Efficient Reduction Research Articles

Highly coordinated Ni-N5 sites for efficient electrocatalytic CO2 reduction toward CO with faradaic efficiency exceeding 99%

Electrochemical production of high value-added CO from CO2 on transition metal-nitrogen-carbon (M−N−C) catalysts is a promising approach to achieve carbon neutral economy, yet the quest for robust catalysts is driven by achieving > 96 % CO faradaic efficiency (FE) under low overpotential and wide potential range. Herein, we report a novel synthetic approach involving post-metallization of the pre-synthesized N-doped carbon (NC-T) support for the fabrication of robust and efficient Ni@NC-T quasi-molecular catalysts toward CO2 electroreduction reaction (CO2RR). The optimum Ni@NC-1100 catalyst exhibited an extremely high FECO > 99 % at −0.72 V vs. reversible hydrogen electrode (RHE). Of interest is the FECO maintained above 96 % over a wide potential window from −0.52 V to −1.12 V. Density functional theory (DFT) calculation validated that the presence of axial pyrrolic-N significantly enhances the Ni-N5 active site for CO2 activation, resulting in the lowest activation energy for the *COOH intermediate generation compared to other axial ligands.

An efficient test suit reduction methodology for regression testing

<span lang="EN-US">This paper's goal is to provide a more effective algorithm for reducing the amount of test cases in a test suit during the regression testing phase. This algorithm divide the entire test suit into equivalence classes in first step and then apply boundary value coverage to select test case out of repeated test cases which has same importance in test suit. This algorithm is based on the concept that before selecting best test cases out of repeated test case in test suit to prepare reduced test suit we can divide all test cases in number of equivalence classes so number of test case under consideration reduced by great extend. This paper proposed a method of experimentation involving test cases from different software application areas; minimization algorithms and the maths and algorithms of minimization algorithms in details. Test case techniques are equivalence portioning and boundary value analysis. Along with this concept, I also discuss a case study to verify and check new algorithm for its efficiency, for that I apply my algorithm on one of the program or group of program. This complete proposed methodology shall be applied to different software applications belonging to soft computing, Engineering software, Financial Software, Cloud Applications, Business Applications, AI and Machine Learning, Data Analytics are being identified. This selection has been made keeping in mind the trends, industrial importance, economic values and research challenges. Minimization in test cases would lead to lesser testing effort and desirable test completion.</span>

Enhancing PAPR reduction efficiency in MIMO-OFDM systems via selective mapping and metaheuristic algorithms

The relentless evolution of communication systems, driven by the demands of 5G and the impending 6G networks, necessitates heightened data rates and spectral efficiency. orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation employed in multi-input multi-output (MIMO) systems, stands as a pivotal technology. Yet, OFDM grapples with challenges, notably the peak-to-average power ratio (PAPR) issue. Selective mapping (SLM) has been a favored technique for mitigating PAPR in OFDM, albeit challenged by computational complexities in its pursuit of discovering optimal phase factors. This paper pioneers a transformative approach by integrating metaheuristic algorithms genetic algorithm (GA), particle swarm optimization (PSO), and the innovative fireworks algorithm (FWA) into SLM for PAPR reduction while minimizing computational complexity. Simulation results not only affirm the efficacy of SLM-based techniques but also spotlight the potential of metaheuristic algorithms in addressing PAPR challenges in modern communication systems. The study transcends single-antenna systems, extending to MIMO-OFDM systems based on WiMAX standards, validating the efficacy of these techniques in multi-antenna configurations. Crucially, the FWA, proposed for the first time in this paper, emerges as a robust candidate, striking an enviable balance between computational efficiency and performance, achieving a notable PAPR reduction with a favorable search number.

