bluuebunny/crossref_metadata_2025 huggingface dataset:
In Situ X‐Ray Photoelectron Spectroscopy Study of Atomic Layer Deposited Cerium Oxide on SiO2: Substrate Influence on the Reaction Mechanism During the Early Stages of Growth
Authors: Morales Carlos , Gertig Max , Kot Małgorzata , Alvarado Carlos , Schubert Markus Andreas , Zoellner Marvin Hartwig , Wenger Christian , Henkel Karsten , Flege Jan Ingo
Published: October 2024

Thermal atomic layer deposition (ALD) of cerium oxide using commercial Ce(thd)4 precursor and O3 on SiO2 substrates is studied employing in‐situ X‐ray photoelectron spectroscopy (XPS). The system presents a complex growth behavior determined by the change in the reaction mechanism when the precursor interacts with the substrate or the cerium oxide surface. During the first growth stage, non‐ALD side reactions promoted by the substrate affect the growth per cycle, the amount of carbon residue on the surface, and the oxidation degree of cerium oxide. On the contrary, the second growth stage is characterized by a constant growth per cycle in good agreement with the literature, low carbon residues, and almost fully oxidized cerium oxide films. This distinction between two growth regimes is not unique to the CeOx/SiO2 system but can be generalized to other metal oxide substrates. Furthermore, the film growth deviates from the ideal layer‐by‐layer mode, forming micrometric inhomogeneous and defective flakes that eventually coalesce for deposit thicknesses above 10 nm. The ALD‐cerium oxide films present less order and a higher density of defects than films grown by physical vapor deposition techniques, likely affecting their reactivity in oxidizing and reducing conditions.
Dual NHC/HAT‐Promoted Esterification to Access α‐Aryl Glycines
Authors: McGill Matthew J. , Wayment Adam X. , Schull Cullen R. , Scheidt Karl A.
Published: October 2024

α‐Aryl glycines are among the most important carbonyl compounds, particularly as nonproteinogenic α‐amino acids present in many pharmacophores. As such, many strategies have been developed to access this motif, but direct carboxylation methods remain underdeveloped. Herein, we employ a dual NHC/HAT catalysis strategy to access 2‐azaallyl radicals, which subsequently couple with in situ‐generated ester azolium radical intermediates. Base‐mediated collapse of the ensuing tetrahedral intermediate liberates the NHC catalyst and benzophenone‐protected aryl glycine. This methodology was employed to esterify a variety of aryl‐substituted glycine derivatives, as well as allylic and benzylic sites. Mechanistic studies reveal that this radical process operates under both oxidative and reductive quenching cycles, while preliminary experiments employing a chiral NHC and Lewis acid additive demonstrate modest enantioselectivity.
Achieving High Ferroelectric Polarization in Ultrathin BaTiO3 Films on Si
Authors: Bagul Pratik , Han Han , Lagrain Pieter , Sergeant Stefanie , Hoflijk Ilse , Serron Jill , Richard Olivier , Conard Thierry , Van Houdt Jan , De Wolf Ingrid , McMitchell Sean R. C.
Published: October 2024

Ferroelectrics show promise for low‐power, non‐volatile memory technologies. However, material challenges in state‐of‐the‐art ferroelectric hafnates and the high coercive fields required limit their application in devices. Scaling of other candidate materials is challenging, often requiring epitaxial single‐crystalline growth using specialised substrates. Here, ferroelectricity is demonstrated in polycrystalline BaTiO3 films at 10 nm thickness on Si substrates. They exhibit the highest reported remnant polarization for polycrystalline layers, 13 µC cm−2, a value that is competitive with the epitaxial BaTiO3 state‐of‐the‐art. This is realised by introducing a novel conductive oxygen barrier, platinum silicide, which also offers strain enhancement of the ferroelectricity. Moreover, it is demonstrated that these layers can be positioned in device‐like stacks whilst maintaining ferroelectricity at 10 nm. The findings of polycrystalline perovskite ferroelectric growth in stack configurations akin to those in production flows paves the way for high performance perovskites with greater material complexity.
Self‐Induced Bi‐interfacial Modification via Fluoropyridinic Acid For High‐Performance Inverted Perovskite Solar Cells
Authors: Li Kunpeng , Zhu Yong , Chang Xiong , Zhou Mengni , Yu Xixi , Zhao Xinlong , Wang Tao , Cai Zhongming , Zhu Xing , Wang Hua , Chen Jiangzhao , Zhu Tao
Published: October 2024

The uncontrolled crystallization of perovskite generates a significant number of internal and interfacial defects, posing a major challenge to the performance of perovskite solar cells (PSCs). In this paper, a novel bi‐interfacial modification strategy utilizing 5‐fluoropyridinic acid (FPA) is proposed to modulate crystal growth and provide defect passivation. It is demonstrated that FPA is self‐deposited at both the top and bottom interfaces of perovskite films during thermal annealing. The CO and N functional groups in FPA serve as chelating agents, binding closely to uncoordinated Pb2+/Pb clusters, thereby passivating defects and reducing charge recombination at the interfaces. The strong chemical interactions between FPA and Pb further stabilize the Pb‐I framework, promoting the formation of high‐quality perovskite films, as confirmed by in situ photoluminescence measurements. Consequently, the modified inverted PSCs achieved an exceptional power conversion efficiency (PCE) of 25.37%. Moreover, the devices retained over 93.17% of initial efficiency after 3000 h of continuous illumination under one‐sun equivalent conditions in a nitrogen atmosphere. This paper presents a promising pathway for enhancing the performance and stability of inverted PSCs through a self‐induced bi‐interfacial modification approach.
The Effects of International Orientation on the Dimensions of the Environmental Performance of Agri‐Food Companies: A Chilean Perspective
Authors: Barbosa Marcelo Werneck
Published: October 2024

