Built-In Positive Valence Space Shifting the Chemical Equilibrium Forward for Nitrate Reduction to Ammonia.

The electrochemical conversion of nitrate pollutants into value-added ammonia (NH3) is an appealing alternative synthetic route for sustainable NH3 production. However, the development of the electrocatalytic nitrate-to-ammonia reduction reaction (NO3RR) has been hampered by unruly reactants and products at the interface and the accompanied sluggish kinetic rate. In this work, a built-in positive valence space is successfully constructed over FeCu nanocrystals to rationally regulate interfacial component concentrations and positively shift the chemical equilibrium. With positive valence Cu optimizing the active surface, the space between the stern and shear layers becomes positive, which is able to continuously attract the negatively charged NO3- reactant and repulse the positively charged NH4+ product even under high current density, thus significantly boosting the NO3RR kinetics. The system with a built-in positive valence space affords an ampere-level NO3RR performance with the highest NH3 yield rate of 150.27 mg h-1 mg-1 at -1.3 V versus RHE with an outstanding NH3 current density of 189.53 mA cm-2, as well as a superior Faradaic efficiency (FE) of 97.26% at -1.2 V versus RHE. The strategy proposed here underscores the importance of interfacial concentration regulation and can find wider applicability in other electrochemical syntheses suffering from sluggish kinetics.

Prediction and design optimization of mechanical properties for rubber fertilizer hose reinforced with helically wrapped nylon.

Predicting and optimizing the mechanical performance of the helically wound nylon-reinforced rubber fertilizer hose (HWNR hose) is crucial for enhancing the performance of hose pumps. This study aims to enhance the service life of HWNR hoses and the efficiency of liquid fertilizer transport. First, a finite element simulation model and a mathematical model were established to analyze the influence of fiber layer arrangement on the maximum shear strain on the coaxial surface (MSS) and the reaction force on the extrusion roller (RF). For the first time, the Crested Porcupine Optimizer algorithm was used to improve the Generalized Regression Neural Network (CPO-GRNN) method to establish a surrogate model for predicting the mechanical properties of HWNR hoses, and it was compared with Response Surface Methodology (RSM). Results showed CPO-GRNN's superiority in handling complex nonlinear problems. Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed for optimization design. Compared to the original HWNR hose with an MSS of 0.906 and an RF of 30,376N, the optimized design reduced the MSS by 7.99% and increased the RF by 2.46%, significantly enhancing their service life and liquid fertilizer transport capacity. However, further research on fatigue damage is needed.

Fast, Accurate, and Versatile Data Analysis Platform for the Quantification of Molecular Spatiotemporal Signals.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, and imaging modalities. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.

A facile nanozyme-based colorimetric method to realize the quantitative and specific detection of casein phosphopeptides in food samples.

As a popular nutritional enhancer, casein phosphopeptides (CPPs) have attracted growing attention in food industry. However, conventional methods for CPPs detection are usually less precise or requires expensive instruments. Herein, a nanozyme-based colorimetric method was developed to achieve the quantitative detection of CPPs in food samples. This method is based on a facilely fabricated peroxidase-like nanozyme (Fe@UiO-66), which combines the specific binding of CPPs, as well as the nanozyme-catalyzed colorimetric sensing that can be easily detected by spectrometer. The method displayed good quantitative ability toward CPPs with the linear range of 2-30 µg/mL, the low limit of detection of 0.267 µg/mL and limit of quantification of 1.335 µg/mL. We highlighted the specificity, anti-interference and practicability of this method, by investigating the performances toward food samples. Besides, a smartphone-based colorimetric sensing platform was also established, which is conducive to the portable detection. The developed nanozyme-based colorimetric sensing method provides a promising strategy for CPPs detection in food samples.

Rare-Earth Lanthanum-Evoked Amorphization and Optimization to Boost Ambient Nitrogen Fixation over Single-Atom Catalysts.

Single-atom catalysts (SACs) have been widely studied in a variety of electrocatalysis. However, its application in the electrocatalytic nitrogen reduction reaction (NRR) field still suffers from unsatisfactory performance, due to the sluggish mass transfer and significant kinetic barriers. Herein, a novel rare-earth-lanthanum-evoked optimization strategy is proposed to boost ambient NRR over SACs. The incorporation of La with a large atomic radius tends to break the atomic long-range order and trigger the amorphization of SACs, endowing a greater density of dangling bonds that could modify affinity for reactants and adsorbates. Moreover, with unique 5d16s2 valence-electron configurations, its presence could further enrich the electron density and enhance the intrinsic activity of single-metal center via the valence orbital coupling. As expected, the La-modified catalyst presents excellent activity toward the electrochemical NRR, delivering a maximum ammonia yield rate of 33.91 µg h-1 mg-1 and a remarkable Faradaic efficiency of 53.82%.