Enhancing Methylene Blue Removal through Adsorption and Photocatalysis—A Study on the GO/ZnTiO3/TiO2 Composite

This study focuses on synthesizing and characterizing a graphene oxide/ZnTiO3/TiO2 (GO/ZTO/TO) composite to efficiently remove methylene blue (MB) from water, presenting a novel solution to address industrial dye pollution. GO and ZTO/TO were synthesized by the modified Hummers and sol–gel methods, respectively, while GO/ZTO/TO was prepared using a hydrothermal process. The structural and surface properties of the composite were characterized using various analytical techniques confirming the integration of the constituent materials and suitability for dye adsorption. The study revealed that GO/ZTO/TO exhibits an adsorption capacity of 78 mg g−1 for MB, with only a 15% reduction in adsorption efficiency until the fifth reuse cycle. Furthermore, the study suggests optimal adsorption near neutral pH and enhanced performance at elevated temperatures, indicating an endothermic reaction. The adsorption behavior fits the Langmuir isotherm, implying monolayer adsorption on homogeneous surfaces, and follows pseudo-second-order kinetics, highlighting chemical interactions at the surface as the rate-limiting step. The photocatalytic degradation of MB by GO/ZTO/TO follows pseudo-first-order kinetics, with a higher rate constant than that of GO alone, demonstrating the enhanced photocatalytic activity of the composite. In conclusion, GO/ZTO/TO emerges as a promising and sustainable approach for water purification, through an adsorption process and subsequent photocatalytic degradation.

Photosynthetic Costs and Impact on Epidemiological Parameters Associated with Ht Resistance Genes in Maize Lines Infected with Exserohilum turcicum.

Northern corn leaf blight, caused by Exserohilum turcicum, is mainly controlled by the use of resistant cultivars. Maize lines carrying individual resistance genes B37Ht1, B37Ht2, B37Ht3, and B37Htn1 express different defense symptoms having an impact on the photosynthetic activity, the accumulation of reactive oxygen species, and epidemiological parameters. Plants were inoculated with a race 0 isolate of E.turcicum conferring a compatible interaction with B37 and incompatible interactions with plants carrying resistance genes. Five days postinoculation (dpi), the resistant lines displayed a reduction in leaf CO2 assimilation of 30 to 80% compared with healthy plants. At 14 dpi, inoculated plants of B37Ht1 showed a significant decrease in leaf CO2 assimilation, similar to B37 (up to 94%). The instantaneous carboxylation efficiency was significantly reduced on inoculated plants of the lines B37Ht2, B37Ht3, and B37Htn1 (54 to 81%) at 5 dpi. Curiously, the reduction in carboxylation efficiency for B37 and B37Ht1 (up to 95%) was higher at 14 dpi than at 5 dpi (up to 81%). At 6 dpi, low levels of H2O2 were detected in B37Ht1, in contrast to B37Htn1, where a high H2O2 level and peroxidase activity were observed. The sporulation rate on B37Ht1, B37Ht3, and B37Htn1 decreased by 92% compared with the susceptible control, whereas strong sporulation occurred in lesions on line B37Ht2. The resistance in maize to E. turcicum conferred by Ht resistance genes is associated with photosynthetic costs and may have quite contrasting effects on host physiology and major epidemiological parameters, such as sporulation, which contributes inoculum for secondary infections.

Construction of Cu Single‐Atom Catalysts by Taking Spatial‐Confinement and Chemical‐Anchoring Effect of Hyperbranched Phthalocyanine Copper for Efficient Oxygen Reduction Reaction

AbstractAtomically dispersed nonprecious metal‐based catalysts have been considered as the most promising alternatives to Pt‐based catalysts since their excellent catalytic activities and almost 100 % atom utilization in oxygen reduction reaction. However, the agglomeration of metal atoms is unavoidable during pyrolysis process, thus leads to the decrease of electrocatalytic performance. Herein, hyperbranched phthalocyanine copper (HCuPc) wrapping nano‐silica is synthesized via in situ polymerization and served as precursor for preparing atomically dispersed Cu−N−C electrocatalysts. Owing to the confinement effect of chemical‐anchoring and spatial‐hindrance, the migration and agglomeration of Cu atoms are restricted in carbonization process. The aberration‐corrected high‐angle annular dark‐field scanning transmission electron microscopy and X‐ray photoelectron spectroscopy (XPS) are performed to confirm the atomically dispersed of as‐synthesized catalyst, which is labelled as HCu−N−C/SiO2. In addition, the HCu−N−C/SiO2 possess superior ORR electrocatalytic activities with a half‐wave potential of 0.874 V vs RHE and a limiting current density of 5.7 mA cm−2. The zinc‐air batteries assembled with HCu−N−C/SiO2 catalyst exhibit a high specific capacity of 789 mAh g−1 as well as a maximum discharge power density of 176 mW cm−2. This work proves that hyperbranched phthalocyanine structure could be a useful confined framework to the fabrication of singles‐atom catalysts.

