Metal-Organic Frameworks/Heterojunction Structures for Surface-Enhanced Raman Scattering with Enhanced Sensitivity and Tailorability.

Metal-organic frameworks (MOFs), which are composed of crystalline microporous materials with metal ions, have gained considerable interest as promising substrate materials for surface-enhanced Raman scattering (SERS) detection via charge transfer. Research on MOF-based SERS substrates has advanced rapidly because of the MOFs' excellent structural tunability, functionalizable pore interiors, and ultrahigh surface-to-volume ratios. Compared with traditional noble metal SERS plasmons, MOFs exhibit better biocompatibility, ease of operation, and tailorability.

A SERS nanocellulose-paper-based analytical device for ultrasensitive detection of Alzheimer's disease.

Background: Alzheimer's disease (AD), one of the most prevalent neurodegenerative diseases, results in severe cognitive decline and irreversible memory loss. Early detection of AD is significant to patients for personalized intervention since effective cure and treatment methods for AD are still lacking. Despite the severity of the disease, existing highly sensitive AD detection methods, including neuroimaging and brain deposit-positive lesion tests, are not suitable for screening purposes due to their high cost and complicated operation.

Cellulose Nanostructures as Tunable Substrates for Nanocellulose-Metal Hybrid Flexible Composites.

Nanocomposite represents the backbone of many industrial fabrication applications and exerts a substantial social impact. Among these composites, metal nanostructures are often employed as the active constituents, thanks to their various chemical and physical properties, which offer the ability to tune the application scenarios in thermal management, energy storage, and biostable materials, respectively. Nanocellulose, as an emerging polymer substrate, possesses unique properties of abundance, mechanical flexibility, environmental friendliness, and biocompatibility.

Microembossing: A Convenient Process for Fabricating Microchannels on Nanocellulose Paper-Based Microfluidics.

Nanopaper, derived from nanofibrillated cellulose, has generated considerable interest as a promising material for microfluidic applications. Its appeal lies in a range of excellent qualities, including an exceptionally smooth surface, outstanding optical transparency, a uniform nanofiber matrix with nanoscale porosity, and customizable chemical properties. Despite the rapid growth of nanopaper-based microfluidics, the current techniques used to create microchannels on nanopaper, such as 3D printing, spray coating, or manual cutting and assembly, which are crucial for practical applications, still possess certain limitations, notably susceptibility to contamination.

Deep Learning for Microfluidic-Assisted Multi-Parameter Identification Using YOLOv7.

The is an ideal model organism for studying human diseases and genetics due to its transparency and suitability for optical imaging. However, manually sorting a large population of for experiments is tedious and inefficient. The microfluidic-assisted sorting chip is considered a promising platform to address this issue due to its automation and ease of operation.