bluuebunny/crossref_metadata_2025_split huggingface dataset:
New Facile Continuous Microwave Pipeline Technology for the Preparation of Highly Stable and Active Carbon‐Supported Platinum Catalyst
Authors: Feng Zhanxiong , Lu Jiapeng , Zhang Chuang , Liu Dezheng , Jia Zhiyong , Wang Yun , Wang Cheng 
Published: January 2024

AbstractNowadays, the depletion of non‐renewable energy sources has become a prominent issue, and environmental concerns such as air pollution stemming from vehicle emissions have reached a critical stage. In this manuscript, we introduce a novel approach for the fabrication of Pt/C catalysts on a large scale, utilizing a simple, rapid, and continuous pipeline microwave synthesis method. Moreover, we incorporate a heating treatment process in an N2−H2 (5 % H2) environment to enhance the activity and durability of the catalyst. The synthesized Pt/C‐400 catalyst demonstrates an impressive electrochemical active surface area of 103.2 m2/gpt and a mass‐specific activity of 315 mA/mg at a half‐wave potential of 0.9 V. Following 30000 cycles of Pt attenuation testing and 30000 cycles of carrier attenuation testing, the Pt/C‐400 catalyst exhibits a remarkable retention rate of 75 %. Furthermore, based on single‐cell testing, the Pt/C‐400 catalyst achieves a voltage of 0.606 V at a current density of 2000 mA/cm2, surpassing the performance of other Pt/C catalysts discussed in this article. This study presents an efficient and practical method for large‐scale synthesis of high‐performance and durable catalysts. The findings hold significant implications for the commercialization of Proton Exchange Membrane Fuel Cells and contribute to addressing the pressing need for sustainable energy solutions.
Recent Progress in Electric‐field Enhanced 3D Graphene Electrodes using Laser Scribing for In‐plane Microsupercapacitors
Authors: Pak Sangyeon , Jang A‐Rang , Lee Young‐Woo 
Published: January 2024

AbstractThe increasing demand for miniature, flexible electronic devices have fueled the need for compact and high‐performing energy storage solutions. Microsupercapacitors (mSCs) with reduced dimension and novel electrode design have gained prominence. This concept paper summarizes and views the recent advancements in mSCs with a focus on 3D graphene electrodes and their novel electrode design to increase energy performance of the devices. Especially, we focus on these 3D graphene structures fabricated using a laser‐scribing method which offer an efficient, cost‐effective approach for enhanced mSC performance. Further, this work delves into the vital link between the electrical field effect and geometrically engineered interdigitated electrodes, which is pivotal for maximizing the ion transport and mSC energy storage performance. The insights presented here are promising for meeting the power requirements of future miniature electronics.
Formation of Sterically Congested C−N Bonds by Electrochemical Reductive Coupling of Amines and α‐Bromocarboxamides
Authors: Ghosh Titli , Kaizawa Hazuki , Funato Shohei , Rahman M. Azadur , Sasaki Norihiko , Nokami Toshiki , Abe Manabu , Nishikata Takashi 
Published: January 2024

AbstractNucleophilic substitution of α‐bromocarboxamide with amines have been demonstrated to synthesize sterically congested C−N bonds. Electrochemical reductive coupling is an efficient route to access hindered amino acid derivatives possessing a quaternary carbon center with excellent yields under mild reaction conditions. Cyclic voltammetry analyses indicated the cathodic reduction of α‐bromocarboxamides in the presence of amines as nucleophiles. The control experiment using the N‐methyl derivative of α‐bromocarboxamide suggested that the aziridinone is the most probable intermediate in this method.
Electrocatalytic Activity of CO2 Reduction to CO on Cadmium Sulfide Enhanced by Chloride Anion Doping
Authors: Wang Mingyan , Cao Weiqi , Yu Jingkun , Yang Dexin , Qi Kongsheng , Zhao Yuhua , Hua Zhixin , Li Hongping , Lu Siyu 
Published: January 2024