Like other Latin American economies, Chile has significantly increased its presence in international agriculture markets. Agricultural commodities are primarily developed within specialized exporters or multinational enterprises and exported to several different countries. In Chile, the fruit sector accounts for almost half of total exports. Internationally oriented companies explore business opportunities in foreign markets and invest adequate resources in international operations. In addition, more internationally oriented companies could be more inclined to invest in green practices due to external pressures and, consequently, achieve higher environmental performance. In this context, environmental performance is related to the extent to which available natural resources are protected during the production, delivery, and consumption of agricultural products. To the best of our knowledge, there is scattered evidence of the relationship between international orientation and the environmental performance of agri‐food companies, especially in Latin America. Grounded on the natural resources‐based view theory, this study assessed the effects of environmental collaboration on five dimensions of environmental performance (greenhouse gas emissions, energy efficiency, food loss and waste, food quality and safety, and water footprint management) in agri‐food companies with a survey with Chilean firms. Data were analyzed using the partial least square—structural equation modeling. We found that international orientation positively influences all five dimensions of environmental performance. Our study identified that the dimension most impacted by international orientation is water footprint management, and the least impacted is food quality and safety. With the aid of multi‐group analysis, we concluded that there are no significant differences in these relationships between micro/small and medium/large companies. A significant difference was observed in food loss and waste between fruit and nonfruit producers. We expect the outcomes of this study will support exporting‐related decisions and public policies in Latin America.
Spontaneous Generation of Alkoxide Radical from Alcohols on Microdroplets Surface
Authors: Fang Ye‐Guang , Li Xiaoxu , Yuan Chang , Li Xiaojiao , Yuan Xu , Zhang Dongmei , Zhang Xinxing , Zhu Chongqin , Fang Wei‐Hai
Published: October 2024

Water microdroplets have been demonstrated to exhibit extraordinary chemical behaviors, including the abilities to accelerate chemical reactions by several orders of magnitude and to trigger reactions that cannot occur in bulk water. One of the most striking examples is the spontaneous generation of hydroxyl radical from hydroxide ions. Alcohols and alkoxide ions, being structurally similar to water and hydroxide ions, might exhibit similar behavior on microdroplets. Here, we report the spontaneous generation of alkoxide radicals from alcohols (RCH2OH) in aqueous microdroplets through quantum chemical calculations, quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations, ab initio MD simulations, and mass spectrometry. Our results show that an electric field (EF) on the order of 10−1 V/Å and partial solvation at the air‐water interface jointly promote the dissociation of RCH2OH into RCH2O− and H3O+ ions. QM/MM MD simulations indicate that RCH2O− can be ionized to produce RCH2O⋅ radicals on the microdroplet surface. Furthermore, partial solvation and the EF collaboratively catalyze the isomerization of the RCH2O⋅ radical into a more stable tautomer, R⋅CHOH. This study highlights the molecular mechanisms underlying the widespread generation of radicals at the microdroplet surface and provides insights into the importance of fundamental alcohol chemistry in the atmosphere.
Rapid Surface Reconstruction of Amorphous‐Crystalline NiO for Industrial‐Scale Electrocatalytic PET Upcycling
Authors: Ding Wei , Ji Dongxiao , Wang Kangkang , Li Yinghui , Luo Qingliang , Wang Rongwu , Li Linlin , Qin Xiaohong , Peng Shengjie
Published: October 2024

The conversion of plastic waste into valuable chemicals through innovative and selective nano‐catalysts offers significant economic benefits and positive environmental impacts. However, our current understanding of catalyst design capable of achieving industrial‐grade current densities is limited. Herein, we develop a self‐supported amorphous‐crystalline NiO electrocatalyst for the electrocatalytic upcycling of polyethylene terephthalate (PET) into formate and hydrogen fuel. The catalyst achieves an industrial current density of over 1 A cm−2 at 1.5 V vs. RHE, with an 80 % Faradaic efficiency and a formate production rate of 7.16 mmol cm−2 h−1. In situ Raman spectroscopy, X‐ray absorption spectroscopy, and density functional theory calculations reveal that the rapid transformation of amorphous‐crystalline NiO into γ‐NiOOH at the amorphous‐crystalline interface provides a thermodynamic advantage for formate desorption, leading to the high activity required for industrial applications, which is challenging to achieve for fully crystalline NiO. A techno‐economic analysis indicates that recycling waste PET using this catalytic process could generate a profit of $582 per ton. This work presents a cost‐effective and highly efficient approach to promoting the sustainable utilization of waste PET.
Bimagnetic Core/Shell Nanoprobes with Tunable Exchange Coupling for High Resolution and Sensitive Magnetic Particle Imaging
Authors: Li Qilong , Li Changjian , Wang Yueqi , Li Miaomiao , Liang Zeyu , Wang Qiyue , Wang Bingzhe , Huang Canyu , Tian Jie , Li Fangyuan , Ling Daishun
Published: October 2024