Functionalization of niobium nitrogen-doped titanium dioxide (TiO2) nanoparticles with ethanolic extracts of Mentha arvensis.

Titanium dioxide (TiO2) nanoparticles have gained significant attention due to their wide-ranging applications. This research explores an approach to functionalize Niobium Nitrogen Titanium Dioxide nanoparticles (Nb-N-TiO2 NPs) with Mentha arvensis ethanolic leaf extracts. This functionalization allows doped NPs to interact with the bioactive compounds in extracts, synergizing their antioxidant activity. While previous studies have investigated the antioxidant properties of TiO2 NPs synthesized using ethanolic extracts of Mentha arvensis, limited research has focused on evaluating the antioxidant potential of doped nanoparticles functionalized with plant extracts. The characterization analyses are employed by Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and Ultraviolet-visible (UV-Vis) spectroscopy to evaluate these functionalized doped nanoparticles thoroughly. Subsequently, the antioxidant capabilities through the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric-reducing antioxidant power (FRAP) assays have been assessed. Within functionalized Nb-N-TiO2, the FTIR has a distinctive peak at 2350, 2010, 1312, 1212, and 1010cm-1 with decreased transmittance associated with vibrations linked to the Nb-N bond. SEM revealed a triangular aggregation pattern, 500nm to 2µm of functionalized Nb-N-TiO2 NPs. Functionalized doped Nb-N-TiO2 NPs at 500µgmL-1 exhibited particularly robust antioxidant activity, achieving an impressive 79% efficacy at DPPH assessment; meanwhile, ferric reduction efficiency of functionalized doped Nb-N-TiO2 showed maximum 72.16%. In conclusion, doped Nb-N-TiO2 NPs exhibit significantly enhanced antioxidant properties when functionalized with Mentha arvensis ethanolic extract compared to pure Nb-N-TiO2 manifested that doped Nb-N-TiO2 have broad promising endeavors for various biomedicine applications.

Fluorine Modification Promoted Water Dissociation into Atomic Hydrogen on a Copper Electrode for Efficient Neutral Nitrate Reduction and Ammonia Recovery.

Electrocatalytic nitrate reduction to ammonia (NITRR) offers an attractive solution for alleviating environmental concerns, yet in neutral media, it is challenging as a result of the reliance on the atomic hydrogen (H*) supply by breaking the stubborn HO-H bond (∼492 kJ/mol) of H2O. Herein, we demonstrate that fluorine modification on a Cu electrode (F-NFs/CF) favors the formation of an O-H···F hydrogen bond at the Cu-H2O interface, remarkably stretching the O-H bond of H2O from 0.98 to 1.01 Å and lowering the energy barrier of water dissociation into H* from 0.64 to 0.35 eV at neutral pH. As a benefit from these advantages, F-NFs/CF could rapidly reduce NO3- to NH3 with a rate constant of 0.055 min-1 and a NH3 selectivity of ∼100%, far higher than those (0.004 min-1 and 9.2%) of the Cu counterpart. More importantly, we constructed a flow-through coupled device consisting of a NITRR electrolyzer and a NH3 recovery unit, realizing 98.1% of total nitrogen removal with 99.3% of NH3 recovery and reducing the denitrification cost to $5.1/kg of N. This study offers an effective strategy to manipulate the generation of H* from water dissociation for efficient NO3--to-NH3 conversion and sheds light on the importance of surface modification on a Cu electrode toward electrochemical reactions.

Enabling Logistics Automation in Nanofactory: Cobalt Phosphide Embedded Metal-Organic Frameworks for Efficient Electrocatalytic Nitrate Reduction to Ammonia.

