AIMC Topic: Semiconductors

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Ultralow-Power Single-Sensor-Based E-Nose System Powered by Duty Cycling and Deep Learning for Real-Time Gas Identification.

ACS sensors
This study presents a novel, ultralow-power single-sensor-based electronic nose (e-nose) system for real-time gas identification, distinguishing itself from conventional sensor-array-based e-nose systems, whose power consumption and cost increase wit...

Hybrid neuromorphic hardware with sparing 2D synapse and CMOS neuron for character recognition.

Science bulletin
Neuromorphic computing enables efficient processing of data-intensive tasks, but requires numerous artificial synapses and neurons for certain functions, which leads to bulky systems and energy challenges. Achieving functionality with fewer synapses ...

Device simulations with A U-Net model predicting physical quantities in two-dimensional landscapes.

Scientific reports
Although Technology Computer-Aided Design (TCAD) simulation has paved a successful and efficient way to significantly reduce the cost of experiments under the device design, it still encounters many challenges as the semiconductor industry goes throu...

Methodology for Quantifying Volatile Compounds in a Liquid Mixture Using an Algorithm Combining B-Splines and Artificial Neural Networks to Process Responses of a Thermally Modulated Metal-Oxide Semiconductor Gas Sensor.

Sensors (Basel, Switzerland)
Metal oxide semiconductor (MOS) gas sensors have many advantages, but the main obstacle to their widespread use is the cross-sensitivity observed when using this type of detector to analyze gas mixtures. Thermal modulation of the heater integrated wi...

Room-Temperature Semiconductor Gas Sensors: Challenges and Opportunities.

ACS sensors
Our demand for ubiquitous and reliable gas detection is spurring the design of intelligent and enabling gas sensors for the next-generation Internet of Things and Artificial Intelligence. The desire to introduce gas sensors everywhere is fueled by op...

Bioinspired and Low-Power 2D Machine Vision with Adaptive Machine Learning and Forgetting.

ACS nano
Natural intelligence has many dimensions, with some of its most important manifestations being tied to learning about the environment and making behavioral changes. In primates, vision plays a critical role in learning. The underlying biological neur...

A voting-based ensemble feature network for semiconductor wafer defect classification.

Scientific reports
Semiconductor wafer defects severely affect product development. In order to reduce the occurrence of defects, it is necessary to identify why they occur, and it can be inferred by analyzing the patterns of defects. Automatic defect classification (A...

Multivalued Logic for Optical Computing with Photonically Enabled Chiral Bio-organic Structures.

ACS nano
Photonic bio-organic multiphase structures are suggested here for integrated thin-film electronic nets with multilevel logic elements for multilevel computing via a reconfigurable photonic bandgap of chiral biomaterials. Herein, inspired by an artifi...

Novel High-Efficiency Nanocomposite Gate Design of Quantum-Dot Cellular Automata Based on Deep Learning.

Computational intelligence and neuroscience
With the development of science and technology, the feature size of CMOS devices will always shrink to the limit. Therefore, some new nanodevices will eventually become substitutes for microelectronic devices. A new electronic revolution will break o...

A Heterogeneously Integrated Spiking Neuron Array for Multimode-Fused Perception and Object Classification.

Advanced materials (Deerfield Beach, Fla.)
Multimode-fused sensing in the somatosensory system helps people obtain comprehensive object properties and make accurate judgments. However, building such multisensory systems with conventional metal-oxide-semiconductor technology presents serious d...