Magnetic particle imaging (MPI) has demonstrated versatile applications in biomedicine, including tumor imaging, cell tracking, and image‐guided hyperthermia. Despite these advancements, the prevalent use of clinically approved tracers has posed limitations on MPI′s resolution and sensitivity. In this study, we engineered a bimagnetic core/shell nanocrystals (BMCS) tailored for MPI by optimizing the heterostructure and modulating the exchange coupling effect between the two magnetic components. The resulting BMCS exhibited remarkably heightened susceptibility and magnetization while maintaining low coercivity, thereby substantially improved both MPI resolution and sensitivity compared to conventional tracers such as VivoTrax. At an equivalent mass concentration, BMCS demonstrated a notable 5.08‐fold increase in signal intensity and achieved an unprecedentedly high resolution down to 1 mm. The excellent MPI performance contributes to high resolution MPI and the sensitive detection of orthotopic colorectal cancer in mice. The design strategy employed in BMCS, centered on the exchange coupling effect, introduces an efficacious approach for the development of high performance MPI tracers.
Synthesis of unsaturated polyester resin with phosphate based flame retardants and investigating their thermal, mechanical, and flame‐retardant properties
Authors: Karabulut Deniz , Subaşı Çağlar , Çelebi Hande , Üreyen Mustafa E. , Seyhan Abdullah T. , Özmen Fadime K. , Tezgören Yılmaz , Tezgören Emre , Pelen Özge K. , Ersöz Serap
Published: October 2024

This study reports the effects of triethyl phosphate (TEP), diphenyl cresyl phosphate (DPK), and the combined amount of aluminum hydroxide (ATH) with TEP at different weight ratios as flame retardant (FR) fillers on the physical, structural, mechanical, and flammable properties of unsaturated polyester resin (UPR). The synthesis of unsaturated polyester chains based on maleic anhydride (MA), phthalic anhydride (PA), propylene glycol (PG), ethylene glycol (EG), and diethylene glycol (DEG) was conducted in a prototype stainless steel reactor at 200 ± 5°C. Unsaturated polyester chains confirmed by nuclear magnetic resonance (1H‐NMR) were diluted with styrene monomer to create ready‐to‐apply UPR. Viscosity tests were carried out on the samples that were prepared by mixing FR fillers with UPR at different loading rates without adding accelerator and initiator. Reactivity tests of the cross‐linking initialized UPR suspensions unveiled that FR fillers prolonged the peak time and lowered the peak exotherm temperature. FR filler‐induced alterations in the chemical structure of the cured samples were then monitored using Fourier transform infrared spectroscopy (FTIR). Flexural, hardness, tensile, impact, and heat distortion temperature (HDT) tests were performed on the solid samples with and without the FR fillers. The limiting oxygen index (LOI) of the samples was also examined, and TEP was eventually found to work better than DPK for the corresponding samples involved. Therefore, the samples produced by blending UPR with TEP as well as with the combined amount of TEP and ATH at different weight ratios were characterized through vertical burning (UL‐94), cone calorimeter, and smoke density tests. As a result, it was revealed that TEP operates very well on the gas phase, despite being incompetent on the condensed phase during combustion, whereas ATH acts on both gas and condensed phases in an equal mean. Furthermore, thermal degradation behavior of the samples with and without the FR fillers and their exhaust gas products were investigated using a thermogravimetric analyzer (TGA) coupled with a Fourier transform infrared spectroscopy (TG‐FTIR). All the findings considering the presence of FR fillers were then evaluated and discussed in a brief manner to sort out the best combination of the additives for the UPR resin.
Fractional‐order fast terminal sliding mode trajectory tracking control of quadrotor UAV based on finite time disturbance observer
Authors: Zhou Zhen , Cui Ruogeng , Yu Haiyang , Ge Jiajia , Zhou Ning
Published: October 2024

In this paper, a novel trajectory tracking control problem of the quadrotor UAV is addressed, which considers the system uncertainties and unknown external disturbances meanwhile. To ensure a rapid convergence rate of the states, fast terminal sliding mode control (FTSMC) algorithm is improved combining with a fractional order method. In addition, finite‐time observer is designed to handle disturbances and enhance the robustness of the system. The closed‐loop finite‐time stability of the quadrotor UAV system is established using Lyapunov theory in accordance with the novel control law. To evaluate the effectiveness of our proposed strategy, various simulations under different scenarios are conducted respectively. These simulation results clearly demonstrate the superiority of our control scheme, which we refer to as fractional‐order fast terminal sliding mode control (FOFTSMC).
The contribution of extracellular RNA and its derived biomaterials in disease management
Authors: Wei Yu , Wang Zhangyi , Qin Zixuan , Wan Qianqian , Li Yutao , Tay Franklin R. , Wang Chenyu , Zhang Tong , Niu Lina
Published: October 2024

The RNA found in the circular system is known as extracellular RNA (exRNA). This kind of RNA has been found to play a biological role similar to that of a messenger. They can be used as indicators of disease status or the physiological health of an organism. A large number of RNA‐based biomaterials have been developed by simulating the biological function and structure of natural RNA molecules. The structural programmability of RNA‐based biomaterials provides the spur for scientists to pioneer new approaches in disease detection and prevention. Nevertheless, the link between exRNA function and the design of RNA‐based biomaterials has not been fully understood. Understanding the biological structure and function of exRNA will contribute to the clinical translation of this novel biotechnology. The present review discusses the research progress associated with exRNA and their derivatives to bridge the gap between natural exRNA and RNA‐based biomaterials.
Effect of the sintering temperature on the electrical properties of Y–Al‐doped ZnO varistors
Authors: Wang Lei , Zhang Hang , Zhang Kexin , Shen Yubo , Qu Limin , Yin Yue , Meng Pengfei , Guo Jingke
Published: October 2024