Electrocatalytic nitrate reduction reaction (NitRR) in neutral condition offers a promising strategy for green ammonia synthesis and wastewater treatment, the rational design of electrocatalysts is the cornerstone. Inspired by modern factory design where both machines and logistics matter for manufacturing, we report that cobalt phosphide (CoP) nanoparticles embedded in zinc-based zeolite imidazole frameworks (Zn-ZIF) function as a nanofactory with high performance. By selective phosphorization of bimetallic ZnCo-ZIF, the generated CoP nanoparticles act as "machines" (active sites) for molecular manufacturing (NO3 - to NH4 + conversion). The purposely retained framework (Zn-ZIFs) with positive charge promotes logistics automation, i.e., the automatic delivery of NO3 - reactants and timely discharge of NH4 + products in-and-out the nanofactory due to electrostatic interaction. Moreover, the interaction between Zn-ZIF and CoP modulates the Co sites into electron insufficient state with upshifted d-band center, facilitating the reduction/hydrogenation of NO3 - to ammonia and restricting the competitive hydrogen evolution. Consequently, the assembled CoP/Zn-ZIF nanofactory exhibits superior NitRR performances with a high Faraday efficiency of ≈97% and a high ammonia yield of 0.89mmol cm-1 h-1 in neutral condition, among the best of reported electrocatalysts. Our work provides new insights into the design principles of efficient NitRR electrocatalysts. This article is protected by copyright. All rights reserved.

Trajectory analysis of circulating tumor cells through contorted deterministic lateral displacement array for unruptured trapping: a simulation study

During the multistage process of cancer spread, fragments of cells branch out from the primitive tumor tissue and scatter throughout the body by blood flow stream or lymph, which are termed as circulating tumor cells (CTCs), regarded as an important biomarker for early cancer diagnosis. Deterministic lateral displacement (DLD) is one of the most efficient passive type particle isolation techniques which functions on asymmetrical laminar flow diversion around the placed microposts forming an array, based on the critical dimeter of the device. In this simulation study, complete trajectory analysis of CTCs and WBCs has been performed using COMSOL Multiphysics software with respect to the angular orientation of sample inlet channel. A simulated model of an asymmetric DLD array-based microfluidic device with latest empirical expression for critical diameter has been presented with optimized sample inlet orientation so as to maintain perfect separation efficiency of CTCs along with arrangement for unruptured trapping of CTCs and WBCs. The approximate CTC isolation efficiency was obtained above 95% for sample inlet inclinations up to 0.5°, and further tilt showed reduction in efficiency. Migration angle of CTC trajectory for the modeled device was obtained around 15° for both the sample inlet orientations leading to least intermingling of CTCs and WBCs. A smaller number of CTC–WBC interaction points was observed for clockwise sample inlet tilt compared to the anticlockwise displacement reducing possibilities of cell rupture. The shear rate around central microposts was found to be higher as well in clockwise sample inlet orientation. This simulation study establishes that sample inlet clockwise tilting of maximum around 0.5°–0.7° leads to better CTC isolation and provides better chances of unruptured trapping of cells at the designated outlets. The results of this study provide an approach toward further optimization of DLD devices' functioning and, thus, could help fabricate better DLD-based microfluidic devices for efficient trapping of CTCs.

Sustainedly High‐Rate Electroreduction of CO2 to Multi‐Carbon Products on Nickel Oxygenate/Copper Interfacial Catalysts

AbstractCopper (Cu) is the most attractive electrocatalyst for CO2 reduction to multi‐carbon (C2+) products with high economic value in considerable amounts. However, the rational design of a structurally stable Cu‐based catalyst that can achieve high activity and stability towards C2+ products remain a grand challenge. Here, a highly stable nickel oxygenate/Cu electrocatalyst is developed with abundant NiOOH/Cu interfaces by in situ electrochemical reconstruction. The nickel oxygenate/Cu electrocatalyst achieves a superior Faradaic efficiency of 86.3 ± 3.0% and a record partial current density of 2085 A g−1 for C2+ products with long‐term stability. In situ experimental and theoretical studies demonstrates that the exceptional performance in generating C2+ products is attributed to the presence of the NiOOH/Cu interfaces which increase *CO coverage, lower energy barrier for *CO coupling and stabilize *OCCO simultaneously. This work provides new insights into the rational design of electrocatalysts to achieve stable and efficient electrocatalytic CO2 reduction capabilities.

Phased assembly of neo-sex chromosomes reveals extensive Y degeneration and rapid genome evolution in Rumex hastatulus.

