Digital technologies hold enormous potential for improving the performance of future-
generation sorting and processing plants; however, this potential remains largely untapped …

The progress of science and technology speeds up the upgrading of electrical and
electronic equipment, resulting in the generation of electronic waste (e-waste). Electronic …

Diagnosis of neurodegenerative disorders (NDDs) including Parkinson's disease and
Alzheimer's disease is challenging owing to the lack of tools to detect preclinical biomarkers …

Microplastics (MPs) are currently recognized as emerging pollutants; their identification and
classification are therefore essential during their monitoring and management. In contrast to …

The steady progress in consumer electronics, together with improvement in microflow
techniques, nanotechnology, and data processing, has led to implementation of cost …

We present a combination of convolutional neural network (CNN) framework and fast MIR
(mid-infrared spectroscopy) for classifying different types of dark plastic materials that are …

Infrared (IR) spectroscopy is a powerful and versatile tool for analyzing functional groups in
organic compounds. A complex and time-consuming interpretation of massive unknown …

Fourier Transform Infrared (FTIR) spectroscopy, once primarily associated with structural
analysis, has transcended its conventional role to become a versatile analytical powerhouse …

Electronic components are the main components of PCBs (printed circuit boards), so the
detection and classification of ECs (electronic components) is an important aspect of …

Recycling and utilization of plastic waste are receiving more and more attention, and the
combination of spectroscopic techniques and machine learning is expected to solve the …