Unveiling the Fundamental Mechanisms of Graphene Oxide Selectivity on the Ascorbic Acid, Dopamine, and Uric Acid by Density Functional Theory Calculations and Charge Population Analysis

Synthesis of cobalt phosphide hybrid for simultaneous electrochemical detection of ascorbic acid, dopamine, and uric acid

Ascorbic acid (AA), dopamine (DA), and uric acid (UA) are important biomarkers for the clinical screening of diseases. However, the simultaneous determination of these three analytes is still challenging. Herein, we report a facile metal-organic framework (MOF)-derived method to synthesize a cobalt phosphide (Co2P) hybrid for the simultaneous electrochemical detection of AA, DA and UA. The introduction of highly dispersed Co2P nanoparticles onto a P, N-doped porous carbon matrix is responsible for providing abundant active sites and facilitating electron transfer, thereby contributing to the improved electrocatalytic performance of the hybrid. Well-resolved oxidation peaks and an enhanced current response for the simultaneous oxidation of AA, DA, and UA were achieved using a Co2P hybrid-modified screen-printed electrode (Co2P hybrid-SPE) with the differential pulse voltammetry (DPV) method. The detection limits for AA, DA, and UA in simultaneous detection were calculated as 17.80 μM, 0.018 μM, and 0.068 μM (S/N = 3), respectively. Furthermore, the feasibility of using Co2P hybrid-SPE for the simultaneous detection of AA, DA, and UA in real serum samples was also confirmed.

Exploring the mechanism of graphene-oxide reduction by hydrazine in a multi-epoxide environment with DFT calculations

Reduction mechanisms between hydrazine and a multi-epoxide arrangement were investigated on a finite-sized graphene-oxide model with density functional theory. Three multistep reaction pathways were explored to examine different graphene-oxide (GO) deoxygenation scenarios. Epoxides sharing the same hexagonal ring show the typical one-by-one elimination of the oxygen functional groups through two protonation steps and the formation of cis-diazine and water. Nevertheless, the migration of one of the epoxy groups to an out-of-ring position has to precede the reduction. When a hexagonal ring separates two epoxy groups, forming a partially reduced surface with two hydroxyl groups is energetically favoured. This reduction product is so stable that it may remain on the surface after the termination of the reduction process. If further deoxygenation occurs, it can lead to surface fragmentation due to the ring opening of the remaining epoxides. The formation of nitrogen-containing functional groups at the edge of the graphene-oxide flake is also considered, and their surface presence is evaluated based on their thermodynamic stabilities.

First-Principles Calculations to Investigate the Stability and Thermodynamic Properties of a Newly Exposed Lithium-Gallium-Iridium-Based Full-Heusler Compound

The structural, optical, electrical, thermodynamic, superconducting, and mechanical characteristics of LiGa₂Ir full-Heusler alloys with the MnCu₂Al configuration were comprehensively examined in this work using the first-principles computation approach premised upon density functional analysis. This theoretical approach is the first to investigate the influence of pressure on the mechanical and optical characteristics of LiGa₂Ir. The structural and chemical bonding analysis shows that hydrostatic pressure caused a decrease in the lattice constant, volume, and bond length of each cell. According to the mechanical property calculations, the LiGa₂Ir cubic Heusler alloy exhibits mechanical stability. It also has ductility and anisotropic behavior. This metallic substance shows no band gap throughout the applied pressure range. The physical characteristics of the LiGa₂Ir full-Heusler alloy are analyzed in the operating pressure range of 0-10 GPa. The quasi-harmonic Debye model is employed to analyze thermodynamic properties. The Debye temperature (291.31 K at 0 Pa) increases with hydrostatic pressure. A newly invented structure attracted a lot of attention around the globe for its superior superconductivity (T_c ∼ 2.95 K). Optical functions have also been improved after applying stress to utilize it in optoelectronic/nanoelectric devices. The optical function analysis is supported strongly by the electronic properties. Due to these reasons, LiGa₂Ir imposed an essential guiding principle for relevant future research and could be a credible candidate substance for industrial settings.

Molecular Mechanisms on the Selectivity Enhancement of Ascorbic Acid, Dopamine, and Uric Acid by Serine Oligomers Decoration on Graphene Oxide: A Molecular Dynamics Study

The selectivity in the simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) has been an open problem in the biosensing field. Many surface modification methods were carried out for glassy carbon electrodes (GCE), including the use of graphene oxide and amino acids as a selective layer. In this work, molecular dynamics (MD) simulations were performed to investigate the role of serine oligomers on the selectivity of the AA, DA, and UA analytes. Our models consisted of a graphene oxide (GO) sheet under a solvent environment. Serine tetramers were added into the simulation box and were adsorbed on the GO surface. Then, the adsorption of each analyte on the mixed surface was monitored from MD trajectories. It was found that the adsorption of AA was preferred by serine oligomers due to the largest number of hydrogen-bond forming functional groups of AA, causing a 10-fold increase of hydrogen bonds by the tetraserine adsorption layer. UA was the least preferred due to its highest aromaticity. Finally, the role of hydrogen bonds on the electron transfer selectivity of biosensors was discussed with some previous studies. AA radicals received electrons from serine through hydrogen bonds that promoted oxidation reaction and caused the negative shifts and separation of the oxidation potential in experiments, as DA and UA were less affected by serine. Agreement of the in vitro and in silico results could lead to other in silico designs of selective layers to detect other types of analyte molecules.