Solution Process Research Articles

Differential Pressure Power Generation in UGS: Operational Optimization Model and Its Implications for Carbon Emission Reduction

Underground Gas Storage (UGS) is an important facility for natural gas peak adjustment and ensuring the balance between energy supply and demand. The daily gas injection and production capacity of large UGS can reach several hundred million or even billions of cubic meters, and the energy consumed by the injection and production equipment is not to be underestimated, which also contains a large amount of pressure energy that can be utilized for power generation. In this context, the optimization of low-carbon operation of UGS is of great practical significance in engineering. In this study, an innovative UGS system operation optimization method is proposed to integrate a natural gas differential pressure generator set in the UGS system. Considering the complex interconnections among multiple storage areas, multiple wells and wellsites, and the hydro-thermodynamic constraints during the operation of injection and production pipeline network, and with the objective of minimizing the carbon emission, the UGS integrated with Differential Pressure Power Generation System (UGSIDPPGS) is established. In order to solve this complex model, this paper designs an optimization solution framework based on variational assignment, which effectively avoids the problem of falling into inferior solutions during the solution process. The optimization model is applied to the case study of a large-scale depleted gas reservoir in China, and the optimal operation schemes under three scenarios are successfully obtained. The results show that the UGSIDPPGS optimization model, not only effectively utilizes the pressure energy, generates up to 56.908×106kW·h per month, and reduces the CO2 emission by 56,738 tons, but also achieves the low-carbon and economic operation of the UGS. In conclusion, the operation strategy proposed in this study is of great value for optimizing the operation of UGS, and provides practical guidance and suggestions for the low carbon and environmental protection of UGS and the utilization of new energy sources.

Carbon dioxide capture in sodium carbonate solution: Mass transfer kinetics and DTAC surfactant enhancement mechanism

Sodium carbonate solvent absorbent has been widely studied for CO2 reduction to deal with global warming because of its green, low cost, and non-corrosive advantages. However, in the application of sodium carbonate as an absorbent for CO2 capture, there is no unified cognition of the mass transfer process, which leads to the lack of guidance for the industrial large-scale process. Moreover, the mechanism of mass transfer enhancement of surfactants, which can effectively improve the mass transfer performance, has not been effectively explored in the literature. Based on this, this paper firstly adopts the molecular dynamics method to analyze the solution characteristics after surfactant addition and optimize the surfactant. Subsequently, a classical dissolved oxygen test method was used to measure the gas-liquid mass transfer coefficient for CO2 absorption into sodium carbonate solution. And based on this mass transfer coefficient measurement method, the mass transfer process of sodium carbonate solution with surfactant was analyzed. The results showed that the sodium carbonate solution with 5 wt% concentration and 10 wt% concentration at 30 °C did not satisfy the pseudo first-order fast chemical reaction kinetics assumption. To improve CO2 absorption mass transfer rate, dodecyl trimethyl ammonium chloride (DTAC) surfactant was introduced, which was improved by 119 % compared with non-enhanced solvent at 5 wt% concentration solution, and the assumption of pseudo first order fast chemical reaction was satisfied. After the introduction of surfactant, the barrier effect decreased the liquid phase mass transfer coefficient, but the Marangoni effect happened in the 5 wt% concentration of sodium carbonate solution, which enhanced the liquid-phase mass-transfer coefficient. This finding reveals the mechanism of mass transfer promotion of sodium carbonate by the surfactant DTAC, which is of great engineering significance for the application in the field of decarbonization after the introduction of surfactant.

