Transition metal selenides(TMSs)are effective pre-electrocatalysts and are commonly used in electro-chemical *** the electrocatalytic oxygen evolution reaction(OER),metal cations in TMSsare in-situ reconstructed and c...
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Transition metal selenides(TMSs)are effective pre-electrocatalysts and are commonly used in electro-chemical *** the electrocatalytic oxygen evolution reaction(OER),metal cations in TMSsare in-situ reconstructed and converted into high-valence metal ***,a limited understanding of the effects of electro-oxidation and anion leaching has resulted in insufficient theoretical guidance for the rational design of efficient ***,FeSe@NiSe nanorods were fabricated for the OER using a facile hydrothermal sel-enization method supported on FeNi ***-situ Raman spectroscopy and multiple characterization techniques were employed to elucidate the mechanism of FeSe@NiSe surface *** cations on the catalyst surface were reconstructed and converted into OER-active species Fe/NiOOH at low *** the applied potential increased,electro-oxidation andleaching of Se occurred,resulting in SeO42-adsorption on the catalyst surface,which further enhanced catalytic *** a result,the reconstructed FeSe@NiSe/iron-nickel foam(INF)exhib-ited exceptional catalytic activity for OER,achieving an ultralow overpotential of 283 mV at a current density of 100 mA·***,the bifunctional FeSe@NiSe/INF electrode facilitated overall water splitting,affording a current density of 10 mA·cm-2 only at 1.53 V,even superior to the noble RuO2(+)‖Pt/C(-).This work offers valuable insights into the surface evolution and electro-catalytic mechanisms of TMSs.
Brief Biography: Vishrant Tripathi obtained his PhD from the EECS department at MIT, working with Prof. Modiano at the Lab for Information and Decision Systems (LIDS). He is currently working on building efficient dat...
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Brief Biography: Vishrant Tripathi obtained his PhD from the EECS department at MIT, working with Prof. Modiano at the Lab for Information and Decision Systems (LIDS). He is currently working on building efficient data center networks at Google. His research interests primarily lie in the optimization of resources in resource constrained networked systems. The main applications of his work are in multi-agent robotics, federated learning, edge computing, cloud infrastructure, and monitoring for IoT. More recently, he has also been working on software defined networking and next-generation wireless networks. In 2022, he won the Best Paper Runner Up Award at ACM MobiHoc. Copyright is held by author/owner(s).
This paper proposes a solution to enhance and compare different neural network (NN)-based side-slip angle estimators. The feed-forward neural networks (FFNNs), recurrent neural networks, long short-term memory units (...
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In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital...
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In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital-izations,and increased healthcare *** reminder systems often fail due to a lack of personalization and real-time *** address this critical challenge,we introduce MediServe,an advanced IoT-enabled medication management system that seamlessly integrates deep learning techniques to provide a personalized,secure,and adaptive *** features a smart medication box equipped with biometric authentication,such as fingerprint recognition,ensuring authorized access to prescribed medication while preventing misuse.A user-friendly mobile application complements the system,offering real-time notifications,adherence tracking,and emergency alerts for caregivers and healthcare *** system employs predictive deep learning models,achieving an impressive classification accuracy of 98%,to analyze user behavior,detect anomalies in medication adherence,and optimize scheduling based on an individual’s habits and health ***,MediServe enhances accessibility by employing natural language processing(NLP)models for voice-activated interactions and text-to-speech capabilities,making it especially beneficial for visually impaired users and those with cognitive ***-based data analytics and wireless connectivity facilitate remote monitoring,ensuring that caregivers receive instant alerts in case of missed doses or medication ***,machine learning-based clustering and anomaly detection refine medication reminders by adapting to users’changing health *** combining IoT,deep learning,and advanced security protocols,MediServe delivers a comprehensive,intelligent,and inclusive solution for medication *** innovative approach not only improves the quality of life for elderly
Construction and demolition (C&D) waste management is challenging in urban areas due to the high volume of waste generated and widespread illegal dumping. City authorities are struggling with environmental, econom...
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The Ethereum blockchain platform has witnessed a surge in crypto-cybercrimes, particularly phishing attacks, resulting in significant financial losses. Analyzing the Ethereum transaction network to detect phishing use...
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In the realm of education, the pursuit of effective learning outcomes often faces the challenge of limited resources. This paper explores the intersection of maximizing learning outcomes and minimizing costs through a...
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Agriculture encompasses a way of life and a profession for the general population. Most global traditions and cultures revolve around agriculture. With the help of advanced farming, agriculture may become more profita...
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Knee joint rehabilitation exercise refers to a therapeutic procedure of a patient having dysfunctions in certain abilities to move knee joint due to some medical conditions like trauma or paralysis. The exercise is ba...
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