Modification of Cu(111) Surface with Alkylphosphonic Acids in Aqueous and Ethanol Solution. An Experimental and Theoretical Study

Alkylphosphonic acids are well known for their ability to form self-assembled monolayers on hydroxide surfaces. A crucial step to understanding fundamentally how these surfaces are created is the elucidation of the interaction process that leads to such interface creation. In this study, we employed electrochemical impedance spectroscopy (EIS), Monte Carlo and molecular dynamics to understand this process. The interaction with the Cu(111) surface of three different alkylphosphonic acids (hexyl-, octyl- and decylphosphonic acids) is evaluated in an aqueous acidic and in an ethanol solution by Monte Carlo and molecular dynamics simulations, while EIS measurements are used to put in evidence the impact of the layer made in ethanol on copper protection. Nyquist diagrams of copper samples modified with an alkylphosphonic monolayer showed a higher polarization resistance that mitigates the copper corrosion in an aqueous acid medium. The phase–frequency Bode plots had higher and broader phase maxima for a modified copper surface with phosphonic moieties, which confirmed the ability of this organic layer to prevent copper corrosion.

Application of Machine Learning in Battery: State of Charge Estimation Using Feed Forward Neural Network for Sodium-Ion Battery

Estimating the accurate State of Charge (SOC) of a battery is important to avoid the over/undercharging and protect the battery pack from low cycle life. Current methods of SOC estimation use complex equations in the Extended Kalman Filter (EKF) and the equivalent circuit model. In this paper, we used a Feed Forward Neural Network (FNN) to estimate the SOC value accurately where battery parameters such as current, voltage, and charge are mapped directly to the SOC value at the output. A FNN could self-learn the weights with each training data point and update the model parameters such as weights and bias using a combination of two gradient descents (Adam). This model comprises the Dropout technique, which can have many neural network architectures by dropping the neuron/mode at each epoch/training cycle using the same weights and biases. Our FNN model was trained with data comprising different current rates and tested for different cycling data, for example, 5th, 10th, 20th, and 50th cycles and at a different cutoff voltage (4.5 V). The battery used for estimating the SOC value was a Na-ion based battery, which is highly non-linear, and it was fabricated in a house using Na0.67Fe0.5Mn0.5O2 (NFM) as a cathode and Na metal as a reference electrode. The FNN successfully estimated the SOC value for the highly non-linear nature of the Na-ion battery at different current rates (0.05 C, 0.1 C, 0.5 C, 1 C, 2 C), for different cycling data, and at higher cut-off voltage of –4.5 V Na+, reaching the R2 value of ~0.97–~0.99, ~0.99, and ~0.98, respectively.

An Experimental and Theoretical Investigation of the Efficacy of Pantoprazole as a Corrosion Inhibitor for Mild Steel in an Acidic Medium

The corrosion behavior of mild steel in a 1 M aqueous sulfuric acid medium in the presence and absence of the drug Pantoprazole was investigated using potentiodynamic polarization and quantum chemical calculations as well as Monte Carlo and molecular dynamic simulations. The potentiodynamic experiments indicated that this molecule, as a result of its adsorption on a mild steel surface, functioned as a mixed inhibitor. The goal of the study was to use theoretical calculations to acquire a better understanding of how inhibition works. The adsorption behavior of the examined compounds on the Fe (1 1 0) surface was calculated using a Monte Carlo simulation. Furthermore, the molecules were studied using density functional theory (DFT), especially the PBE functional, to determine the relationship between the molecular structure and the corrosion inhibition behavior of the chemical under research. The adsorption energies of Pantoprazole (in its three different protonation states) iron were calculated more precisely using molecular mechanics with periodic boundary conditions (PBC). The predicted theoretical parameters were found to be in agreement with the experimental data, which was a considerable help in understanding the corrosion inhibition mechanism displayed by this chemical.

Recent Advancements in the Synthesis and Application of Carbon-Based Catalysts in the ORR

Fuel cells are a promising alternative to non-renewable energy production industries such as petroleum and natural gas. The cathodic oxygen reduction reaction (ORR), which makes fuel cell technology possible, is sluggish under normal conditions. Thus, catalysts must be used to allow fuel cells to operate efficiently. Traditionally, platinum (Pt) catalysts are often utilized as they exhibit a highly efficient ORR with low overpotential values. However, Pt is an expensive and precious metal, posing economic problems for commercialization. Herein, advances in carbon-based catalysts are reviewed for their application in ORRs due to their abundance and low-cost syntheses. Various synthetic methods from different renewable sources are presented, and their catalytic properties are compared. Likewise, the effects of heteroatom and non-precious metal doping, surface area, and porosity on their performance are investigated. Carbon-based support materials are discussed in relation to their physical properties and the subsequent effect on Pt ORR performance. Lastly, advances in fuel cell electrolytes for various fuel cell types are presented. This review aims to provide valuable insight into current challenges in fuel cell performance and how they can be overcome using carbon-based materials and next generation electrolytes.