Efficient and Fully Non-Halogen Solution Processed Cs2AgBiBr6 Perovskite Solar Cell

For traditional hole transport material (HTM) 2,2′,7,7′-tetrakis(N,N′-di-pmethoxyphenylamino)9,9′-spirbiuorene(Spiro-OMeTAD) used in Cs2AgBiBr6 perovskite solar cell (PSC), the strong dependence of its performance on the hygroscopic and volatility additives, together with the mismatched energy level with Cs2AgBiBr6 and gold electrodes, are considered to be the two key factors restricting the improvement of performance. Considering this, we reported a series of dopant-free D-π-D type HTMs comprising of FNP as donor unit and Cz-Mp dimer linked benzene as π-bridge, termed o-PCz, m-PCz, and p-PCz by adjusting the linkage position of π-bridge moieties. HTM p-PCz with planar rigid structure, exhibits higher hole mobility and better film morphology compared with o-PCz and m-PCz. Notably, o-PCz, m-PCz, and p-PCz all show good dissolvability in non-halogenated solvent tetrahydrofuran (THF), making it possible to fabricate Cs2AgBiBr6 PSCs with full non-halogenated solution process. As a result, the dopant-free p-PCz based Cs2AgBiBr6 PSC device achieved an efficiency of 2.44% with enhanced ambient and thermal stability. Hence, the successful development of dopant-free p-PCz would make a great contribution for efficient and stable lead-free Cs2AgBiBr6 PSCs with full non-halogenated solution process.

Catalytic Degradation of Acid Orange 7 Using CoFe2O4@Biochar Heterogeneous Catalytic Ozonation Process in Aqueous Solutions

Catalytic Degradation of Acid Orange 7 Using CoFe2O4@Biochar Heterogeneous Catalytic Ozonation Process in Aqueous Solutions

Solving Fuzzy Delay Differential Equations using Fuzzy Elzaki Transform and Fuzzy Elzaki Decomposition Method

Objective: In this work, the fuzzy Elzaki transform and fuzzy Elzaki decomposition method are used to solve fuzzy delay differential equations. The fuzzy Elzaki decomposition method is a combination of the fuzzy Elzaki transform and Adomian decomposition method in a fuzzy environment. The use of transforms in solving differential equations makes the solution process simpler. Methodology: The fuzzy Elzaki transform is applied in the fuzzy delay differential equation. The nonlinear terms are decomposed using Adomian polynomials in a nonlinear fuzzy delay differential equation. In the transformed domain, the resulting algebraic equation is solved. The solution in the original time domain is obtained by applying the inverse Elzaki transform. Findings: The fuzzy Elzaki transform and fuzzy Elzaki decomposition method are useful for handling the complexities associated with fuzzy functions and delays in differential equations. The technique used to solve the fuzzy delay differential equation gives results with better accuracy compared to the exact solution. The applicability of the method is illustrated with numerical examples. Novelty: The Elzaki transform is a helpful tool for solving delay differential equations with discontinuities. For the resilient solution of complicated differential equations, especially those including nonlinearity and fuzzy logic, the fuzzy Elzaki decomposition approach is useful. It gives an organized way to find the solution to fuzzy delay differential equation by utilizing the advantages of both the Elzaki transform and the Adomian decomposition method in a fuzzy situation. Keywords: Triangular Fuzzy Number, Fuzzy Elzaki Transform, Adomian decomposition method, Fuzzy Elzaki decomposition method, Fuzzy Delay Differential Equations (FDDE)

High‐Performance Synaptic Devices Based on Cross‐linked Organic Electrochemical Transistors with Dual Ion Gel

AbstractOrganic electrochemical transistors (OECTs) represent a promising approach for flexible, wearable, biomedical electronics, and sensors integrated with diverse substrates. Their ability to operate at low voltages and interact effectively with biological systems makes them particularly suitable for neuromorphic applications. For neuromorphic devices, OECTs must enhance electrical performance, biocompatibility, and signal storage/erasure capabilities. While UV cross‐linking methods with various side effects on organic semiconductors are predominant in improving mobility and current retention time, thermal cross‐linking based on the solution process has not been extensively explored. Additionally, despite significant research on the modification of electrolyte property, the ionic charge compensation mechanisms between multiple electrolytes are still unclear. This study employs a cross‐linking strategy involving the chemical reaction of poly(3‐hexylthiophene‐2,5‐diyl) (P3HT) with di‐tert‐butyl‐peroxide (DTBP) to create a cross‐linked P3HT active layer. Furthermore, a dual ion gel structure combining a conventional ion gel with a chitosan‐based ion gel is investigated for increased ionic transport to enhance OECT performance. Using the above two methods, the enhanced electrical performance showing the mobility of 25 F cm−1 V−1 s−1 and synaptic properties showing long‐term plasticity of cross‐linked OECTs with a dual ion gel structure are demonstrated, suggesting their potential application as high‐performance neuromorphic devices.