Y chromosomes are thought to undergo progressive degeneration due to stepwise loss of recombination and subsequent reduction in selection efficiency. However, the timescales and evolutionary forces driving degeneration remain unclear. To investigate the evolution of sex chromosomes on multiple timescales, we generated a high-quality phased genome assembly of the massive older (<10MYA) and neo (<200,000 years) sex chromosomes in the XYY cytotype of the dioecious plant Rumex hastatulus and a hermaphroditic outgroup R. salicifolius. Our assemblies, supported by fluorescence in situ hybridization, confirmed that the neo-sex chromosomes were formed by two key events: an X-autosome fusion and a reciprocal translocation between the homologous autosome and the Y chromosome. The enormous sex-linked regions of the X (296 MB) and two Y chromosomes (503 MB) both evolved from large repeat-rich genomic regions with low recombination; however, the complete loss of recombination on the Y still led to over 30% gene loss and major rearrangements. In the older sex-linked region, there has been a significant increase in transposable element abundance, even into and near genes. In the neo sex-linked regions, we observed evidence of extensive rearrangements without gene degeneration and loss. Overall, we inferred significant degeneration during the first 10 million years of Y chromosome evolution but not on very short timescales. Our results indicate that even when sex chromosomes emerge from repetitive regions of already-low recombination, the complete loss of recombination on the Y chromosome still leads to a substantial increase in repetitive element content and gene degeneration.

Magnetic induction heating-assisted synthesis of biodiesel using an alumina/iron oxide nanocatalyst

While generating biodiesel from vegetable oils presents various advantages over fossil fuels, ongoing actions aim to improve the efficiency of this production process. Emphasis is placed on optimizing experimental conditions, including the catalyst selection, reaction media and the energy source for heating and mixing, thereby revealing existing research gaps in biodiesel production. In this sense, we have designed a magnetic nanocatalyst based on iron oxide nanoparticles (IONPs) of 18 nm in diameter incorporated within an alumina matrix of around 500 nm infused with potassium hydroxide that provides the catalyst's mesoporosity and basicity. Magnetization analyses confirmed the superparamagnetic behaviour of the nanocatalyst at room temperature and a saturation magnetisation high enough to ease magnetic recovery for reuse. Additionally, magnetic nanoparticles can serve as nanoheaters when subjected to an alternating magnetic field. The heating efficiency of the isolated IONPs was assessed under various frequency and field conditions, yielding specific absorption rate values of up to 80 W/g. Such heating capacity has allowed the synthesis of fatty acid methyl ester (FAMEs), which constitute the biodiesel at 65 °C under optimal field conditions (100 kHz and 48 kA/m) and ideal reaction parameters: 5 % catalyst, methanol/oil ratio 12:1 and 6 h of reaction, with a conversion of up to 98.6 % determined through NMR characterization of the FAMEs and a 95.6 % yield. FAMEs presence was confirmed by optimizing a swift and efficient FTIR method and their purity by TLC. Overall, the designed nanocatalyst presented for FAME synthesis, which incorporates magnetic separability and effective heating capabilities, holds great promise for cost reduction and process efficiency.

Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition

AbstractThe retail industry encounters huge obstacles with computer vision (CV) technology due to frequent model retraining with changing products and time-consuming, costly data annotation. Previous research in this field has been primarily focused on optimizing model performance rather than minimizing annotation effort. Therefore, the main idea of this paper is to evaluate active learning as a method to minimize annotation effort in the retail industry. The MVTEC Densely Segmented Supermarket dataset is used to evaluate various active learning methods such as the Least Confident, Entropy and Cost-Effective Active Learning (CEAL) along with Mask R-CNN model. The results demonstrate that annotating only 20.83$$-$$ - 24.34% of the data achieves 95% of the full dataset’s performance. When training, out-of-sample data share similar characteristics, the Least Confident and CEAL methods reduce annotation requirements by 7.7$$-$$ - 15.7% while maintaining 95% and 97% of the full dataset’s performance. However, the Entropy method under-performs compared to the random selection baseline. Ultimately, none of the methods show a clear advantage when the data characteristics differ between training and out-of-sample data. Finally, the proposed active learning methods on an industry-specific retail dataset remarkably propels the development of highly efficient and cost-effective CV solutions meticulously tailored for the retail industry.

