Recent progress in energy, environment, and electronic applications of MXene nanomaterials
Since the discovery of graphene, two-dimensional (2D) materials have gained widespread
attention, owing to their appealing properties for various technological applications. Etched …
attention, owing to their appealing properties for various technological applications. Etched …
COVID-19-the role of artificial intelligence, machine learning, and deep learning: a newfangled
DN Vinod, SRS Prabaharan - Archives of Computational Methods in …, 2023 - Springer
The absolute previously infected novel coronavirus (COVID-19) was found in Wuhan, China,
in December 2019. The COVID-19 epidemic has spread to more than 220 nations and …
in December 2019. The COVID-19 epidemic has spread to more than 220 nations and …
Promising materials and synthesis methods for resistive switching memory devices: a status review
In recent years, the emergence of memory devices, especially resistive random-access
memories (RRAM), has been a front-runner in many technological applications. This is due …
memories (RRAM), has been a front-runner in many technological applications. This is due …
Density functional theory and molecular dynamics simulations for resistive switching research
MA Villena, O Kaya, U Schwingenschlögl… - Materials Science and …, 2024 - Elsevier
Resistive switching (RS) devices, often referred to as memristors, have exhibited interesting
electronic performance that could be useful to enhance the capabilities of multiple types of …
electronic performance that could be useful to enhance the capabilities of multiple types of …
Flexible aluminum-doped hafnium oxide ferroelectric synapse devices for neuromorphic computing
The HfO2-based ferroelectric tunnel junction has received outstanding attention owing to its
high-speed and low-power characteristics. In this work, aluminum-doped HfO2 (HfAlO) …
high-speed and low-power characteristics. In this work, aluminum-doped HfO2 (HfAlO) …
Effect of heterojunction order between CaTiO3 and Mn doped SrTiO3 on memristive performance and its mechanism analysis
Y Yang, Z Cao, S Mao, J Qin, Z Rao, M Liu, C Ke… - Applied Materials …, 2023 - Elsevier
It is well-known that memristive devices can be applied to brain-like parallel computing, but
the interface effects have an indelible impact on memristive performance. In this work, two …
the interface effects have an indelible impact on memristive performance. In this work, two …
Machine learning empowers efficient design of ternary organic solar cells with PM6 donor
Organic solar cells (OSCs) hold great potential as a photovoltaic technology for practical
applications. However, the traditional experimental trial-and-error method for designing and …
applications. However, the traditional experimental trial-and-error method for designing and …
Revealing the improved stability of amorphous boron-nitride upon carbon doping
We report on a large improvement of the thermal stability and mechanical properties of
amorphous boron-nitride upon carbon doping. By generating versatile force fields using first …
amorphous boron-nitride upon carbon doping. By generating versatile force fields using first …
Unraveling the importance of fabrication parameters of copper oxide-based resistive switching memory devices by machine learning techniques
In the present study, various statistical and machine learning (ML) techniques were used to
understand how device fabrication parameters affect the performance of copper oxide …
understand how device fabrication parameters affect the performance of copper oxide …
Intensive harmonized synapses with amorphous Cu 2 O-based memristors using ultrafine Cu nanoparticle sublayers formed via atomically controlled electrochemical …
Resistive random-access memory (RRAM) devices have significant advantages for
neuromorphic computing but have fatal problems of uncontrollability and abrupt resistive …
neuromorphic computing but have fatal problems of uncontrollability and abrupt resistive …