Proton-exchange induced reactivity in layered oxides for lithium-ion batteries.

LiNixCoyMn1-x-yO2 (0 < x, y < 1, NCM) is the dominant positive material for the state-of-the-art lithium-ion batteries. However, the sensitivity of NCM materials to moisture makes their manufacturing, storage, transportation, electrode processing and recycling complicated. Although it is recognized that protons play a critical role in their structure stability and performance, proton exchange with Li+ in NCM materials has not been well understood. Here, we employ advanced characterizations and computational studies to elucidate how protons intercalate into the layered structure of NCM, leading to the leaching of Li+ and the formation of protonated NCM. It is found that protonation facilitates cation rearrangement and formation of impurity phases in NCM, significantly deteriorating structural stability. The adverse effects induced by protons become increasingly pronounced with a higher Ni content in NCM. Through a comprehensive investigation into the thermodynamics and kinetics of protonation, we discover that Li deficiencies in NCM materials can be resolved via solution process in the presence of Li+ ions and controlled proton concentration. The underlying mechanism of relithiation is further explored through materials characterizations and kinetics modeling. This work provides crucial insights into controlling structural and compositional defects of Li-ion battery positive material in complicated processing environment.

Explicit Runge–Kutta Numerical Manifold Method for Solving the Burgers’ Equation via the Hopf–Cole Transformation

This paper presents an efficient numerical manifold method for solving the Burgers’ equation. To improve accuracy and streamline the solution process, we apply a nonlinear function transformation technique that reformulates the original problem into a linear diffusion equation. We utilize a dual cover mesh along with an explicit multi-step time integration method for spatial and temporal discretization, respectively. Constant cover functions are employed across mathematical covers, interconnected by a linear weight function for each manifold element. The full discretization formulation is derived using the Galerkin weak form. To efficiently compute the inverse of the symmetric positive definite mass matrix, we employ the Crout algorithm. The performance and convergence of our method are rigorously evaluated through several benchmark numerical tests. Extensive comparisons with exact solutions and alternative methods demonstrate that our approach delivers an accurate, stable, and efficient computational scheme for the Burgers’ equation.

Research on Target Allocation for Hard-Kill Swarm Anti-Unmanned Aerial Vehicle Swarm Systems

In response to the saturated attacks by low, slow, and small UAV swarms, there is currently a lack of effective countermeasures. Counter-UAV swarm technology is an important issue that urgently requires breakthroughs. This paper conducts research on a mid–short-range hard-kill counter-swarm scenario where fewer swarms confront multiple swarms and stronger swarms confront weaker swarms. The requirement is for counter-swarm UAVs to quickly penetrate the swarm at mid–short range and collide with as many incoming UAVs as possible to destroy them. To address the sparse solution space problem, an improved genetic algorithm that integrates multiple strategies is adopted to calculate the spatial density distribution of the incoming swarm. A baseline is identified through gradient descent that maximizes the density integral in a straight-line direction. Based on this baseline, the solution space for single strikes on the swarm is filtered. During the solution process, an elite strategy is introduced to prevent the overall degradation of the population performance. Additionally, the feasibility of the flight trajectory needs to be assessed. A piecewise cubic spline interpolation method is used to optimize the flight trajectory, minimizing the maximum curvature. Ultimately, multiple counter-swarm UAV targets within the swarm and their corresponding trajectories are obtained.