To investigate the relationship between the electrical properties of Y–Al doped ZnO varistors and sintering temperature, in this study, we measured the voltage–current characteristics and electrical performance parameters of samples sintered at –. Scanning electron microscopy observations revealed that as the sintering temperature increased, the grain size grew significantly, leading to a reduction in voltage gradient. Through characteristic testing, X‐ray diffraction and energy dispersive X‐ray spectroscopy analysis, it was found that the increase in sintering temperature promoted the formation of interface negative charge and defect reactions by , increasing and ; tends to aggregate in the grain area, further increasing ; the volatilization of gradually increases, causing a decrease in ; the first increases and then decreases with the changes in and , resulting in a U‐shaped variation characteristic of the nonlinear coefficient and leakage current density. At a sintering temperature of , the performance of ZnO varistors is optimal.
Using Soil Sensors to Assess Soil Salinity
Authors: Pandit Shailesh , Clay David E.
Published: October 2024

This article is reproduced from Chapter 6 of the new book, Salinity and Sodicity: A Growing Global Challenge to Food Security, Environmental Quality and Soil Resilience, in a slightly modified form. The book is available for purchase from Wiley.com or Amazon.com. The article covers the use of electromagnetic (EM) sensors for measuring apparent electrical conductivity (ECa). In the field, electrical conductivity (EC) can be measured by two primary approaches: physical contact and electromagnetic (EM) induction. With physical contact, a current is injected into the soil, and the detector measures the resulting voltage. An EM meter does not make direct contact but uses a coil to produce an EM field. A sensor then measures the soil‐induced changes to the original EM field. Both types of sensors measure the ECa, which is different from laboratory‐derived EC values. When using ECa sensors, it is important to remember that they are sensitive to many factors, including salinity, soil moisture, bulk density, soil texture, and temperature. The purpose of this article is to provide an overview on the use of EM sensors to provide examples on the use of these sensors in the field. Earn 1.5 CEUs in Soil & Water Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.
Connecting the dots: A narrative review of the relationship between heart failure and cognitive impairment
Authors: Massussi Mauro , Bellicini Maria Giulia , Adamo Marianna , Pilotto Andrea , Metra Marco , Padovani Alessandro , Proietti Riccardo
Published: October 2024

Large clinical data underscore that heart failure is independently associated to an increased risk of negative cognitive outcome and dementia. Emerging evidence suggests that cerebral hypoperfusion, stemming from reduced cardiac output and vascular pathology, may contribute to the largely overlapping vascular dementia and Alzheimer's disease. Despite these insights, cognitive outcomes remain largely overlooked in heart failure management. This narrative review outlines the prevalence and risk of cognitive impairment in heart failure patients, exploring potential shared pathophysiological mechanisms and examining the impact of heart failure therapy on cognitive deficits. Additionally, it discusses clinical implications and suggests future treatment approaches targeting therapeutic outcomes. Cognitive impairment is prevalent among individuals with heart failure, with reported rates varying widely depending on assessment methods. Shared pathological pathways and risk factors, including atrial fibrillation (AF), hypertension, obesity and type 2 diabetes mellitus, suggest a causal link. Mechanisms such as poor perfusion, microembolic events, ischaemic syndromes and cerebral inflammation contribute to this relationship. Moreover, heart failure itself may exacerbate cognitive dysfunction. This emerging understanding posits that vascular dementia and Alzheimer's disease may represent a pathophysiological continuum, driven by both the accumulation of misfolded proteins and cerebrovascular pathology due to cardiovascular dysfunction. Understanding these links is crucial for developing effective treatment strategies. The complex interplay between heart failure and cognitive impairment underscores the necessity for a holistic patient care approach. Both conditions share analogous disease processes, influencing self‐management and independence in patients. Prioritizing brain health in heart failure management is essential to enhance patient prognosis and general well‐being.
Time‐domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects
Authors: Tian Zhuoran , Zou Chunjiang , Wu Yun
Published: October 2024

The internal defects in rock masses can significantly impact the quality and safety of geotechnical projects. Mechanical waves, as a common nondestructive testing (NDT) method, can reflect the external and internal structures of rock or rock masses. Analyses on the reflected and transmitted waves enable nondestructive identification and assessment of potential defects within rocks. Previous studies mainly focused on the variation of single or limited wave features like main frequency, amplitude and energy between the intact and non‐intact samples. In fact, most information contained in the waveforms is neglected. Techniques of data mining can provide a powerful tool to reveal this information and therefore a more accurate determination of the internal structures. In this study, 995,412 NDT data from 14 types of granite and gypsum samples with different cross‐section shapes and different types of defects are recorded by an ultrasonic wave generation and collection system. This dataset can be used not only as the training data for defect classification in NDT but also as a good reference for conventional NDT analyses. Besides, time‐series data analysis is an opportunity and challenging issue, this dataset holds great potential for broader application in general time‐series classification analysis.
Nanofiber‐Coated CF/PEEK Composite: Boosting Osteogenesis for Enhanced Bone Grafting
Authors: Yang Dan‐Lei , Stephen Louise A. , Qayyum Junaid Ahmad , Yang Dongmin , Farquharson Colin , Radacsi Norbert
Published: October 2024

