AIMC Topic: Electricity

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Toward a new generation of electrically controllable hygromorphic soft actuators.

Advanced materials (Deerfield Beach, Fla.)
An innovative processing strategy for fabricating soft structures that possess electric- and humidity-driven active/passive actuation capabilities along with touch- and humidity-sensing properties is reported. The intrinsically multifunctional materi...

Optimizing parameters on alignment of PCL/PGA nanofibrous scaffold: An artificial neural networks approach.

International journal of biological macromolecules
This paper proposes an artificial neural networks approach to finding the effects of electrospinning parameters on alignment of poly(ɛ-caprolactone)/poly(glycolic acid) blend nanofibers. Four electrospinning parameters, namely total polymer concentra...

Artificial Electrical Morris-Lecar Neuron.

IEEE transactions on neural networks and learning systems
In this paper, an experimental electronic neuron based on a complete Morris-Lecar model is presented, which is able to become an experimental unit tool to study collective association of coupled neurons. The circuit design is given according to the i...

Spatiotemporal evolution and driver analysis of wastewater greenhouse gas emissions in Chinese mainland: Insights and future trends.

Environmental research
Wastewater greenhouse gas (GHG) emissions represent a complex system characterized by distinct spatial-temporal patterns influenced by various drivers. This study examined the spatiotemporal heterogeneity of wastewater GHG emission intensity and tota...

Prediction of electrical load demand using combined LHS with ANFIS.

PloS one
Enhancement prediction of load demand is crucial for effective energy management and resource allocation in modern power systems and especially in medical segment. Proposed method leverages strengths of ANFIS in learning complex nonlinear relationshi...

Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems.

The Journal of chemical physics
Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduct analog resistive switching, and examine the potential of memristors for use in neuromorphic system...

[Research and application of photovoltaic cell online monitoring system for animal robot stimulator].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Power supply plays a key role in ensuring animal robots to obtain effective stimulation. To extending the stimulating time, there is a need to apply photovoltaic cells and monitor their parameter variations, which can help operators to obtain the opt...

Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning.

The Journal of chemical physics
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A MOB pairwise decomposition ...

3D printable and fringe electric field adhesion enabled variable stiffness artificial muscles for semi-active vibration attenuation.

Soft matter
Soft robots are able to generate large and compliant deformation in an unconstructed environment, but their operation capability is limited by low stiffness. Thus, developing the function of variable stiffness while preserving its compliance is a cha...

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...