Bithiophene-Functionalized Infrared Two-Photon Absorption Metal Complexes as Single-Molecule Platforms for Synergistic Photodynamic, Photothermal, and Chemotherapy.

A planar conjugated ligand functionalized with bithiophene and its Ru(II), Os(II), and Ir(III) complexes have been constructed as single-molecule platform for synergistic photodynamic, photothermal, and chemotherapy. The complexes have significant two-photon absorption at 808 nm and remarkable singlet oxygen and superoxide anion production in aqueous solution and cells when exposed to 808 nm infrared irradiation. The most potent Ru(II) complex Ru7 enters tumor cells via the rare macropinocytosis, locates in both nuclei and mitochondria, and regulates DNA-related chemotherapeutic mechanisms intranuclearly including DNA topoisomerase and RNA polymerase inhibition and their synergistic effects with photoactivated apoptosis, ferroptosis and DNA cleavage. Ru7 exhibits high efficacy in vivo for malignant melanoma and cisplatin-resistant non-small cell lung cancer tumors, with a 100 % survival rate of mice, low toxicity to normal cells and low residual rate. Such an infrared two-photon activatable metal complex may contribute to a new generation of single-molecule-based integrated diagnosis and treatment platform to address drug resistance in clinical practice and phototherapy for large, deeply located solid tumors.

The Inhibition Mechanisms of Three Structurally Different Salvianolic Acids on the Non-Enzymatic Glycation of Bovine Serum Albumin.

The antiglycation mechanisms of three structurally different salvianolic acids (Sals) including salvianolic acid A (Sal-A), salvianolic acid B (Sal-B) and salvianolic acid C (Sal-C) were investigated using the bovine serum albumin (BSA)-fructose model. The results showed that the three compounds could inhibit the formation of glycation products, maintain protein structural stability, mitigate the development of amyloid fibrils and scavenge radicals. Notably, Sal-A possessed the highest anti-glycated activity compared with Sal-B and Sal-C. This may be related to the fact that Sal-A contained the most molecules of caffeic acid (Sal-A, Sal-B, and Sal-C possessing two, one, and zero caffeic acid units, respectively), and caffeic acid played a leading role in the antiglycation properties relative to Danshensu. Moreover, these compounds quenched the intrinsic fluorescence intensity of BSA in a static mode, with the binding constants in the order of Sal-A > Sal-B > Sal-C. Obviously, Sal-A possessed the strongest binding affinity among these compounds, which may be one of the reasons why it exhibited the optimal antiglycation capability. Furthermore, molecular docking demonstrated that the three Sals exerted protective effects on BSA by preventing glycation modification of lysine and arginine residues. These findings would provide valuable insights into the potential application of Sals for alleviating non-enzymatic glycation of protein.

Optimizing Intermediate Adsorption over PdM (M=Fe, Co, Ni, Cu) Bimetallene for Boosted Nitrate Electroreduction to Ammonia.

Electrochemical reduction of nitrate to ammonia (NO3RR) is a promising and eco-friendly strategy for ammonia production. However, the sluggish kinetics of the eight-electron transfer process and poor mechanistic understanding strongly impedes its application. To unveil the internal laws, herein, a library of Pd-based bimetallene with various transition metal dopants (PdM (M=Fe, Co, Ni, Cu)) are screened to learn their structure-activity relationship towards NO3RR. The ultra-thin structure of metallene greatly facilitates the exposure of active sites, and the transition metals dopants break the electronic balance and upshift its d-band center, thus optimizing intermediates adsorption. The anisotropic electronic characteristics of these transition metals make the NO3RR activity in the order of PdCu>PdCo≈PdFe>PdNi>Pd, and a record-high NH3 yield rate of 295 mg h-1 mgcat -1 along with Faradaic efficiency of 90.9 % is achieved in neutral electrolyte on PdCu bimetallene. Detailed studies further reveal that the moderate N-species (*NO3 and *NO2) adsorption ability, enhanced *NO activation, and reduced HER activity facilitate the NH3 production. We believe our results will give a systematic guidance to the future design of NO3RR catalysts.

Rational design of antibodies and development of a novel method for (1-3)-ß-D glucan detection as an alternative to Limulus amebocyte lysate assay.