This study presents the fabrication of carbon‐fiber‐reinforced polyetheretherketone (CF/PEEK) by 3D printing, which is subsequently coated with elastic nanofibers by electrospinning. CF/PEEK is an FDA‐approved implantable material possessing excellent mechanical properties similar to those of human cortical bone. As such, it is a prime candidate for replacing conventional metallic implants. However, it is limited by its bioinertness and inferior osteogenic properties. In this study, CF/PEEK is engineered to have improved hydrophilic properties and generated micro/nano‐topographical structures on its surface. This is achieved by electrospinning directly onto the 3D‐printed CF/PEEK with fibers incorporating hydroxyapatite particles and gelatin. The results show that the micro‐/nano‐topographical CF/PEEK demonstrates a significant increase in mineralizing potential compared to non‐coated implants, where no mineralized matrix is observed. These fiber coating modifications to CF/PEEK are a promising and important step forward in the improvement of in vivo implant‐bone osteointegration.
Efficiency and Super‐Efficiency in the CRO Industry, 2012–2021: A Two‐Stage Exploration
Authors: Díaz Ricardo F. , Sanchez‐Robles Blanca
Published: October 2024

This paper explores the productivity of contract research organizations (CROs) by computing and exploring efficiency and super‐efficiency data envelopment analysis (SDEA) scores for a sample of companies over 2012–2021. Main findings suggest that CRO efficiency and super‐efficiency is high and has increased more than 25% over 2012–2021. The top positions in the rankings according to efficiency are not limited to a few companies; in contrast, many firms in the sample are able to reach a top position in at least one concept of efficiency, suggesting the high degree of rivalry and competition in this industry. A second‐stage preliminary analysis of variables associated with efficiency suggests that best performers implement a sound human capital policy, with controlled costs. Moreover, they also have a careful short‐term cash‐flow management, with brief collection periods. Big and small firms outperform the rest of the companies, suggesting the presence of increasing returns and niche advantages in some stages of the supply chain. Finally, results suggest that the COVID pandemic had an asymmetric impact on CROs, affecting positively only large CROs.
3D‐printing continuous plant fiber/polylactic acid composites with lightweight and high strength
Authors: Xing Dan , Wang Haigang , Tao Yubo , Zhang Jingfa , Li Peng , Koubaa Ahmed
Published: October 2024

Continuous plant yarn‐reinforced polylactic acid (PLA) composites were produced through in situ 3D printing, focusing on how plant fiber attributes influence the crystallization, mechanical, and rheological properties of the printed composites. The aim of this study was to assess the viability of plant fibers as substitutes for synthetic ones in engineering additive manufacturing. Plant fibers promoted the crystallization of PLA due to their shear induction and nucleation agent induction effects. The inherent triangular void defect during printing decreased with increasing plant fiber‐volume fraction. Rheological analysis revealed a transition to more elastic behavior post‐fiber addition, indicating solid‐like properties. The tensile strength of flax fiber‐yarn/PLA composite (volume fraction of 50.79%) was 342.37% higher than that of pure PLA, with a 22.2% lower density than pure PLA. Flax fiber demonstrated a superior reinforcement effect than carbon fiber in compressive strength for 3D printed honeycomb sheets with lower energy consumption and footprint. Optimizing fiber characteristics holds promise for high‐performance 3D‐printed natural fiber composites, particularly in vehicle applications.

Highlights

Plant fiber/polylactic acid (PLA) composites were in situ printed with a volume fraction of 50.79%.

Plant fibers promoted the crystallization of PLA during the printing process.

The tensile strength of flax fiber/PLA increased by 342.3% with a 22.2% lower density than PLA.

Flax fiber showed a better reinforcement than carbon fiber in a compressive test of printed honeycomb.
Association of Benzodiazepine Prescription With Short‐Term Prognosis in Elderly Patients Attended in Emergency Department: Results From the EDEN PROJECT
Authors: Ruiz‐Ramos Jesus , Alquézar‐Arbé Aitor , Juanes‐Borrego Ana , González‐del‐Castillo Juan , Jacob Javier , Burillo Guillermo , Aguiló Sira , Fernandez Cesáreo , Plaza‐Díaz Adrián , Millán‐Soria Javier , Jara‐Torres Gema , López‐Delmas Nieves , Muñoz‐Triano Esperanza , Martín‐Durán Cristina , Delgado‐Sardina Violeta , Gallardo‐Sánchez Blanca Andrea , Osorio‐Quispe Ivet Gina , Real‐López Antonio , Gordo‐Remartinez Susana , González‐Ferreira Lucía , Álvarez‐Madrigal Alberto , Martínez‐Ibarreta‐Zorita Julia , Sánchez‐Moreno María , Sanchez‐Moreno Maite , Sánchez‐Serrano Jesús Ángel , Hernando‐Fernández Raquel , Turcios‐Torres Jennifer , Ponte‐Márquez Paola , Miró Òscar
Published: October 2024

Aim

Benzodiazepine prescription is a growing phenomenon among the elderly population. However, information related to the frequency of these drugs among the elderly population attending in emergency departments (ED) and its impact over prognosis is scarce. The aim of this study is to assess the prevalence of benzodiazepine prescription and to analyze its association with short‐term prognosis in elderly patients attended in ED.