AbstractThe electrocatalytic CO2 reduction (ECR) to produce valuable fuel is a promising process for addressing atmospheric CO2 emissions and energy shortages. In this study, Cl‐anion doped cadmium sulfide structures were directly fabricated on a nickel foam surface (Cl/CdS‐NF) using an in situ hydrothermal method. The Cl‐anion doping could significantly improve ECR activity for CO production in ionic liquid and acetonitrile mixed solution, compared to pristine CdS. The highest Faradaic efficiency of CO is 98.1 % on a Cl/CdS‐NF‐2 cathode with an excellent current density of 137.0 mA cm−2 at −2.25 V versus ferrocene/ferrocenium (Fc/Fc+, all potentials are versus Fc/Fc+ in this study). In particular, CO Faradaic efficiencies remained above 80 % in a wide potential range of −2.05 V to −2.45 V and a maximum partial current density (192.6 mA cm−2) was achieved at −2.35 V. The Cl/CdS‐NF‐2, with appropriate Cl anions, displayed abundant active sites and a suitable electronic structure, resulting in outstanding ECR activity. Density functional theory calculations further demonstrated that Cl/CdS is beneficial for increasing the adsorption capacities of *COOH and *H, which can enhance the activity of the ECR toward CO and suppress the hydrogen evolution reaction.
A machine learning approach for modelling and optimization of complex systems: Application to condensate stabilizer plants
Authors: Alkatheri Mohammed , Hourfar Farzad , Khoshnevisan Ladan , Fgaier Hedia , Almansoori Ali , Elkamel Ali 
Published: January 2024

AbstractRecent advancements in supervised machine learning tools have demonstrated their ability to achieve accurate and efficient prediction results. In this paper, we leverage these tools as alternative approaches to model a specific application in the gas industry, based on operating data. The chosen application is a natural gas condensate stabilization process, in which light end components are removed to reduce condensate vapour pressure, meeting storage and transportation specifications. Here, we develop and evaluate various supervised machine learning models to predict the performance of two industrial condensate stabilizer units. By utilizing large datasets from these units and encompassing comprehensive operating data of input–output variables, we not only demonstrate the capability of these techniques to offer reliable and accurate predictions but also shed light on their potential impacts and implementations. The impacts of applying selected AI and machine learning algorithms are two‐fold. First, our research presents an innovative approach to process modelling and optimization in the gas industry, showing the potential for enhanced operational efficiency, profitability, and safety. Second, we propose a data‐driven surrogate‐based optimization framework, where the generated machine learning models can replace detailed first‐principle models, offering a streamlined method to find optimal values for variables to reduce operational energy consumption. Furthermore, we address the validation requirements of our machine learning models, ensuring their robustness and reliability in real‐world applications. By incorporating rigorous validation procedures, we guarantee the quality of our predictions and support their practical implementation. In conclusion, our research not only highlights the capabilities of machine learning in gas industry applications but also emphasizes their potential impacts and contributions to operational excellence. So, the presented approach can pave the way for improved performance, efficiency, and profitability in the gas industry.
Virtual reality modeling application based on multi perspective and deep learning in the new media presentation and brand building of Dongguan City memory
Authors: Ye Yunfeng , Liu Huifang , Kuang Wenhui , Chen Wenxuan 
Published: January 2024

AbstractTo help the new media presentation and brand building of Dongguan City memory, a virtual reality modeling model based on multi‐perspective and deep learning is proposed. First, in order to address the issue of imbalanced input and output information in depth map prediction tasks, as well as poor accuracy of predicted depth map boundaries, a depth map prediction model based on multiple perspectives and deep learning is built. Then, a single perspective modeling framework is proposed to address the scarcity of perspectives in practical situations, and a dynamic fusion model is built for single‐view virtual reality scenes based on multi‐view generation networks. The results indicated that the mean square error, average relative error, and average logarithmic error were minimized at 0.52, 0.138, and 0.068, respectively. The multi‐threshold accuracy index demonstrated peak values at 0.772, 0.8821, and 0.947, respectively. The grid simplification algorithm exhibited the shortest running times at 1.57, 2.52, 3.91, and 6.53 s, respectively. Moreover, the single‐view modeling frame displayed the smallest angle distance at 0.1449, while the overlap degree of the point cloud scene reached the highest levels at 77.47, 79.49, 83.5, and 84.47, respectively. To sum up, the model has a good application effect in virtual reality modeling and positively affects virtual reality technology development.
Fluorescent Enzymatic Sensor Based Glucose Oxidase Modified Bovine Serum Albumin‐Gold Nanoclusters for Detection of Glucose
Authors: Abraham Merin K , Madanan Anju S , Varghese Susan , R. S. Lekshmi , Shkhair Ali Ibrahim , N. S. Vijila , George Sony 
Published: January 2024