With advances in medicine, increasing medical interventions have increased the risk of invasive fungal disease development. (1-3)-ß-D glucan (BDG) is a common fungal biomarker in serological tests. However, the scarcity of Limulus resources for BDG detection poses a challenge. This study addresses the need for an alternative to Limulus amebocyte lysate by using BDG mutant antibody for chemiluminescence detection. The wild-type BDG antibody was obtained by immunizing rabbits. An optimal V52HI/N34L Y mutant antibody, which has increased 3.7-fold of the testing efficiency compared to the wild-type antibody, was first achieved by mutating "hot-spot" residues that contribute to strong non-covalent bonds, as determined by alanine scanning and molecular dynamics simulation. The mutant was then applied to develop the magnetic particle chemiluminescence method. 574 clinical samples were tested using the developed method, with a cutoff value of 95 pg/mL set by Limulus amebocyte lysate. The receiver operating characteristic curve demonstrated an area under the curve of 0.905 (95% CI: 0.880-0.929). Chemiluminescence detected an antigen concentration of 89.98 pg/mL, exhibiting a sensitivity of 83.33% and specificity of 89.76%. In conclusion, the results showed a good agreement with Limulus amebocyte lysate and demonstrated the feasibility of using BDG mutant antibodies for invasive fungal disease diagnosis. The new method based on chemiluminescence for detecting BDG could shorten the sample-to-result time to approximately 30 min, rescue Limulus from being endangered and is resource efficient in terms of equipment and the non-use of a skilled technician.

MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy.

BACKGROUND: MRI-based tumor shrinkage patterns (TSP) after neoadjuvant therapy (NAT) have been associated with pathological response. However, the understanding of TSP after early NAT remains limited. We aimed to analyze the relationship between TSP after early NAT and pathological response after therapy in different molecular subtypes. METHODS: We prospectively enrolled participants with invasive ductal breast cancers who received NAT and performed pretreatment DCE-MRI from September 2020 to August 2022. Early-stage MRIs were performed after the first (1st-MRI) and/or second (2nd-MRI) cycle of NAT. Tumor shrinkage patterns were categorized into four groups: concentric shrinkage, diffuse decrease (DD), decrease of intensity only (DIO), and stable disease (SD). Logistic regression analysis was performed to identify independent variables associated with pathologic complete response (pCR), and stratified analysis according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. RESULTS: 344 participants (mean age: 50 years, 113/345 [33%] pCR) with 345 tumors (1 bilateral) had evaluable 1st-MRI or 2nd-MRI to comprise the primary analysis cohort, of which 244 participants with 245 tumors had evaluable 1st-MRI (82/245 [33%] pCR) and 206 participants with 207 tumors had evaluable 2nd-MRI (69/207 [33%] pCR) to comprise the 1st- and 2nd-timepoint subgroup analysis cohorts, respectively. In the primary analysis, multivariate analysis showed that early DD pattern (OR = 12.08; 95% CI 3.34-43.75; p < 0.001) predicted pCR independently of the change in tumor size (OR = 1.37; 95% CI 0.94-2.01; p = 0.106) in HR+/HER2- subtype, and the change in tumor size was a strong pCR predictor in HER2+ (OR = 1.61; 95% CI 1.22-2.13; p = 0.001) and triple-negative breast cancer (TNBC, OR = 1.61; 95% CI 1.22-2.11; p = 0.001). Compared with the change in tumor size, the SD pattern achieved a higher negative predictive value in HER2+ and TNBC. The statistical significance of complete 1st-timepoint subgroup analysis was consistent with the primary analysis. CONCLUSION: The diffuse decrease pattern in HR+/HER2- subtype and stable disease in HER2+ and TNBC after early NAT could serve as additional straightforward and comprehensible indicators of treatment response. TRIAL REGISTRATION: Trial registration at https://www.chictr.org.cn/ . REGISTRATION NUMBER: ChiCTR2000038578, registered September 24, 2020.

Virtual water flows and drivers in the international trade of agricultural products of the regional comprehensive economic partnership.

The regional comprehensive economic partnership (RCEP) is today the largest free trade area in the world. This paper examines agricultural trade in the RCEP from 2010 to 2019 through the perspective of virtual water. And the drivers of the virtual water flow between China and the RCEP are also explored. The results are as follows: the virtual water flow during the study period was 2,576.51 billion m3. From a temporal perspective, the annual virtual water flow over the study period is characterized by a slow rise-significant fall-slow rise. It has the characteristics of concentration in spatial distribution and water resources and product structure. However, the concentration degree showed a downward trend during the study period. Then, we have divided the major trading into four categories based on whether there is a shortage of water on both sides of the trade. In terms of the drivers of virtual water flows between China and the RCEP, we have used the gravity model to arrive at the following findings: crop yields, bilateral economic scale, and agricultural labor resources are the main drivers. Our research results have reference values for adjusting bilateral agricultural trade and water conservation.