Methods

A retrospective analysis of the EDEN (Emergency Department Elderly in Need) cohort was conducted. This registry included all elderly patients attending in 52 Spanish EDs for any condition, between April 1st and 7th in 2019. Socio‐demographic data, comorbidities, and medication were recorded by consulting the patient's electronic health records. The assessed outcomes consisted on new ED visit, hospitalization, and mortality at 30 days after the first ED visit, associated with the use of benzodiazepines at baseline in comparison with no prescription of benzodiazepines. Crude and adjusted logistic regression analyses including patient's comorbidities were performed. Two sensitivity analyses were performed considering concomitant prescription of other central nervous system depressants as well as direct discharge from the ED.

Results

25 557 patients were evaluated (mean age 78 [IQR: 71–84]). 7865 (30.8%) patients were taken benzodiazepines at admission. After adjustment for comorbidities and other central nervous system drugs, benzodiazepine prescription was associated with ED revisit [OR: 1.10 (95%CI: 1.03–1.18)]. Similar results were found in the sensitivity analysis, eliminating patients with central nervous depressors [OR: 1.11 (1.03–1.25)] and patients discharged to home [OR: 1.13 (1.04–1.23)]. No association was found between the use of these drugs and new hospitalizations [OR: 0.90 (0.77–1.05)] or mortality 30 days after discharge [OR: 1.01 (0.88–1.18)]. The results held for all three outcomes in the sensitivity analyses.

Conclusion

The use of benzodiazepines is a frequent phenomenon among the elderly population attended in the ED, being associated with an increased risk of new visits to the emergency room, but not with an increased risk of 30‐day hospitalization or mortality.
Rapid estimation of DON content in wheat flour using close‐range hyperspectral imaging and machine learning
Authors: Saini Dinesh Kumar , Rana Anshul , Halder Jyotirmoy , Billah Mohammad Maruf , Gill Harsimardeep S. , Zhang Jinfeng , Thapa Subash , Ali Shaukat , Turnipseed Brent , Glover Karl , Maimaitijiang Maitiniyazi , Sehgal Sunish K.
Published: October 2024

Fusarium head blight (FHB) is one of the most destructive fungal diseases affecting wheat (Triticum aestivum). Moreover, it is notorious for producing mycotoxin deoxynivalenol (DON), posing a significant global threat to food and feed safety. Traditional methods like enzyme‐linked immunosorbent assay (ELISA) and gas chromatography‐mass spectrometry (GC‐MS) are commonly used to assess DON levels in grain or flour samples and are time‐consuming and expensive. Therefore, a faster, cost‐effective method to estimate DON content is needed, especially for enhancing breeding efforts to reduce DON levels in wheat. In this study, we envisioned integrating close‐range hyperspectral imaging with deep learning (DL) models to estimate DON content in wheat meal/flour. We selected 243 advanced breeding lines from the South Dakota State University (SDSU) wheat breeding program that were evaluated in FHB nurseries (2019–2020 and 2020–2021). The wheat meal samples were analyzed for DON content using GC‐MS and subsequently subjected to close‐range hyperspectral imaging. We evaluated three conventional machine learning (ML), two DL models and data augmentation. Among the conventional ML models, partial least squares regression (PLSR) (with R2P = 0.88 and 0.90 for original and augmented datasets, respectively) demonstrated the highest prediction accuracies for DON content. However, the one‐dimensional convolutional neural network (1D‐CNN) achieved the highest prediction accuracies (R2P = 0.90 and = 0.96 for original and augmented datasets, respectively) compared to all tested models and demonstrated the lowest error. In conclusion, integration of advanced hyperspectral imaging with ML approaches exhibits significant potential for high‐throughput and cost‐effective estimation of DON content in wheat, thereby accelerating wheat breeding efforts for reduced DON levels.
Applying Machine Learning to Elucidate Ultrafast Demagnetization Dynamics in Ni and Ni80Fe20
Authors: Ahmadian Baghbaderani Hasan , Choi Byoung‐Chul
Published: October 2024

Understanding the correlation between fast and ultrafast demagnetization (UFD) processes is crucial for elucidating the microscopic mechanisms underlying UFD, which is pivotal for various applications in spintronics. Initial theoretical models attempt to establish this correlation but face challenges due to the complex interplay of physical phenomena. To address this, a variety of machine learning (ML) methods are employed, including supervised learning regression algorithms and symbolic regression (SR), to analyze limited experimental data and derive meaningful mathematical expressions between demagnetization time (τM) and the Gilbert damping factor (α). The results reveal that polynomial regression and K‐nearest neighbors algorithms perform best in predicting τM. Additionally, variable‐selection sure‐independence‐screening‐and‐sparsifying‐operator (VS‐SISSO) as a SR method suggests a direct correlation between τM and α for Ni and Ni80Fe20, indicating spin‐flip scattering predominantly influences the UFD mechanism. The developed models demonstrate promising predictive capabilities, validated against independent experimental data. Comparative analysis between different materials underscores the significant impact of material properties on UFD behavior. This study underscores the potential of ML in unraveling complex physical phenomena and offers valuable insights for future research in ultrafast magnetism.
Amazonian manatee critical habitat revealed by artificial intelligence‐based passive acoustic techniques
Authors: Erbs Florence , van der Schaar Mike , Marmontel Miriam , Gaona Marina , Ramalho Emiliano , André Michel
Published: October 2024

