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Electronics

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Advances in Biodegradable Electronic Skin: Material Progress and Recent Applications in Sensing, Robotics, and Human-Machine Interfaces.

Advanced materials (Deerfield Beach, Fla.)
The rapid growth of the electronics industry and proliferation of electronic materials and telecommunications technologies has led to the release of a massive amount of untreated electronic waste (e-waste) into the environment. Consequently, catastro...

Combination of explainable machine learning and conceptual density functional theory: applications for the study of key solvation mechanisms.

Physical chemistry chemical physics : PCCP
We present explainable machine learning approaches for the accurate prediction and understanding of solvation free energies, enthalpies, and entropies for different salts in various protic and aprotic solvents. As key input features, we use fundament...

Vision-Based Detection and Classification of Used Electronic Parts.

Sensors (Basel, Switzerland)
Economic and environmental sustainability is becoming increasingly important in today's world. Electronic waste (e-waste) is on the rise and options to reuse parts should be explored. Hence, this paper presents the development of vision-based methods...

Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning.

Antimicrobial resistance and infection control
BACKGROUND: Cardiac implantable electronic device (CIED) surgical site infections (SSIs) have been outpacing the increases in implantation of these devices. While traditional surveillance of these SSIs by infection prevention and control would likely...

Obtaining Electronic Properties of Molecules through Combining Density Functional Tight Binding with Machine Learning.

The journal of physical chemistry letters
We have introduced a machine learning workflow that allows for optimizing electronic properties in the density functional tight binding method (DFTB). The workflow allows for the optimization of electronic properties by generating two-center integral...

Neuromorphic Liquids, Colloids, and Gels: A Review.

Chemphyschem : a European journal of chemical physics and physical chemistry
Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses ...

Recent advances in biomimetic soft robotics: fabrication approaches, driven strategies and applications.

Soft matter
Compared to traditional rigid-bodied robots, soft robots are constructed using physically flexible/elastic bodies and electronics to mimic nature and enable novel applications in industry, healthcare, aviation, military, Recently, the fabrication of...

Nonlinear decision-making with enzymatic neural networks.

Nature
Artificial neural networks have revolutionized electronic computing. Similarly, molecular networks with neuromorphic architectures may enable molecular decision-making on a level comparable to gene regulatory networks. Non-enzymatic networks could in...

Development and validation of the Alcoholic Beverage Identification Deep Learning Algorithm version 2 for quantifying alcohol exposure in electronic images.

Alcoholism, clinical and experimental research
BACKGROUND: Seeing alcohol in media has been demonstrated to increase alcohol craving, impulsive decision-making, and hazardous drinking. Due to the exponential growth of (social) media use it is important to develop algorithms to quantify alcohol ex...

Multicomponent and multifunctional integrated miniature soft robots.

Soft matter
Miniature soft robots with elaborate structures and programmable physical properties could conduct micromanipulation with high precision as well as access confined and tortuous spaces, which promise benefits in medical tasks and environmental monitor...