This paper builds on our earlier radial basis function network with multiple connections (RBFMC) by placing it within a fuzzy inference framework for nonlinear system identification. The idea is inspired by the diversity of neurotransmitters found in biological neurons: instead of a single hidden-to-output weight, RBFMC gives each hidden unit a multi-dimensional connection whose components act as independent filters. Once fuzzy logic is added, each hidden neuron becomes a fuzzy rule, and its antecedent is built from several Gaussian membership functions, one per connection. The resulting Fuzzy RBFMC produces an interpretable, multi-filter description of local regions of the input space …
Performance Evaluation Of Controllers Using Fuzzy Delphi And Ahp Techniques, Kamala. R. Aliyeva, Nihad Mehdiyev, Shamil Mehdi
Performance Evaluation Of Controllers Using Fuzzy Delphi And Ahp Techniques, Kamala. R. Aliyeva, Nihad Mehdiyev, Shamil Mehdi
Chemical Technology, Control and Management
This study introduces an enhanced decision-support framework that integrates the Fuzzy Delphi method with the Analytic Hierarchy Process (AHP) to improve controller tuning and performance evaluation in uncertain environments. Traditional tuning techniques typically depend on crisp expert judgments and deterministic performance indices; however, industrial control systems are characterized by nonlinear behaviors, uncertain parameter variations, and subjective expert evaluations that are often vague or inconsistent. The Fuzzy Delphi procedure is applied to systematically gather, filter, and consolidate expert insights, enabling a refined set of performance criteria such as stability margins, robustness to disturbances, settling time, overshoot, control effort, and energy consumption …
Motor Imagery Eeg Decoding For Brain-Computer Interfaces: Structured Representation, Transfer, And Drift, Yiming Shen
Motor Imagery Eeg Decoding For Brain-Computer Interfaces: Structured Representation, Transfer, And Drift, Yiming Shen
Graduate Doctoral Dissertations
Motor imagery EEG decoding is often summarized by the accuracy of a final classifier, but the classifier is only the last stage of the pipeline. Before classification, the signal has already been shaped by preprocessing, feature extraction, source-session organization, and adaptation. This dissertation studies how feature representation, source-session transfer, and drift shape reliable MI-EEG decoding for brain-computer interfaces.
It first studies within-session decoding on public MI-EEG datasets using nested validation that keeps preprocessing, feature fitting, and model selection inside the training folds. This analysis separates gains from feature representation from gains due to nonlinear classification, and relates both comparisons to …
One Size Does Not Fit All: Revisiting World Models And Neurosymbolic Ai, Amit P. Sheth, Madhur Thareja, Anushka Pawar, Niyati Rawal
One Size Does Not Fit All: Revisiting World Models And Neurosymbolic Ai, Amit P. Sheth, Madhur Thareja, Anushka Pawar, Niyati Rawal
Publications
World models are being built twice, from opposite ends, without a shared theory of how the two halves should meet. One lineage grounds the world model in perception: a self-supervised, latent-predictive encoder – exemplified by Joint Embedding Predictive Architectures (JEPA) – that learns the structure of sensory experi-ence. A second, older lineage grounds the world model in cognition: an explicit, inspectable structure of entities, rules, and constraints, ranging from knowledge graphs to formal logic to physical law. Neither lineage alone has produced a world model that is simultane-ously adaptive and auditable. We argue this is not solved by picking a …
In Situ Electrochemical Characterization Techniques For Active Hydrogen In Electrocatalytic Nitrate Reduction To Ammonia, Hong-Mei Li, Mei Yi, Zhao-Yu Jin, Ming-Hao Xie, Khalid M. Omer, Yong Guo, Pan-Pan Li
In Situ Electrochemical Characterization Techniques For Active Hydrogen In Electrocatalytic Nitrate Reduction To Ammonia, Hong-Mei Li, Mei Yi, Zhao-Yu Jin, Ming-Hao Xie, Khalid M. Omer, Yong Guo, Pan-Pan Li
Journal of Electrochemistry
Electrocatalytic nitrate reduction to ammonia (NitRR) represents a sustainable pathway that integrates environmental remediation with the production of high-value ammonia. However, the activity and selectivity of this process are limited by the generation, consumption, and dynamic equilibrium of the key transient intermediate—active hydrogen (*H). Precise modulation of *H necessitates a comprehensive understanding of its behavior, which relies fundamentally on advanced in situ electrochemical characterization techniques. However, a systematic review dedicated to the rational selection and application of in situ electrochemical techniques for the specific characterization of *H in NitRR, with clear definitions of each technique's "detectable targets, quantitative accuracy, and …
Neural Network Driven By Electrochemical Performance Data For Predicting The Discharge Termination Time Of Seawater Electrolyte-Based Metal-Air Batteries, Peng-Peng Shen, Yi-Chi Pan, Yu-Rong Liu, Lu-Dan Zhang, Ning Niu, Guan-Jun Wang, De-Kun Yang, Xin-Long Tian, Peng Rao
Neural Network Driven By Electrochemical Performance Data For Predicting The Discharge Termination Time Of Seawater Electrolyte-Based Metal-Air Batteries, Peng-Peng Shen, Yi-Chi Pan, Yu-Rong Liu, Lu-Dan Zhang, Ning Niu, Guan-Jun Wang, De-Kun Yang, Xin-Long Tian, Peng Rao
Journal of Electrochemistry
Seawater electrolyte-based metal-air batteries exhibit great promise for marine energy supply systems. However, conventional statistical analysis methods, though applicable to seawater metal-air battery lifetime prediction, have inherent limitations of insufficient prediction accuracy and large error. Herein, a deep time-series regression framework based on InceptionTime and incorporating prior-biased attention pooling is proposed to construct a nonlinear mapping between electrochemical performance sequences and the discharge termination time of catalysts. Specifically, chronoamperometric profiles are employed to extract long-term stability features, while prior knowledge derived from linear sweep voltammetry is introduced to strengthen the attention weighting over critical potential regions. Under a nested leave-one-catalyst-out …
Microwave-Assisted Synthesis Of Core-Shell Structured Pd@Pdptcufe Recessed Truncated Octahedral Nanocrystals For Multifunctional Electrocatalysis, De-Zhong Hu, Wen-Dan Jiang, Wei Keat Ng, Jun Yang, Xiong-Wu Kang
Microwave-Assisted Synthesis Of Core-Shell Structured Pd@Pdptcufe Recessed Truncated Octahedral Nanocrystals For Multifunctional Electrocatalysis, De-Zhong Hu, Wen-Dan Jiang, Wei Keat Ng, Jun Yang, Xiong-Wu Kang
Journal of Electrochemistry
Developing cost-efficient and durable multifunctional electrocatalysts of hydrogen evolution reaction, oxygen reduction reaction and oxygen evolution reaction is crucial for improving energy conversion efficiency in electrolytic water splitting electrolyzer and advancing rechargeable zinc-air batteries. Polyhedral shaped nanocrystals with well-defined crystal facets represent a type of model catalysts that enables the exploration of structure-activity relationships. However, it is still very challenging to prepare alloy nanocrystals with multiple metal components due to their complicated redox potentials and mixing enthalpy. Herein, we report a rapid microwave-assisted polyol reduction method for syntheses of core-shell Pd@PdPtCu, Pd@PdPtCuNi, Pd@PdPtCuCo and Pd@PdPtCuZn octahedral nanocrystals, and recessed truncated-octahedral …