Solubility of Sulfamerazine in Acetonitrile + Ethanol Cosolvent Mixtures: Thermodynamics and Modeling

Sulfamerazine (SMR) is a drug used as an antibacterial agent in the treatment of some pathologies, such as bronchitis, prostatitis and urinary tract infections. Although this drug was developed in 1945 and, due to its toxicity, was partially displaced by penicillin, due to the current problem of bacterial resistance, compounds such as SMR have regained validity. In this context, the thermodynamic study of SMR in cosolvent mixtures of acetonitrile (MeCN) + ethanol (EtOH) at nine temperatures (278.15–318.15 K) is presented. The solubility of SMR was determined by UV–Vis spectrophotometry, following the guidelines of the shake-flask method. The solubility process was endothermic in all cases; thus, the minimum solubility was reached in pure EtOH at 278.15 K, and the maximum solubility was reached in pure MeCN at 318.15 K. Both the solution process and the mixing process were entropy-driven. On the other hand, the solubility data were modeled by using the van’t Hoff–Yalkowsky–Roseman model, obtaining an overall average relative deviation of 3.9%. In general terms, it can be concluded that the solution process of SMR in {MeCN (1) + EtOH (2)} mixtures is thermodependent, favored by the entropy of the solution and mixture; additionally, the van’t Hoff–Yalkowsky–Roseman model allows very good approximations to be obtained and is a simple model that starts from only four experimental data.

Simulation of landslide dam failure due to overtopping considering wide-graded soil erosion

Landslide dams, as a particular type of secondary geological disaster, can cause serious flood disasters. Therefore, accurately predicting potential dam failure processes is crucial for developing reasonable emergency response plans. Currently, several landslide dam failure models have been proposed, but most of these models do not appropriately consider the wide gradation of landslide dam materials, which is essential for accurate erosion calculations. Therefore, this research proposes a relative exposure formula under three-dimensional conditions to account for the concealment and exposure effects between large and small particles in wide-graded soil. Based on this, the incipient velocity of wide-graded soil is derived, and a mathematical model of overtopping failure of landslide dams is established. As part of the model, a numerical solution process is also developed to ensure convergence. To evaluate the performance of this new mathematical model, the discharge process of Tangjiashan landslide dam was used as a real-world case for dam failure calculation. The calculated results of key dam failure outcomes were compared with actual measurements, showing that the results of this model are largely consistent with actual measurements, with the error controlled within 10%. Additionally, the mathematical model proposed in this article was compared with two other existing dam failure models, revealing that the model proposed here has advantages in controlling the error of key dam failure outcomes, mainly due to the comprehensive consideration of erosion calculation in wide-graded soil. To further evaluate the stability of the model, the breach processes of the “11.3” Baige landslide dam and the Yigong landslide dam were also calculated, and the results showed reasonable consistency. Based on the model presented in this article, the influence of the grading width of landslide dam materials on key dam failure outcomes was discussed. It was found that grading width significantly affects the development process of breach flow. Specifically, wider grading width leads to smaller peak values of breach flow and later peak times. Additionally, the final size of the breach is affected by grading width, as it has a significant impact on erosion strength, although the sensitivity of this parameter is relatively weak. Given the significant impact of grading width on the dam failure process, especially for landslide dams containing wide-graded soil, it is essential to fully consider the wide grading of materials for accurate dam failure calculations.