AbstractAn enzymatic fluorescent probe is developed for the selective detection of glucose. In this work, a Bovine Serum Albumin stabilized gold nanocluster (BSA‐AuNCs) was synthesized by microwave assisted method, and it is modified with glucose oxidase, thereby a fluorescent enzymatic sensor (BSA‐AuNCs@GoX) was designed for the sensitive detection of glucose with a limit of detection of 0.03 mM. The red fluorescence exhibited by the probe is quenched by the production of H2O2 on addition of glucose via. a static quenching mechanism from UV visible absorption and Fluorescence lifetime results. The developed probe exhibits good selectivity and sensitivity with other coexisting molecular species such as glycine, creatinine, methionine, histidine, uric acid, albumin, and ions such as sodium, potassium, calcium, magnesium, zinc etc. that appear in the body fluid. The practical applicability was studied in paper strip and extended its reproducibility in biological matrixes such as human serum and urine and found a good recovery percentage of 94–101 %. By this way, we have fabricated an effective fluorescent enzymatic “turn‐off” sensing probe for the detection of glucose.
Facile Synthesis of High‐Entropy Alloy Nanowires for Electrocatalytic Alcohol Oxidation
Authors: Ling Xinyi , Ao Yunyun , Zheng Jinyu , Han Min , Xu Dongdong 
Published: January 2024

AbstractConsidering the structural and compositional advantages of high‐entropy alloy (HEA) as high‐efficient electrocatalysts, we here present a facile method to prepare high‐entropy alloy nanowires with seven elements in an aqueous solution. The as‐synthesized PdPtCuAgAuPbCo nanowires possess dispersed one‐dimensional morphology and exhibit enhanced electrocatalytic performance with the mass activity of 9.9 A mgPd+Pt−1 toward ethanol electrooxidation. The HEA nanowires also perform superior stability, resistance to CO poisoning, and good electrocatalytic activities toward other alcohols (e. g., ethylene glycol and methanol) oxidation. The synthesis strategy is easy to operate with low cost and has wide application prospects for preparing desired electrocatalysts for fuel cells.
Design and synthesis of vancomycin‐functionalized ZnFe2O4 nanoparticles as an effective antibacterial agent against methicillin‐resistant Staphylococcus aureus
Authors: Akbari Minoo , Rezayan Ali Hossein , Rastegar Hossein , Alebouyeh Mahmoud , Yahyaei Mohammad 
Published: January 2024

AbstractThe emergence of antibiotic‐resistant bacterial infections is a principal threat to global health. Functionalization of nanomaterial with antibiotics is known as a useful method for increasing the effectiveness of existing antibiotics. In this study, vancomycin‐functionalized ZnFe2O4 nanocomposite (ZnFe2O4@Cell@APTES@Van) was synthesized, and its functional groups and particle size were characterized using Fourier‐transform infrared spectroscopy, thermogravimetric analysis, dynamic light scattering, scanning electron microscope, and transmission electron microscopy. The antibacteria activity of the synthesized nanocomposite was evaluated using minimum inhibitory concentration and minimum bactericidal concentration against Escherichia coli, Staphylococcus aureus, and methicillin‐resistant Staphylococcus aureus (MRSA). Cytotoxicity assay was done by 2,3‐bis‐(2‐methoxy‐4‐nitro‐5‐sulfophenyl)‐2H‐tetrazolium‐5‐carboxanilide method. Characterization analyses of synthesized nanocomposite confirmed the binding of vancomysin on the surface of ZnFe2O4@Cell@APTES. Nanocomposite exhibited an aggregated semi‐spherical structure with hydrodynamic radii of ∼382 nm. In vitro antibacterial activity test showed that vancomycin and vancomycin functionalized ZnFe2O4 have no antibacterial effect against E. coli. S. aureus was sensitive to vancomycin and ZnFe2O4@Cell@APTES@Van NPs and ZnFe2O4 NPs did not improve vancomycin antibacterial activity against these bacteria. MRSA is resistant to vancomycin while ZnFe2O4@Cell@APTES@Van NPs was efficient in inhibiting MRSA growth. In summary, this study showed that attachment of vancomycin to ZnFe2O4 NPs was increased its antibacterial activity against MRSA.
Participant Misrepresentation in Online Focus Groups: Red Flags and Proactive Measures
Authors: Andrew Lesley , Gizzarelli Emily , Estai Mohamed , Wallace Ruth 
Published: January 2024