Molecular Coupling Strategy Achieving In Situ Synthesis of Agglomeration-Free Solid Composite Electrolytes.

Solid composite electrolytes (SCEs) synergize inorganic and polymer merits for viable commercial application. However, inferior filler-polymer interfacial stability ultimately leads to the agglomeration of inorganic particles and greatly impedes Li+ migration. Herein, triethoxyvinylsilane (VTEO) is employed to form a strong chemical interaction between poly(vinylene carbonate) (PVC) and montmorillonite (MMT) via in situ solidification, which eliminates the agglomeration and improves interfacial compatibility. Consequently, the obtained solid composite electrolytes (PVC-s-MMT) achieve increased Li+ conductivity (0.4 mS cm-1 at 25 °C), enhanced transference number (0.74), and increased oxidation potential (5.2 V). The Li/PVC-s-MMT/LiFePO4 cells exhibit outstanding cycling performance (>99.5% after 600 cycles) at 1C at room temperature. Moreover, density functional theory (DFT) calculations are applied to uncover the fast interfacial conducting channels of PVC-s-MMT. Our work provides a feasible in situ synthesis method to prepare agglomeration-free SCEs, which is highly compatible with existing battery production processes of liquid electrolytes.

Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease.

BACKGROUND: Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. OBJECTIVES: To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods. METHODS: We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance. RESULTS: A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89). CONCLUSIONS: Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.

Extending Ring-Chain Coupling Empirical Law to Lithium-Mediated Electrochemical Ammonia Synthesis.

With its efficient nitrogen fixation kinetics, electrochemical lithium-mediated nitrogen reduction reaction (LMNRR) holds promise for replacing Haber-Bosch process and realizing sustainable and green ammonia production. However, the general interface problem in lithium electrochemistry seriously impedes the further enhancement of LMNRR performance. Inspired by the development history of lithium battery electrolytes, here, we extend the ring-chain solvents coupling law to LMNRR system to rationally optimize the interface during the reaction process, achieving nearly a two-fold Faradaic efficiency up to 54.78±1.60 %. Systematic theoretical simulations and experimental analysis jointly decipher that the anion-rich Li+ solvation structure derived from ring tetrahydrofuran coupling with chain ether successfully suppresses the excessive passivation of electrolyte decomposition at the reaction interface, thus promoting the mass transfer of active species and enhancing the nitrogen fixation kinetics. This work offers a progressive insight into the electrolyte design of LMNRR system.

In situ observation of a stepwise [2 + 2] photocycloaddition process using fluorescence spectroscopy.

Using highly sensitive and selective in situ techniques to investigate the dynamics of intermediates formation is key to better understand reaction mechanisms. However, investigating the early stages of solid-state reactions/transformations is still challenging. Here we introduce in situ fluorescence spectroscopy to observe the evolution of intermediates during a two-step [2 + 2] photocycloaddition process in a coordination polymer platform. The structural changes and kinetics of each step under ultraviolet light irradiation versus time are accompanied by the gradual increase-decrease of intensity and blue-shift of the fluorescence spectra from the crystals. Monitoring the fluorescence behavior using a laser scanning confocal microscope can directly visualize the inhomogeneity of the photocycloaddition reaction in a single crystal. Theoretical calculations allow us to rationalize the fluorescence behavior of these compounds. We provide a convenient strategy for visualizing the solid-state photocycloaddition dynamics using fluorescence spectroscopy and open an avenue for kinetic studies of a variety of fast reactions.

Correlation between synthetic MRI relaxometry and apparent diffusion coefficient in breast cancer subtypes with different neoadjuvant therapy response.

