AIMC Topic: Silicon

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Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced Raman scattering (SERS) technology. In this study, gold@silver-porous silicon (Au@Ag-PSi) composite ...

Machine-Learning-Assisted Rational Design of Si─Rhodamine as Cathepsin-pH-Activated Probe for Accurate Fluorescence Navigation.

Advanced materials (Deerfield Beach, Fla.)
High-performance fluorescent probes stand as indispensable tools in fluorescence-guided imaging, and are crucial for precise delineation of focal tissue while minimizing unnecessary removal of healthy tissue. Herein, machine-learning-assisted strateg...

Machine Learning Method and Hyperspectral Imaging for Precise Determination of Glucose and Silicon Levels.

Sensors (Basel, Switzerland)
This article introduces an algorithm for detecting glucose and silicon levels in solution. The research focuses on addressing the critical need for accurate and efficient glucose monitoring, particularly in the context of diabetic management. Underst...

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain.

Science and engineering ethics
The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent ...

Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

Scientific reports
Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg r...

Node-Loss Detection Methods for CZ Silicon Single Crystal Based on Multimodal Data Fusion.

Sensors (Basel, Switzerland)
Monocrystalline silicon is an important raw material in the semiconductor and photovoltaic industries. In the Czochralski (CZ) method of growing monocrystalline silicon, various factors may cause node loss and lead to the failure of crystal growth. C...

Deep Learning Model to Denoise Luminescence Images of Silicon Solar Cells.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Luminescence imaging is widely used to identify spatial defects and extract key electrical parameters of photovoltaic devices. To reliably identify defects, high-quality images are desirable; however, acquiring such images implies a higher cost or lo...

Cuttlefish eye-inspired artificial vision for high-quality imaging under uneven illumination conditions.

Science robotics
With the rise of mobile robotics, including self-driving automobiles and drones, developing artificial vision for high-contrast and high-acuity imaging in vertically uneven illumination conditions has become an important goal. In such situations, bal...

A Flexible Pressure Sensor Based on Silicon Nanomembrane.

Biosensors
With advances in new materials and technologies, there has been increasing research focused on flexible sensors. However, in most flexible pressure sensors made using new materials, it is challenging to achieve high detection sensitivity across a wid...

Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces.

Nature communications
A wearable silent speech interface (SSI) is a promising platform that enables verbal communication without vocalization. The most widely studied methodology for SSI focuses on surface electromyography (sEMG). However, sEMG suffers from low scalabilit...