ABSTRACTCovid‐19 public health measures prompted a significant increase in online research. This approach has several benefits over face‐to‐face data‐collection methods, including lower cost and wider geographical reach of participants. Yet when the online data‐collection instrument is a survey, there are also well‐documented drawbacks of participant misrepresentation and related data‐authenticity issues. However, the scholarly literature has not looked at participant misrepresentation in online focus‐group empirical research. This case study communicates a concerning situation that arose during our research project: dishonest participant behavior threatened the integrity and validity of our data collected through online focus‐group sessions as well as e‐surveys. We describe the study context, initial red flags alerting us to the issue, subsequent investigations, and implications for research ethics, funding, and data quality. We conclude with a discussion of potential steps to safeguard future online focus‐group research against similar issues.
The “Young Athlete Body Project”—A pilot study evaluating the acceptability of and results from an eating disorder prevention program for adolescent athletes
Authors: Sundgot‐Borgen Christine , Wisting Line , Sundgot‐Borgen Jorunn , Steenbuch Karoline , Skrede Jenny Vik , Nilsen Karoline , Stice Eric , Mathisen Therese Fostervold 
Published: January 2024

AbstractBackgroundThe high frequency of eating disorders (EDs) in sports speaks of a need for early‐stage preventive measures.ObjectivesThis study evaluated the acceptability of an age, sex, and sports adapted version of the “Body Project” and changes in mental health symptoms.MethodsThis noncontrolled pilot study included a class of athletes from 18 sports (N = 73, 13–14 years) at a sport‐specialized junior high school in six small‐group workshops. We interviewed 34 athletes on program acceptability, and all athletes responded to questionnaires at pretest, posttest, and 6‐month follow‐up including the Body Appreciation Scale 2–Children, Social Attitudes towards Appearance Questionnaire‐4 revised, Eating Disorder Examination Questionnaire Short form‐12 modified, and questions about body appearance pressure (BAP).ResultsAthletes found the program acceptable and beneficial, but some missed physically oriented activities or did not identify with the focus, particularly boys. There were acceptable levels in mental health constructs before the workshops. There were temporary changes in the percentage of boys experiencing “BAP in society” by −14.8% points (95% CI: −.6 to .0, p = .04), % in total group experiencing “BAP at school” by +11% points (95% CI: .0–.2, p = .05), thinness idealization by girls (g = .6, p = .002) and total group (g = .4, p = .006), and muscularity idealization by boys (g = .3, p = .05) and total group (g = .23, p = .04).DiscussionAthletes experienced benefits from the Young Athlete Body Project. Seeing stabilization in outcomes may mean a dampening of the otherwise expected worsening in body appreciation and ED symptoms over time.Public SignificanceAdolescent athletes are at risk for developing EDs. Due to lack of prevention programs for this group, we adapted and evaluated a well‐documented effective program, the Body Project, to fit male and female athletes <15 years. The athletes accepted the program and experienced participation benefits, with stronger acceptance among girls. Our promising findings encourage larger scaled randomized controlled trials to further evaluate a refined version this program among very young athletes.
CRISPR‐based environmental DNA detection for a rare endangered estuarine species
Authors: Nagarajan Raman P. , Sanders Leigh , Kolm Natalie , Perez Alejandro , Senegal Taylor , Mahardja Brian , Baerwald Melinda R. , Schreier Andrea D. 
Published: January 2024

AbstractEnvironmental DNA (eDNA) methods complement traditional aquatic monitoring surveys and are especially advantageous for rare and listed species to detect spatial and temporal distribution patterns. However, improvements in ease of use and portability could increase the utility of eDNA methods, leading to more widespread application, including expanding its role in management decision‐making processes. We describe the development of an eDNA detection assay for delta smelt (Hypomesus transpacificus), an endangered fish in the San Francisco Estuary, using SHERLOCK (Specific High‐Sensitivity Enzymatic Reporter Unlocking). SHERLOCK is a clustered regularly interspaced short palindromic repeats (CRISPR)‐based diagnostic tool with the ability to detect species‐specific genetic variants, making it ideal for genetic‐based taxonomic identification of any organism. Because of its high sensitivity and specificity, SHERLOCK is adaptable to eDNA detection in water samples. Here, we describe adaptation of a delta smelt SHERLOCK assay for use with estuarine water eDNA samples. This version of the assay exhibits increased sensitivity compared to the original delta smelt SHERLOCK protocol (new limit of detection approximately three copies per reaction compared to ~300 in original assay) and successfully detected delta smelt eDNA in both experimental and natural contexts. Overall, our results demonstrate that SHERLOCK eDNA detection offers managers an alternative, isothermal methodology, and highlights some challenges for detection of rare, endangered species at low abundance.
Mixed‐Valence Manganese Carboxylate Clusters, {MnIII6MnII4}, {MnIII7MnII5Na}, and {MnIII7MnII5}, Derived from the Combined Use of Di‐2‐pyridyl Ketone with Selected Aliphatic Diols
Authors: Skordi Katerina , Alexandropoulos Dimitris I. , Fournet Adeline D. , Panagiotou Nikos , Perlepes Spyros P. , Christou George , Tasiopoulos Anastasios J. 
Published: January 2024