Theoretical designs of ORR/OER single‐atom catalysts TM@Ti2CT2 (T = O, S, Cl)

AbstractDriven by the goal of establishing a fossil‐fuel‐free and nuclear‐power‐free economy based on renewable energy, metal‐air batteries are regarded as promising energy conversion and storage devices. Developing efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) bifunctional electrocatalysts for the air electrode of metal‐air batteries is becoming increasingly important. In this work, 36 transition metal (TM) single‐atom catalysts are designed based on MXenes Ti2CT2 with different surface terminal atoms (T = O, S, Cl), and their ORR/OER catalytic activity and stability are evaluated by the density functional theory. Ni@Ti2CO2, Pd@Ti2CS2, and Co@Ti2CCl2 are found to exhibit good catalytic activity with ORR/OER overpotentials of .54 V/.62 V, .59 V/.29 V, .44 V/.40 V. The aggregation behavior of three catalysts is estimated by comparing the average binding energy of one, two, three, and four TM atoms anchored on Ti2CT2. This work cannot only provide a theoretical guide to develop bifunctional single‐atom catalysts, but also help us understand the effect of terminal atoms on the electronic structures and catalytic activity of TM@Ti2CT2.

Doping Ferrocene-Based Conjugated Microporous Polymers with 7,7,8,8-Tetracyanoquinodimethane for Efficient Photocatalytic CO2 Reduction

The design and synthesis of organic photocatalysts remain a great challenge due to their strict structural constraints. However, this could be mitigated by achieving structural flexibility by constructing permanent porosity into the materials. Conjugated microporous polymers (CMPs) are an emerging class of porous materials with an amorphous, three-dimensional network structure, which makes it possible to integrate the elaborate functional groups to enhance photocatalytic performance. Here, we report the synthesis of a novel CMP, named TAPFc-TFPPy-CMP, constructed by 1,1′3,3′-tetra(4-aminophenyl)ferrocene (TAPFc) and 1,3,6,8-tetrakis(4-formylphenyl)pyrene (TFPPy) monomers. The integration of the p-type dopant 7,7,8,8-tetracyanoquinodimethane (TCNQ) into the TAPFc-TFPPy-CMP improved the light adsorption performance, leading to a decrease in the optical bandgap from 2.00 to 1.43 eV. The doped CMP (TCNQ@TAPFc-TFPPy-CMP) exhibited promising catalytic activity in photocatalytic CO2 reduction under visible light, yielding 546.8 μmol g−1 h−1 of CO with a selectivity of 96% and 5.2 μmol g−1 h−1 of CH4. This represented an 80% increase in the CO yield compared to the maternal TAPFc-TFPPy-CMP. The steady-state photoluminescence (PL) and fluorescence lifetime (FL) measurements reveal faster carrier separation and transport after the doping. This study provides guidance for the development of organic photocatalysts for the utilization of renewable energy.

Boron-Nitrogen-Embedded Polycyclic Aromatic Hydrocarbon-Based Controllable Hierarchical Self-Assemblies through Synergistic Cation-π and C-H···π Interactions for Bifunctional Photo- and Electro-Catalysis.

Boron-Nitrogen-embedded polycyclic aromatic hydrocarbons (BN-PAHs) as novel π-conjugated systems have attracted immense attention owing to their superior optoelectronic properties. However, constructing long-range ordered supramolecular assemblies based on BN-PAHs remains conspicuously scarce, primarily attributed to the constraints arising from coordinating multiple noncovalent interactions and the intrinsic characteristics of BN-PAHs, which hinder precise control over delicate self-assembly processes. Herein, we achieve the successful formation of BN-PAH-based controllable hierarchical assemblies through synergistically leveraged cation-π and C-H···π interactions. By carefully adjusting the solvent conditions in two progressive assembly hierarchies, the one-dimensional (1D) supramolecular assemblies with "rigid yet flexible" assembled units are first formed by cation-π interactions, and then they can be gradually fused into two-dimensional (2D) structures under specific C-H···π interactions, thus realizing the precise control of the transformation process from BN-PAH-based 1D primary structures to 2D higher-order assemblies. The resulting 2D-BNSA, characterized by enhanced electrical conductivity and ordered 2D layered structure, provides anchoring and dispersion sites for loading two appropriate nanocatalysts, thus facilitating the efficient photocatalytic CO2 reduction (with a remarkable CH4 evolution rate of 938.7 μmol g-1 h-1) and electrocatalytic acetylene semihydrogenation (reaching a Faradaic efficiency for ethylene up to 98.5%).

Photocatalytic CO2 Reduction Using Mixed Catalytic Systems Comprising an Iron Cation with Bulky Phenanthroline Ligands.