Topology optimization and diverse truss designs considering nodal stability and bar buckling

Ensuring the bar stability is crucial in truss design. However, unstable nodes lacking lateral support complicate the calculation of bar buckling lengths. bar buckling constraints make the feasible region of optimization problems concave, further complicating the solution process. Moreover, traditional truss optimization methods typically yield a single optimal result, limiting the design options available to engineers. In this study, nominal disturbing load conditions are applied to the structure to eliminate unstable nodes, thereby ensuring accurate buckling length calculations. Additionally, the advanced allowable stress iteration (AASI) approach is proposed to address truss optimization problems with bar buckling constraints. To generate geometrically diverse and structurally competitive trusses, we develop a bar-length penalty (BLP) method. To validate the effectiveness of these methods, three numerical studies are presented. The results demonstrate that the proposed AASI approach produces optimized structures free from unstable nodes and bar buckling. Compared to structures optimized using the allowable stress iteration (ASI) method, which can only optimize for a single load case, those designed with the new approach maintain bar stability under all load conditions. Compared to the traditional method of increasing the cross-sectional area of unstable bars to ensure stability, much lighter trusses can be generated while maintaining the same load-bearing capacity. By applying the proposed BLP method to penalize specific bars, it is possible to achieve optimized structures with distinct topologies, similar masses, and equivalent load-carrying capacities. The proposed methods provide valuable insights for truss optimization design.

Improvements for the solution of crack evolution using extended finite element method

It is demonstrated that the eXtended Finite Element Method (XFEM) is of remarkable efficiency in simulating crack evolution by eliminating the need for remeshing and refinement. In this paper, it is shown how to enhance the solution efficiency through a comprehensive mathematical investigation of the solution process using XFEM. A typical example is presented to illustrate the disparities in nodal displacements along the two symmetric faces of the crack resulting from the approximation of XFEM. By analysing the structure and components of the global stiffness matrix, the underlying causes of these discrepancies are identified. Building upon these findings, two improvements of the solution are proposed to gain an acceptable accuracy in computing the nodal displacements. The first improvement consists of the subdivision of the enriched elements depending on the characteristic of the distribution of Gauss points. The second improvement is set by determining the optimal number of Gauss points in each sub-element near the crack tip. To calculate the stress intensity factor of the crack under surface pressure, such improvements are applied in conjunction with the interaction integral method, which significantly reduces computational time and eliminates the influence of surface tractions. The numerical solution is validated by comparing it with the analytical solution and the standard XFEM solution. The proposed improvements can enhance both the accuracy of the solution and the computational efficiency of XFEM.

Data-driven prediction of relevant scenarios for robust combinatorial optimization

We study iterative constraint and variable generation methods for (two-stage) robust combinatorial optimization problems with discrete uncertainty. The goal of this work is to find a set of starting scenarios that provides strong lower bounds early in the process. To this end we define the Relevant Scenario Recognition Problem (RSRP) which finds the optimal choice of scenarios which maximizes the corresponding objective value. We show for classical and two-stage robust optimization that this problem can be solved in polynomial time if the number of selected scenarios is constant and NP-hard if it is part of the input. Furthermore, we derive a linear mixed-integer programming formulation for the problem in both cases.Since solving the RSRP is not possible in reasonable time, we propose a machine-learning-based heuristic to determine a good set of starting scenarios. To this end, we design a set of dimension-independent features, and train a Random Forest Classifier on already solved small-dimensional instances of the problem. Our experiments show that our method is able to improve the solution process even for larger instances than contained in the training set, and that predicting even a small number of good starting scenarios can considerably reduce the optimality gap. Additionally, our method provides a feature importance score which can give new insights into the role of scenario properties in robust optimization.

Interface analysis of oxide free MoS2 films fabricated by solution process.

We report a solution-based approach for the synthesis of oxidation-free MoS2 films, focusing on interface analysis. Through a sulfurization-free solution process and single-step annealing, the oxidation-free MoS2 film is successfully prepared on Si3N4 surfaces, showing improved uniformity with a surface roughness below 0.5nm and a thickness of 4nm at a precursor solution concentration of 30 mM, annealed between 700 and 800ºC. The MoS2 films exhibit a hexagonal lattice structure with crystallographic orientations of (1 1 0 0) and (1 2 1 0) with lattice spacings of 0.27nm and 0.16nm respectively. Interfacial analysis by X-ray photoelectron spectroscopy (XPS) on SiO2 reveals migration of oxygen species as evidenced by a shift in the Si 2p spectrum at binding energies between 102.6eV and 102.8eV. MoS2 films on Si3N4 show a complex Si 2p peak evolution at binding energies between 100.9 and 101.8eV, providing valuable insights into the synthesis of oxide-free MoS2 films for potential applications in advanced electronic devices.