BACKGROUND: To evaluate the correlation between synthetic MRI (syMRI) relaxometry and apparent diffusion coefficient (ADC) maps in different breast cancer subtypes and treatment response subgroups. METHODS: Two hundred sixty-three neoadjuvant therapy (NAT)-treated breast cancer patients with baseline MRI were enrolled. Tumor annotations were obtained by drawing regions of interest (ROIs) along the lesion on T1/T2/PD and ADC maps respectively. Histogram features from T1/T2/PD and ADC maps were respectively calculated, and the correlation between each pair of identical features was analyzed. Meanwhile, features between different NAT treatment response groups were compared, and their discriminatory power was evaluated. RESULTS: Among all patients, 20 out of 27 pairs of features weakly correlated (r = - 0.13-0.30). For triple-negative breast cancer (TNBC), features from PD map in the pathological complete response (pCR) group (r = 0.60-0.86) showed higher correlation with ADC than that of the non-pCR group (r = 0.30-0.43), and the mean from the ADC and PD maps in the pCR group strongly correlated (r = 0.86). For HER2-positive, few correlations were found both in the pCR and non-pCR groups. For luminal HER2-negative, T2 map correlated more with ADC than T1 and PD maps. Significant differences were seen in T2 low percentiles and median in the luminal-HER2 negative subtype, yielding moderate AUCs (0.68/0.72/0.71). CONCLUSIONS: The relationship between ADC and PD maps in TNBC may indicate different NAT responses. The no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation. CRITICAL RELEVANCE STATEMENT: The relationship between ADC and PD maps in TNBC may indicate different NAT responses, and the no-to-weak correlation between the ADC and syMRI suggests their complementary roles in tumor microenvironment evaluation. KEY POINTS: • The relationship between ADC and PD in TNBC indicates different NAT responses. • The no-to-weak correlations between ADC and syMRI complementarily evaluate tumor microenvironment. • T2 low percentiles and median predict NAT response in luminal-HER2-negative subtype.

Molecular Imprinting Technology Enables Proactive Capture of Nitrogen for Boosted Ammonia Synthesis under Ambient Conditions.

Electrochemical nitrogen reduction reaction (NRR) is a burgeoning field for green and sustainable ammonia production, in which numerous potential catalysts emerge endlessly. However, satisfactory performances are still not realized under practical applications due to the limited solubility and sluggish diffusion of nitrogen at the interface. Herein, molecular imprinting technology is adopted to construct an adlayer with abundant nitrogen imprints on the electrocatalyst, which is capable of selectively recognizing and proactively aggregating high-concentrated nitrogen at the interface while hindering the access of overwhelming water simultaneously. With this favorable microenvironment, nitrogen can preferentially occupy the active surface, and the NRR equilibrium can be positively shifted to facilitate the reaction kinetics. Approximately threefold improvements in both ammonia production rate (185.7 µg h-1 mg-1 ) and Faradaic efficiency (72.9%) are achieved by a metal-free catalyst compared with the bare one. It is believed that the molecular imprinting strategy should be a general method to find further applicability in numerous catalysts or even other reactions facing similar challenges.

2 A cm-2 Level Large-Scale Production of Hydrogen Enabled by Constructing Higher Capacity of Interface "Electron Pocket".

The batch production of high-purity hydrogen is a key problem that restricts the progress of fuel cells and the blueprint for achieving carbon neutrality. Transition-metal chalcogenide heterojunctions exhibit certain activity toward electrochemical overall water splitting (EOWS), but their high-current-density catalytic performances are still unsatisfactory due to the slow kinetic progression (H* or *O → *OOH). Inspired by the "electron pocket" theory, we designed a Ni-Mo bimetallic disulfide interface heterojunction electrocatalyst system (NM-IHJ-V) with high electronic storage capacity around the Fermi level (-0.5 eV, +0.5 eV) (e-DFE), which injects more power into the kinetic progression processes of intermediate species in the EOWS process. Consequently, it achieves a superhigh current density of 2 A cm-2 level for EOWS (only 1.98 V voltage is needed), which is 11.23-fold higher than that of the benchmarked Pt/C//IrO2 (178 mA cm-2@1.98 V), as well as an excellent long-term stability of 200 h. Most strikingly, NM-IHJ-V can efficiently produce hydrogen at currents up to 5 A. Our proposed strategy of constructing catalysts to produce hydrogen at superhigh current density through the electron pocket theory will supply valuable insights for the designing other catalytic systems.

Eliminating Concentration Polarization with Cationic Covalent Organic Polymer to Promote Effective Overpotential of Nitrogen Fixation.

Electrocatalytic nitrogen reduction reaction offers a sustainable alternative to the conventional Haber-Bosch process. However, it is currently restricted by low effective overpotential due to the concentration polarization, which arises from accumulated products, ammonium, at the reaction interface. Here, a novel covalent organic polymer with ordered periodic cationic sites is proposed to tackle this challenge. The whole network exhibits strong positive charge and effectively repels the positively charged ammonium, enabling an ultra-low interfacial product concentration, and successfully driving the reaction equilibrium to the forward direction. With the given potential unchanged, the suppressed overpotential can be much liberated, ultimately leading to a continuous high-level reaction rate. As expected, when this tailored microenvironment is coupled with a transition metal-based catalyst, a 24-fold improvement is generated in the Faradaic efficiency (73.74 %) as compared with the bare one. The proposed strategy underscores the importance of optimizing dynamic processes as a means of improving overall performance in electrochemical syntheses.