AI Medical Compendium Journal:
ACS sensors

Showing 71 to 80 of 110 articles

On-Demand Optimization of Colorimetric Gas Sensors Using a Knowledge-Aware Algorithm-Driven Robotic Experimental Platform.

ACS sensors
Synthesizing the best material globally is challenging; it needs to know what and how much the best ingredient composition should be for satisfying multiple figures of merit simultaneously. Traditional one-variable-at-a-time methods are inefficient; ...

Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films.

ACS sensors
Through the capture of a target molecule at the metal surface with a highly confined electromagnetic field induced by surface plasmon, surface enhanced Raman spectroscopy (SERS) emerges as a spectral analysis technology with high sensitivity. However...

Magneto-Mechanical Coupling Study of Magnetorheological Elastomer Thin Films for Sensitivity Enhancement.

ACS sensors
Magnetorheological elastomer thin films (MREFs) exhibit remarkable deformability and an adjustable modulus under magnetic fields, rendering them promising in fields such as robotics, flexible sensors, and biomedical engineering. Here, we fabricated M...

An Artificial Olfactory System Based on a Memristor Can Simulate Organ Injury and Functions in Air Purification.

ACS sensors
Artificial olfactory systems are receiving increasing attention because of their potential applications in humanoid robots, artificial noses, and the next generation of human-computer interactions. However, simulating the human olfactory system, whic...

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning.

ACS sensors
Here, we provide a new methodology for reducing false results and time delay of biosensors, which are barriers to industrial, healthcare, military, and consumer applications. We show that integrating machine learning with domain knowledge in biosensi...

In-Sensor Computing Realization Using Fully CMOS-Compatible TiN/HfO-Based Neuristor Array.

ACS sensors
With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneou...

Semi-Selective Array for the Classification of Purines with Surface Plasmon Resonance Imaging and Deep Learning Data Analysis.

ACS sensors
In process analytics or environmental monitoring, the real-time recording of the composition of complex samples over a long period of time presents a great challenge. Promising solutions are label-free techniques such as surface plasmon resonance (SP...

Highly Flexible Deep-Learning-Based Automatic Analysis for Graphically Encoded Hydrogel Microparticles.

ACS sensors
Graphically encoded hydrogel microparticle (HMP)-based bioassay is a diagnostic tool characterized by exceptional multiplex detectability and robust sensitivity and specificity. Specifically, deep learning enables highly fast and accurate analyses of...

Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

ACS sensors
Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutate...

Physicochemical Profiling of Macrophage Heterogeneity Using Deep Learning Integrated Nanosensor Cytometry.

ACS sensors
Label-free single-cell analytics have been developed for understanding the collective immune response mechanism of immune cells. However, it remains difficult to analyze the physicochemical properties of a single cell in high spatiotemporal resolutio...