This study reports on efficient photocatalytic CO2 reduction reactions using mixed catalytic systems of an Fe ion source and various 1,10-phenanthroline derivatives (R1R2p) as ligands in the presence of triethanolamine (TEOA). As the relatively bulky substituents at positions 2 and 9 of R1R2p weakened the ability to coordinate to the Fe ion, the Fe ion formed TEOA complexes. The free R1R2p accepted an electron from the reduced photosensitizer through proton-coupled electron transfer (PCET) using protons of TEOA dissolved in a CH3CN solution in a CO2 atmosphere as the initial step of the catalytic cycle. Although the mixed system of the nonsubstituted 1,10-phenanthroline generates a stable tris(phenanthroline)-Fe(II) complex in solution, this complex could not function as a CO2 reduction catalyst. The mechanism in which R1R2p interacts with the Fe ion after PCET was proposed for this efficient photocatalytic CO2 reduction. The proposed photocatalytic system using the 2,9-di-sec-butyl-phenanthroline ligand could produce CO with high efficiency (quantum yield of 8.2%) combined with a dinuclear Cu(I) complex as a photosensitizer.

Smart Cities and Smart Supply Chain: Integration for Sustainable Urban Development.

As urbanization accelerates globally, the concept of smart cities emerges as a promising solution to address the multifaceted challenges of sustainable urban development. Smart cities leverage advanced technologies to enhance efficiency, sustainability, and quality of life for their residents. Concurrently, the evolution of supply chain management towards smart supply chains has gained traction, driven by the imperative of optimizing logistics, minimizing waste, and enhancing resilience. This paper explores the integration of smart cities and smart supply chains as a holistic approach to foster sustainable urban development. The integration of smart cities and smart supply chains presents a symbiotic relationship wherein advancements in one domain catalyze improvements in the other. Smart cities rely on seamless and efficient supply chain operations to ensure the smooth flow of goods and services, essential for meeting the needs of urban inhabitants. [1],[2] Conversely, smart supply chains benefit from the data-rich environment and infrastructure of smart cities to optimize routing, inventory management, and last-mile delivery, thereby reducing environmental impact and enhancing overall efficiency. Key components of this integration include the utilization of Internet of Things (IoT) devices, big data analytics, artificial intelligence (AI), and blockchain technology to enable real-time monitoring, predictive analytics, and transparent, secure transactions throughout the urban supply chain. By harnessing these technologies, cities can achieve significant improvements in resource utilization, energy efficiency, and carbon footprint reduction. Furthermore, the paper examines the role of public-private partnerships (PPPs) and regulatory frameworks in facilitating the integration of smart cities and smart supply chains. Collaborative efforts between government entities, industry stakeholders, and technology providers are essential to overcome barriers such as data privacy concerns, interoperability challenges, and investment constraints. In conclusion, the integration of smart cities and smart supply chains represents a promising pathway towards achieving the goals of sustainability, resilience, and prosperity in urban environments. By embracing innovative technologies and fostering collaboration, cities can pave the way for a more efficient, equitable, and environmentally conscious future.

Cannabis use and dependence among festival attendees: results from the French OCTOPUS survey

BackgroundChronic use of cannabis is associated with an increased risk of psychosocial, mental and physical health impairments. Sociohealth institutions reach a very limited proportion of cannabis users in need of treatment. Using data collected from festival attendees, this study aimed to estimate the prevalence of dependent cannabis users and to characterize cannabis dependence.MethodsWe used data from the cross-sectional OCTOPUS survey carried out at 13 music events in the French department of Loire-Atlantique between July 2017 and July 2018. 383 participants aged 18 or older underwent a face-to-face interview about their basic sociodemographics, tobacco use, alcohol use and past-year substance use. Using the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) criteria, we estimated the prevalence of dependent cannabis users and characterized their dependence.ResultsMore than two-thirds of participants reported that they had used cannabis in the past 12 months. Among 194 regular cannabis users (at least monthly), 63.4% were dependent. At least 40% of regular users reported health and/or social consequences of cannabis use. Compared to nondependent cannabis users, dependent cannabis users were more likely to be stimulant users and hallucinogen users.ConclusionsDependent cannabis use is common among festival attendees, especially among stimulant or hallucinogen users. Festival settings may be important arenas for i) implementing efficient harm reduction measures to prevent dependence and ii) providing information on care structures and promoting the use of care to dependent users. In addition, healthcare professionals should be aware of trends in polysubstance use among dependent cannabis users.