Bilayer Boost to UV Assisted Supercapacitors: Enhanced Performance with Transparent TiO2/MoO3 Heterojunction Electrode

Photo‐assisted supercapacitor is a promising smart device component for achieving both energy conversion and storage. The photo‐assisted functionality in a supercapacitor is realized through the choice of photo responsive electrode material under suitable illumination conditions. The well‐known electrochemically active electrode materials are wide band gap semiconductors which absorb strongly in UV light. However, most of the prior studies on photo‐assisted supercapacitors used visible light. Herein, we present a transparent TiO2/MoO3 bi‐layer heterojunction made by simple solution process as an efficient electrode for photo‐assisted supercapacitors under UV light illumination. The electrochemical performance of the electrode is significantly enhanced even with a less intense (0.05mW/cm2) UV light, compared to dark as well as the single layer electrode under same illumination condition. The highest areal capacitance of 63.25 mF/cm2 at 0.1 mA/cm2 is achieved, that surpasses most of the recent relevant reports. The synergetic effect of UV illumination and the built‐in potential at the type II heterojunction interface encourages ion insertion and better collection of the photo‐generated carriers. The unique bi‐layer design also leads to better rate capability features. Thus, the work presents a new prospect for the development of transparent energy storage devices to be used in future smart technologies.

APPLICATION OF ELECTROLYTE BASED ON SODIUM CARBONATE FOR ELECTROLYTEPLASMA SURFACE HARDENING OF STEEL 45

This article evaluates the electrolyte-plasma hardening (EPH) of steel 45 using an electrolyte based on sodium carbonate (Na₂CO₃). Theoretical foundations of the electrolysis process of a sodium carbonate aqueous solution were studied during the course of the work. The mechanical and tribological properties of 45 steel samples after EPH were studied. It was found that with an electrolyte composition of 20% Na₂CO₃ and 80% distilled water, a hardened zone with a thickness of up to 5 mm is formed after EPH. The increase in microhardness reached up to 690 HV, which corresponds to a 3–3.5 times increase compared to the initial state. The results of tribological tests showed that the friction coefficient of steel 45 decreased after EPH, indicating a significant improvement in tribological characteristics compared to the initial value before hardening. Electrochemical tests on the corrosion resistance of steel 45 were also carried out. After EPH, the corrosion rate significantly decreased for steel 45 samples, indicating its highest corrosion resistance.

Calcite Dissolution-Reprecipitation Reactions Are a Key Control on the Sr/Ca, Mg/Ca and δ88/86Sr Compositions of Himalayan River Waters

