Results 261 to 270 of about 279,338 (297)

2D Material Decorated ZnO for Screen Printable Wearable Textile‐Based Piezoelectric Nanogenerator

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The project presents a textile‐based piezoelectric nanogenerator (T‐PENG) for sustainable energy harvesting in wearable electronics. Utilizing 2D materials, including MoS2 and screen printable graphene ink, the device achieves enhanced performance. Experimental results and COMSOL simulation validate significant improvement in the output efficiency ...
Iftikhar Ali, Xicai Alex Yue, Benedict R. Gaster, Md Delowar Hussain, Bhaskar Dudem, S. Ravi P. Silva, Carinna Parraman   +6 more
wiley   +1 more source

Two‐Dimensional Piezoelectric Nanomaterials for Nanoelectronics and Energy Harvesting

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Two‐Dimensional Piezoelectric Nanomaterials from properties to applications. Smart materials, especially piezoelectric materials, have gained popularity over the last two decades. Two‐dimensional (2D) piezoelectric materials exhibit attributes including great flexibility, ease of workability, extensive surface area, and many active sites, indicating ...
Yujun Cao, Sikandar Aftab, Zeeshan Ali, Muhammad Farooq Khan, Ghazanfar Nazir, Awais Khalid, Hosameldin Helmy Hegazy, Ibrahim S. Yahia, Altaf Hussain Rajpar, Burragoni Sravanthi Goud, Jae Hong Kim, Erdi Akman, Xin Li   +12 more
wiley   +1 more source

Pengembangan purwarupa sistem peringatan dini longsor berbasis Internet of Things (IoT)

Asep Andang, Eka Wahyu Hidayat, Andhy Romdani, Prama Permana, Andre Taufik Firdaus, Mahendra Pratama, Elpan Ahmad Rifansyah   +6 more
openalex   +2 more sources

Engineered Metal–Organic Frameworks‐Based Materials for Environmental Detection

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Engineered metal–organic frameworks (MOFs) regulated by various material modification strategies are discussed for environmental contaminant detection under different sensing mechanisms, providing future improvements of MOFs in environmental detection. Sensitive and selective detection of contaminants is crucial for environmental protection.
Pan Gao, Song Wang, Yuechao Yao, Yibo Dou   +3 more
wiley   +1 more source

Development of Threats and Vulnerability Assessment Model for Electric Vehicles (EVs) Transportation Internet of Things (T-IoT)

Nurina Zulaikha, Raja Zahilah Raja Md Radzi, Siti Hajar Othman, Hazinah Kutty Mammi, Maheyzah Md Siraj   +4 more
openalex   +1 more source

The Role of Digital Twin Technology in Enhancing Energy Efficiency in Buildings: A Systematic Literature Review

Energy Science &Engineering, EarlyView.
Digital Twin (DT) technology enhances building energy efficiency by enabling continuous monitoring, predictive maintenance, and operational optimization within Building Energy Management Systems. Through real‐time data integration and simulation, DTs provide dynamic feedback loops that optimize performance, reduce operational costs, and improve ...
Suqi Wang, Congxiang Tian, Chao Zhou, Yihan Wu, Divine Senanu Ametefe, Dah John, Marvellous Agbeko Ametefe   +6 more
wiley   +1 more source

Energy Storage System in Microgrids: Challenges and Opportunities

Energy Science &Engineering, EarlyView.
Hybrid integration of multiple Energy Storage Systems (ESSs) within renewable‐powered microgrids enhances reliability, flexibility, and economic sustainability. Lithium‐ion batteries, flow batteries, hydrogen storage, and thermal systems complement each other through coordinated control via Energy Management Systems.
Mohamed G. Moh Almihat, Josiah L. Munda
wiley   +1 more source

Performance Monitoring of Photovoltaic Modules Using Machine‐Learning‐Based Solutions: A Survey of Current Trends

Energy Science &Engineering, EarlyView.
The graphical abstract presents the concept of applying machine‐learning algorithms to assess the performance of photovoltaic modules. Data from solar panels are fed to surrogates of intelligent models, to assess the following performance metrics: identifying faults, quantifying energy production and trend degradation over time. The combination of data
Nangamso Nathaniel Nyangiwe, Abraham Dimitri Kapim Kenfack, Nicolas Thantsha, Mandla Msimanga   +3 more
wiley   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source