For many species at risk, monitoring challenges related to low visual detectability and elusive behavior limit the use of traditional visual surveys to collect critical information, hindering the development of sound conservation strategies. Passive acoustics can cost‐effectively acquire terrestrial and underwater long‐term data. However, to extract valuable information from large datasets, automatic methods need to be developed, tested and applied. Combining passive acoustics with deep learning models, we developed a method to monitor the secretive Amazonian manatee over two consecutive flooded seasons in the Brazilian Amazon floodplains. Subsequently, we investigated the vocal behavior parameters based on vocalization frequencies and temporal characteristics in the context of habitat use. A Convolutional Neural Network model successfully detected Amazonian manatee vocalizations with a 0.98 average precision on training data. Similar classification performance in terms of precision (range: 0.83–1.00) and recall (range: 0.97–1.00) was achieved for each year. Using this model, we evaluated manatee acoustic presence over a total of 226 days comprising recording periods in 2021 and 2022. Manatee vocalizations were consistently detected during both years, reaching 94% daily temporal occurrence in 2021, and up to 11 h a day with detections during peak presence. Manatee calls were characterized by a high emphasized frequency and high repetition rate, being mostly produced in rapid sequences. This vocal behavior strongly indicates an exchange between females and their calves. Combining passive acoustic monitoring with deep learning models, and extending temporal monitoring and increasing species detectability, we demonstrated that the approach can be used to identify manatee core habitats according to seasonality. The combined method represents a reliable, cost‐effective, scalable ecological monitoring technique that can be integrated into long‐term, standardized survey protocols of aquatic species. It can considerably benefit the monitoring of inaccessible regions, such as the Amazonian freshwater systems, which are facing immediate threats from increased hydropower construction.
Organometallic Compound Stabilizes All‐Inorganic Tin‐Based Perovskite Nanocrystals Against Antisolvent Post‐Treatment
Authors: Cheng Huiyuan , Hao Mengmeng , Ding Shanshan , He Dongxu , Zhang Bowei , Wang Kai , Yang Qishuo , Chen Peng , Wang Zitong , Xu Hongzhe , Zhang Chengxi , Wang Lianzhou , Steele Julian A.
Published: October 2024

The isolation and purification of all‐inorganic Sn‐based perovskite nanocrystals (PNCs) remain troublesome, as common antisolvents accelerate the collapse of the optically active perovskite structure. Here, we mitigate such instabilities and endow strong resistance to antisolvent by incorporating the organometallic compound zinc diethyldithiocarbamate, Zn(DDTC)2, during the solution‐based synthesis of all‐inorganic CsSnI3 nanocrystals. Thiourea is shown to form through the thermal‐driven conversion of Zn(DDTC)2 during synthesis, which binds to un‐passivated Sn sites on the crystal surface and shields it from irreversible oxidation reactions. The CsSnI3 PNCs capped with thiourea show great stability after two purification cycles using methyl acetate, with negligible change in morphology, phase, and optical properties. Moreover, the modified PNCs are resistant to other commonly used antisolvents, like ethyl acetate, 1‐pentanol, and isopropanol, offering a platform to explore all‐inorganic Sn‐based nanocrystalline thin films and optoelectronics.
Fully Non‐Fused Ring Electron Acceptors Enable Effective Additive‐Free Organic Solar Cells with Enhanced Exciton Diffusion Length
Authors: Li Kun , Liu Xuefeng , Zhong Jianbin , Chen Yu , Zhang Wei , Wang Pingyang , Wu Yishi , Liao Qing , An Cunbin , Fu Hongbing
Published: October 2024

Low‐cost photovoltaic materials and additive‐free, non‐halogenated solvent processing of photoactive layers are crucial for the large‐scale commercial application of organic solar cells (OSCs). However, high‐efficiency OSCs that possess all these advantages remain scarce due to the lack of insight into the structure‐property relationship. In this work, three fully non‐fused ring electron acceptors (NFREAs), DTB21, DTB22, and DTB23, are reported by utilizing a simplified 1,4‐di(thiophen‐2‐yl)benzene (DTB) core with varied alkoxy chain lengths on the thiophene bridge. The material‐only costs of these acceptors are only 11–13$ per gram. Importantly, DTB22 has an exciton diffusion length (LD) of up to 25.5 nm. The DTB21 and DTB23 exhibit decreased LDs of 20.1 and 23.1 nm, respectively. After blending with the polymer donor PBQx‐TF, the PBQx‐TF:DTB22 film exhibits the fastest hole transfer and the longest carrier recombination lifetime among these OSCs. Consequently, the optimal PBQx‐TF:DTB22‐based OSC achieves an excellent PCE of 17.00%, which is among the highest values for fully NFREAs. In contrast, the PBQx‐TF:DTB21‐ and PBQx‐TF:DTB23‐based OSCs show relatively lower PCEs of 15.13% and 15.63%, respectively. Notably, all these OSCs are fabricated using toluene as the solvent, without any additives. Additionally, the DTB22‐based OSC also demonstrates good stability, retaining 95% of its initial efficiency after 500 h without encapsulation in a glovebox.
Self‐Templated 3D Sulfide‐Based Solid Composite Electrolyte for Solid‐State Sodium Metal Batteries
Authors: Guo Xiaolin , Li Yang , Halacoglu Selim , Graff Kincaid , Zhang Chunyan , Fu Kelvin , Xiong Hui (Claire) , Wang Hui
Published: October 2024