Silicate weathering on the continents is thought to play a critical part in regulating global climate on geological time scales but determination of the magnitude of silicate weathering fluxes is frustrated by the complexity of the weathering processes. Here we present analyses of stable Sr-isotopic compositions (𝛿88/86Sr) in a suite of river waters and bedloads from the Himalayas in Nepal to establish the lithological controls on 𝛿88/86Sr values and the secondary processes that impact carbonate weathering. A control on 𝛿88/86Sr values is lithology with the rivers in carbonate-dominated catchments marginally lower (∼0.07 ‰) than in silicate-dominated catchments. However, as for 87Sr/86Sr ratios, 𝛿88/86Sr values of carbonates are altered by silicate-carbonate mineral exchange during metamorphism. The major potential secondary control on 𝛿88/86Sr values in Himalayan catchments is precipitation of secondary calcite responsible for the marked elevation of Sr/Ca and Mg/Ca ratios in the waters. We re-evaluate the mechanisms for secondary calcite formation and conclude that a balanced solution and re-precipitation process, driven by the relative instability of the primary Mg-rich calcite, provides a better explanation for the elevated Sr/Ca ratios than simple precipitation from a highly over saturated solution. This solution-re-precipitation process is akin to that invoked to explain diagenesis of deep-sea sediments. The mechanism of secondary calcite formation impacts the distinction of cation inputs from carbonate and silicate minerals. The correlation between 𝛿88/86Sr water-calcite fractionations, Sr/Ca partition coefficients and precipitation rates allows the calcite re-precipitation rates to be inferred from the covariation of water 𝛿88/86Sr values and Sr/Ca ratios. These rates are very low (&lt;10-8 mol m-2 s-1) but are consistent with those inferred from field estimates of the amount of calcite re-precipitated, the surface area of carbonate exposed to weathering and the calcite weathering flux. The low precipitation rates are also consistent with previously reported 𝛥44/40Ca isotope fractionations of ∼−0.2‰. The calcite reprecipitation rates are comparable to silicate weathering rates previously inferred from Li-isotopic compositions which is consistent with calcite re-precipitation taking place very close to equilibrium following the initial rapid saturation of the fluids by calcite.

Formamidinium Lead Iodide‐Based Perovskite Solar Cell Fabrication With an Electrospun‐Reduced Graphene Oxide Back Electrode: A Novel Approach

AbstractIn this work, low‐cost and simple structure perovskite solar cells (PSCs) were fabricated using formamidinium lead iodide (FAPbI3) as the light absorber and reduced graphene oxide nanofibers (rGO NFs) as the counter electrode (CE). The FAPbI3 light absorber was prepared using a two‐step solution process, whereas the rGO NFs were synthesized through a simple electrospinning method. The as‐prepared FAPbI3 and rGO NFs were characterized by high‐resolution transmission electron microscopy (HRTEM), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and X‐ray diffraction (XRD) pattern analysis. The surface morphology of the as‐prepared FAPbI3 and rGO NFs showed crystalline and bead‐free fiber structures, as confirmed by HRTEM and FESEM image analysis. The AFM topographical images of FAPbI3 and rGO NFs further reveal the crystalline and fiber structures. XRD pattern analysis confirmed the cubic crystalline phase of FAPbI3 and the graphitic nature of rGO NFs. From the electrochemical impedance spectroscopy studies, the PSC assembled with the FAPbI3 light absorber and rGO NFs‐based CE demonstrated an electrical conductivity of 3.64 × 10−4 S cm−1. The fabricated PSC device achieved an efficiency of 8.78% compared to the 7.49% efficiency of the device with a sputtered gold CE. This work uniquely integrates advanced materials, cost‐effective manufacturing, and enhanced efficiency in PSCs using FAPbI3 light absorbers and rGO NFs, addressing key challenges in cost and sustainability in solar technology.

Impact of edetate sodium on calcium carbonate scaling: Insights from molecular dynamics simulations

In order to mitigate calcium carbonate (CaCO3) scaling in oil and gas wells, antiscaling agents are commonly used. This research employed the molecular dynamics method to simulate the crystallization process of a supersaturated CaCO3 solution, with particular emphasis on examining the influence of the antiscalant edetate sodium (EDTA). Analysis of the spatial distribution of Ca2+ in proximity to CO32− revealed that EDTA effectively impedes the interaction between Ca2+ and CO32−, resulting in a reduction in the mean square displacement and diffusion coefficient of CO32−. The examination of intermolecular interaction energies indicates that the binding energy between Ca2+ and CO32− is approximately −516 kcal mol−1, while the binding energy between Ca2+ and EDTA is estimated at −718 kcal mol−1. These findings suggest that EDTA exhibits a higher affinity for binding with Ca2+ compared to CO32−, consequently hindering the formation of CaCO3.