AbstractThree new polynuclear clusters with the formulae [Mn10O4(OH)(OMe){(py)2C(O)2}2{(py)2C(OMe)(O)}4(MeCO2)6](ClO4)2 (1), Na[Mn12O2(OH)3(OMe){(py)2C(O)2}6{(py)2C(OH)(O)}2(MeCO2)2(H2O)10](ClO4)8 (2) and [Mn12O4(OH)2{(py)2C(O)2}6{(py)2C(OMe)(O)}(MeCO2)3(NO3)3(H2O)(DMF)2](NO3)2 (3) were prepared from the combination of di‐2‐pyridyl ketone, (py)2CO, with the aliphatic diols (1,3‐propanediol (pdH2) or 1,4‐butanediol (1,4‐bdH2)) in Mn carboxylate chemistry. The reported compounds do not include the aliphatic diols employed in this reaction scheme; however, their use is essential for the formation of 1–3. The crystal structures of 1–3 are based on multilayer cores which, to our knowledge, are reported for the first time in Mn cluster chemistry. Direct current (dc) magnetic susceptibility studies showed the presence of dominant antiferromagnetic exchange interactions within 1–3. Alternating current (ac) magnetic susceptibility studies revealed the presence of out‐of‐phase signals below 3.0 K for 2 and 3 indicating the slow relaxation of the magnetization vector, characteristic of single‐molecule magnets; the Ueff value of 2 was found to be 23 K and the preexponential factor τ0 ~7.6×10−9 s.
Synthesis and Photochemical Characterization of Indolizine Fluorophores Obtained by a Multicomponent Palladium Iodide−Catalyzed Oxidative Aminocarbonylation Approach
Authors: Ziccarelli Ida , Amuso Roberta , Mancuso Raffaella , Maggiore Antonio , Lamberti Giuseppe , Vitale Paola , Maiorano Vincenzo , Veltri Lucia , Gabriele Bartolo 
Published: January 2024

AbstractA catalytic carbonylative method for the direct, multicomponent synthesis of indolizine fluorophores has been developed. The process is based on the PdI2/KI‐catalyzed oxidative aminocarbonylation of 2‐(pyridin‐2‐yl)pent‐4‐yn‐1‐carbonyl compounds leading to the corresponding 2‐ynamide intermediates, followed in situ by 5‐exo‐dig cyclization (by amine‐promoted conjugate addition of the pyridine ring nitrogen) and aromatization, to give the finally isolated N,N‐disubstituted 2‐(indolizin‐3‐yl)acetamides. Reactions are carried out under relatively mild conditions (100 °C under 20 atm of a 4 : 1 mixture CO−air for 6–15 h) in MeCN as the solvent and with a low catalyst loading (0.33 mol% PdI2), in the presence of 0.5 equiv. of KI and 3 equiv. of a secondary amine. The optical properties of representative 2‐(indolizin‐3‐yl)acetamide products have also been investigated.
Improving sulfur transformation of lean electrolyte lithium–sulfur battery using nickel nanoparticles encapsulated in N‐doped carbon nanotubes
Authors: Zhang Ze , Xu Yuqing , Xiong Donggen , Yu Ji , Cai Jianxin , Huang Yizhong , Yang Zhenyu 
Published: January 2024

AbstractEfficient redox reactions of lean electrolyte lithium–sulfur (Li–S) batteries highly rely on rational catalyst design. Herein, we report an electrocatalyst based on N‐doped carbon nanotubes (CNT)‐encapsulated Ni nanoparticles (Ni@NCNT) as kinetics regulators for Li–S batteries to propel the polysulfide‐involving multiphase transformation. Moreover, such a CNT‐encapsulation strategy greatly prevents the aggregation of Ni nanoparticles and enables the extraordinary structural stability of the hybrid electrocatalyst, which guarantees its persistent catalytic activity on sulfur redox reactions. When used as a modified layer on a commercial separator, the Ni@NCNT interlayer contributes to stabilizing S cathode and Li anode by significantly retarding the shuttle effect. The corresponding batteries with a 3.5 mg cm−2 sulfur loading achieve the promising cycle stability with ∼85% capacity retention at the electrolyte/sulfur ratios of 5 and 3 μL mg−1. Even at a high loading of 12.2 mg cm−2, the battery affords an areal capacity of 7.5 mA h cm−2.