Rechargeable solid‐state sodium metal batteries (SSMBs) experience growing attention owing to the increased energy density (vs Na‐ion batteries) and cost‐effective materials. Inorganic sulfide‐based Na‐ion conductors also possess significant potential as promising solid electrolytes (SEs) in SSMBs. Nevertheless, due to the highly reactive Na metal, poor interface compatibility is the biggest obstacle for inorganic sulfide solid electrolytes such as Na3SbS4 to achieve high performance in SSMBs. To address such electrochemical instability at the interface, new design of sulfide SE nanostructures and interface engineering are highly essential. In this work, a facile and straightforward approach is reported to prepare 3D sulfide‐based solid composite electrolytes (SCEs), which utilize porous Na3SbS4 (NSS) as a self‐templated framework and fill with a phase transition polymer. The 3D structured SCEs display obviously improved interface stability toward Na metal than pristine sulfide. The assembled SSMBs (with TiS2 or FeS2 as cathodes) deliver outstanding electrochemical cycling performance. Moreover, the cycling of high‐voltage oxide cathode Na0.67Ni0.33Mn0.67O2 (NNMO) is also demonstrated in SSMBs using 3D sulfide‐based SCEs. This study presents a novel design on the self‐templated nanostructure of SCEs, paving the way for the advancement of high‐energy sodium metal batteries.
Compositional Complexity of Metal–Organic Frameworks with Programmable Spatial Arrangement of Multi‐Metallic Components
Authors: Lim Hyeongi , Lee Gihyun , Lee Jeehyoun , Yoo Ahram , Oh Moonhyun
Published: October 2024

The components and structures of metal–organic frameworks (MOFs) are critical two factors that influence their properties and prospective applications. Moreover, the construction of complex MOFs integrating multiple components holds promise to achieve MOFs with unique properties. However, constructing complex MOFs with an intended 3D spatial arrangement of the multiple components remains underdeveloped. Herein, a systematic approach is reported for designing and constructing complex MOFs featuring multi‐metallic components with programmed 3D spatial distributions. Syringe pumps with programmed injection rates are employed to feed the intended amounts of multi‐metallic components into a reactor at specific time points. By controlling the quantities of components present in the reactor, their incorporation within MOFs is carefully managed, eventually achieving the intended spatial arrangement of multi‐metallic components within MOFs. This approach is successfully applied to constructing numerous bimetallic and trimetallic zeolitic imidazolate frameworks with programmed spatial distributions of Zn2+, Co2+, Cu2+, and/or Ni2+, with varied combinations, quantities, sequences, and numbers. This method is also suitable for fabricating the bimetallic MIL‐88B, proving its applicability to many MOFs. Using this method, precise control over multiple components with intended and complex spatial distributions can be attained, enabling the construction of special MOFs with tailored properties and functions.
Laser‐Regulated Iridium‐Diffused Nitrogen–Carbon Sites for Enhanced Hydrazine‐Assisted Alkaline Seawater Splitting and Zinc–Hydrazine Batteries
Authors: Moon Cheol Joo , Maheskumar Velusamy , Min Ahreum , Kumar Anuj , Lee Seongbo , Senthil Raja Arumugam , Ubaidullah Mohd , Choi Myong Yong
Published: October 2024

The current study presents a quick and simple method for synthesizing Ir nanoclusters decorated on an N‐doped carbon (NC) matrix via pulsed laser ablation in liquid, followed by pyrolysis. The resulting Ir–NC material acts as a dual‐functional electrocatalyst, efficiently facilitating hydrogen generation through the hydrazine oxidation reaction (HzOR) and the hydrogen evolution reaction (HER) in alkaline seawater. The optimized Ir–NC‐2 catalyst exhibits a low operating potential of 23 mV versus the reversible hydrogen electrode for HzOR and a remarkably low overpotential of 24 mV for HER, achieving a current density of 10 mA cm−2 in alkaline seawater, surpassing the performance of the Pt/C catalyst. Notably, the Ir–NC‐2 catalyst also demonstrates superior dual‐functionality in overall hydrazine‐assisted seawater splitting, requiring only 0.1 V at 10 mA cm−2 while maintaining stability. Moreover, density functional theory calculations reveal that the strong electronic interaction between the Ir nanoclusters and the NC matrix enhances mass transfer and electron conductivity, significantly boosting HER activity and accelerating the kinetics of hydrazine dehydrogenation. Consequently, the Ir–NC‐2 catalyst performs efficiently in a Zn–hydrazine battery, achieving high energy efficiency of 95.5% and demonstrating excellent stability for 120 h (360 cycles), indicating its potential for practical applications.
Prediction of Sulfur Content during Steel Refining Process Based on Machine Learning Methods
Authors: Gao Jiang , Cui Lingxiao , Wang Weijian , Zhang Lifeng , Yang Wen
Published: October 2024

The neural network technology combining genetic algorithm is utilized to predict the sulfur content and optimize the desulfurization operation at the end of the refining process. Three types of prediction models are developed to achieve the optimal model. The prediction accuracy can be improved by the application of the deep neural network while the root means square error (RMSE) value of the optimal prediction model and the mean absolute error (MAE) value are less than 5 ppm. Moreover, the proportion of heats with prediction errors less than 5 ppm reaches 82%. Effects of dissolved oxygen contents, initial sulfur contents, carbon contents, and the amount of desulfurizer addition on the desulfurization process are considered. The optimal amount of slag addition with various initial sulfur contents is calculated. With the increase of initial sulfur content in the molten steel, the optimal amount of slag‐modified agent addition increases from about 500–750 kg.