Challenges and perspectives in continuous glucose monitoring

Diabetes is a global epidemic that threatens the health and well-being of hundreds of millions of people. The first step in patient treatment is to monitor glucose levels. Currently this is most commonly done using enzymatic strips. This approach suffers from several limitations, namely it requires a blood sample and is therefore invasive, the quality and the stability of the enzymatic strips vary widely, and the patient is burdened by performing the measurement themselves. This results in dangerous fluctuations in glucose levels often going undetected. There is currently intense research towards new approaches in glucose detection that would enable non-invasive continuous glucose monitoring (CGM). In this review, we explore the state-of-the-art in glucose detection technologies. In particular, we focus on the physical mechanisms behind different approaches, and how these influence and determine the accuracy and reliability of glucose detection. We begin by reviewing the basic physical and chemical properties of the glucose molecule. Although these play a central role in detection, especially the anomeric ratio, they are surprisingly often overlooked in the literature. We then review state-of-the art and emerging detection methods. Finally, we survey the current market for glucometers. Recent results show that past challenges in glucose detection are now being overcome, thereby enabling the development of smart wearable devices for non-invasive continuous glucose monitoring. These new directions in glucose detection have enormous potential to improve the quality of life of millions of diabetics, as well as offer insight into the development, treatment and even prevention of the disease

2D MoTe2 nanosheets by atomic layer deposition: Excellent photo-electrocatalytic properties

Herein, the synthesis of MoTe2 nanosheets by means of Atomic Layer Deposition (ALD) is demonstrated for the first time. ALD enables tight control over the thickness and the composition of the deposited material, which are highly appealing features for the nanostructure fabrication. The growth of ALD MoTe2 was studied on substrates of different nature, including TiO2 nanotube (TNT) layers used as active supporting material for fabricating hierarchical nanotubular MoTe2/TNT heterostructure. The combination of newly synthesized Te precursor with commercial Mo precursor rendered the growth of 2D flaky MoTe2 nanosheets mostly out-of-plane oriented. The as-deposited MoTe2 was extensively characterized by different techniques which confirmed its chemical composition and revealed 2D flaky nano-crystalline structures. In parallel, MoTe2/TNT layers were employed to explore and exploit both photoand electrocatalytic properties. The synergy stemming from the out-of-plane MoTe2 nanosheet orientation, with an optimized amount of catalytic active edges, and the fast electron transfer through 1D TiO2 nanotubes triggered the catalytic properties for both, organic pollutant degradation and hydrogen evolution reaction (HER) applications. Remarkably, the application of a cathodic potential originated a gradual HER electrochemical activation over time driving to a higher current density and an overpotential drop. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/

High-performance supercapacitor electrode based on a polyaniline nanofibers/3D graphene framework as an efficient charge transporter

The distinctive architecture of the PANI/3D graphene electrode enhances its supercapacitive performance (1024 F g¬1), the lightweight and porous conducting foam provides “freeways” for fast charge transport.</p

Multiplexed DNA-functionalized graphene sensor with artificial intelligence-based discrimination performance for analyzing chemical vapor compositions

AbstractThis study presents a new technology that can detect and discriminate individual chemical vapors to determine the chemical vapor composition of mixed chemical composition in situ based on a multiplexed DNA-functionalized graphene (MDFG) nanoelectrode without the need to condense the original vapor or target dilution. To the best of our knowledge, our artificial intelligence (AI)-operated arrayed electrodes were capable of identifying the compositions of mixed chemical gases with a mixed ratio in the early stage. This innovative technology comprised an optimized combination of nanodeposited arrayed electrodes and artificial intelligence techniques with advanced sensing capabilities that could operate within biological limits, resulting in the verification of mixed vapor chemical components. Highly selective sensors that are tolerant to high humidity levels provide a target for “breath chemovapor fingerprinting” for the early diagnosis of diseases. The feature selection analysis achieved recognition rates of 99% and above under low-humidity conditions and 98% and above under humid conditions for mixed chemical compositions. The 1D convolutional neural network analysis performed better, discriminating the compositional state of chemical vapor under low- and high-humidity conditions almost perfectly. This study provides a basis for the use of a multiplexed DNA-functionalized graphene gas sensor array and artificial intelligence-based discrimination of chemical vapor compositions in breath analysis applications.</jats:p

Hierarchical MnCo-layered double hydroxides@Ni(OH)₂ core–shell heterostructures as advanced electrodes for supercapacitors

Rational assembly and hetero-growth of hybrid structures consisting of multiple components with distinctive features are a promising and challenging strategy to develop materials for energy storage applications.</p