Doped Polythiophene Chiral Electrodes as Electrochemical Biosensors

π-conducting materials such as chiral polythiophenes exhibit excellent electrochemical stability in doped and undoped states on electrode surfaces (chiral electrodes), which help tune their physical and electronic properties for a wide range of uses. To overcome the limitations of traditional surface immobilization methods, an alternative pathway for the detection of organic and bioorganic targets using chiral electrodes has been developed. Moreover, chiral electrodes have the ability to carry functionalities, which helps the immobilization and recognition of bioorganic molecules. In this review, we describe the use of polythiophenes for the design of chiral electrodes and their applications as electrochemical biosensors.

Recent Applications of Molecular Structures at Silicon Anode Interfaces

Silicon (Si) is a promising anode material to realize many-fold higher anode capacity in next-generation lithium-ion batteries (LIBs). Si electrochemistry has strong dependence on the property of the Si interface, and therefore, Si surface engineering has attracted considerable research interest to address the challenges of Si electrodes such as dramatic volume changes and the high reactivity of Si surface. Molecular nanostructures, including metal–organic frameworks (MOFs), covalent–organic frameworks (COFs) and monolayers, have been employed in recent years to decorate or functionalize Si anode surfaces to improve their electrochemical performance. These materials have the advantages of facile preparation, nanoscale controllability and structural diversity, and thus could be utilized as versatile platforms for Si surface modification. This review aims to summarize the recent applications of MOFs, COFs and monolayers for Si anode development. The functionalities and common design strategies of these molecular structures are demonstrated.

Coupled Electrochemical-Thermal Simulations and Validation of Minichannel Cold-Plate Water-Cooled Prismatic 20 Ah LiFePO4 Battery

This paper discusses the quantitative validation carried out on a prismatic 20 Ah LiFePO4 battery sandwiched between two minichannel cold-plates with distributed flow having a single U-turn. A two-way coupled electrochemical-thermal simulations are performed at different discharge rates (1–4 C) and coolant inlet temperatures (15–35 °C). The predicted battery voltage response at room temperature (22 °C) and the performance of the Battery Thermal Management System (BTMS) in terms of the battery surface temperatures (maximum temperature, Tmax and temperature difference, ΔT) have been analyzed. Additionally, temperature variation at ten different locations on the battery surface is studied during the discharge process. The predicted temperatures are compared with the measured data and found to be in close agreement. Differences between the predicted and measured temperatures are attributed to the assumption of uniform heat generation by the Li-ion model (P2D), the accuracy of electrochemical property input data, and the accuracy of the measuring tools used. Overall, it is suggested that the Li-ion model can be used to design the efficient BTMS at the cell level.

Double-Layer Capacitances Caused by Ion–Solvent Interaction in the Form of Langmuir-Typed Concentration Dependence

Variations of the double layer capacitances (DLCs) at a platinum electrode with concentrations and kinds of salts in aqueous solutions were examined in the context of facilitating orientation of solvent dipoles. With an increase in ionic concentrations, the DLCs increased by ca. a half and then kept constant at concentrations over 1 mol dm−3. This increase was classically explained in terms of the Gouy–Chapman (GC) equation combined with the Stern model. Unfortunately, measured DLCs were neither satisfied with the Stern model nor the GC theory. Our model suggests that salts destroy hydrogen bonds at the electrode–solution interface to orient water dipoles toward the external electric field. A degree of the orientation depends on the interaction energy between the salt ion and a water dipole. The statistical mechanic calculation allowed us to derive an equation for the DLC as a function of salt concentration and the interaction energy. The equation took the Langmuir-type in the relation with the concentration. The interaction energy was obtained for eight kinds of salts. The energy showed a linear relation with the interaction energy of ion–solvent for viscosity, called the B-coefficient.

Fault Structural Analysis Applied to Proton Exchange Membrane Fuel Cell Water Management Issues

Proton exchange membrane fuel cells are relevant systems for power generation. However, they suffer from a lack of reliability, mainly due to their structural complexity. Indeed, their operation involves electrochemical, thermal, and electrical phenomena that imply a strong coupling, making it harder to maintain nominal operation. This complexity causes several issues for the design of appropriate control, diagnosis, or fault-tolerant control strategies. It is therefore mandatory to understand the fuel cell structure for a relevant design of these kinds of strategies. This paper proposes a fuel cell fault structural analysis approach that leads to the proposition of a structural graph. This graph will then be used to highlight the interactions between the control variables and the functionalities of a fuel cell, and therefore to emphasize how changing a parameter to mitigate a fault can influence the fuel cell state and eventually cause another fault. The final aim of this work is to allow an easier implementation of an efficient and fault-tolerant control strategy on the basis of the proposed graphical representation.

Catalysts for Oxygen Reduction Reaction in the Polymer Electrolyte Membrane Fuel Cells: A Brief Review

This mini-review presents a short account of materials with exceptional activity towards oxygen reduction reaction. Two main classes of catalytic materials are described, namely platinum group metal (PGM) catalyst and Non-precious metal catalyst. The classes are discussed in terms of possible application in low-temperature hydrogen fuel cells with proton exchange membrane and further commercialization of these devices. A short description of perspective approaches is provided and challenging issues associated with developed catalytic materials are discussed.