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Highly sensitive Raman probe detects enzyme e - Vimarsana News

Highly sensitive Raman probe detects enzyme e

Raman imaging offers a greater potential for detecting multiple enzyme activities than fluorescence imaging, demonstrate Tokyo Tech researchers by developing 9CN-rhodol-based activatable Raman probes using a novel mechanism for Raman signal activation. The strategy allows a synthesis of highly activatable Raman probes with high aggregation and multiplexing ability, making it a promising tool for extending the range of Raman probes for the detection of multiple enzyme activities in heterogeneous biological tissues.

New Approach for ZT Enhancement in Thermoelectric Materials - Vimarsana News

New Approach for ZT Enhancement in Thermoelectric Materials

Today, more than half of the total energy produced by fossil fuels is lost as waste heat, accelerating global warming.

Source: azom.com
Study Demonstrates a New Promising Application for Bi-Containing Oxychlorides in SOFCs - Vimarsana News

Study Demonstrates a New Promising Application for Bi-Containing Oxychlorides in SOFCs

Solid oxide fuel cells (SOFCs) are a promising solution to the contemporary problem of the impending global energy crisis. SOFCs show high efficiency, lower emissions, and have low operating costs, making them an ideal power source for a fossil fuel-free society.

Source: azom.com
Tokyo Institute of Technology Teams Selected for 2022 Interdisciplinary Research Support for Scientists - Vimarsana News

Tokyo Institute of Technology Teams Selected for 2022 Interdisciplinary Research Support for Scientists

Tokyo Institute of Technology has selected two teams for the 2022 Interdisciplinary Research Support for Scientists Program, which supports research that transcends individual fields.This support program aims to promote interdisciplinary research tha

CycPeptMPDB: A database aimed at promoting dr - Vimarsana News

CycPeptMPDB: A database aimed at promoting dr

CycPeptMPDB, a novel database—created by Tokyo Tech researchers—focused on the membrane permeability of cyclic peptides, could accelerate the development of drugs based on these promising compounds. This database was created by gathering published information on thousands of cyclic peptides and organizing it neatly in an online-accessible platform. Thanks to its search and visualization capabilities, CycPeptMPDB could pave the way to new computational and machine learning methods for screening and designing drugs with cyclic peptides.