bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting the Excitation Dynamics in Lanthanide Nanoparticles
Authors: Spelthann Simon , Thiem Jonas , Melchert Oliver , Komban Rajesh , Gimmler Christoph , Demicran Ayhan , Ruehl Axel , Ristau Detlev 
Published: April 2023

AbstractWith their dipole‐forbidden 4f transitions, lanthanides doped in nanoparticles promise high excited state lifetimes and quantum yields that are required for applications such as composite lasers or nanoscale quantum memories. Quenching at the nanoparticle surface, however, severely reduces the lifetime and quantum yield and requires resource‐consuming experimental optimization that could not be replaced by simulations due to the limitations of existing approaches until now. Here, a versatile approach is presented that fully accounts for spatiotemporal dynamics and reliably predicts the lifetimes and quantum yields of lanthanide nanoparticles. LiYF4:Pr3+nanoparticles are synthesized as a model system, and the lifetimes of a concentration series (≈10 nm, 0.7−1.47 at%) are used to match the model parameters to the experimental conditions. Employing these parameters, the lifetimes and quantum yields of a size series (≈5 at%, 12−21 nm) are predicted with a maximum uncertainty of 12.6%. To demonstrate the potential of the model, a neutral shell is added around the core particles in the model which extends the lifetime by up to 44%. Furthermore, spatiotemporal analysis of single nanoparticles points toward a new type of energy trapping in lanthanide nanoparticles. Consequently, the numerical optimization brings applications such as efficient nanoparticle lasers or quantum memories within reach.
Synthesis of 1‐Phospho‐3‐benzoxepins via a Silver‐catalyzed Reaction of 2‐Alkynylacetophenones with Diazomethylphosphonates
Authors: She Rui , Qiu Jialin , Liu Yan , Peng Yungui 
Published: April 2023

AbstractA synthetic protocol for construction of 3‐benzoxepin skeleton through a silver‐catalyzed annulation/nucleophilic/ring‐expansion reaction of 2‐alkynylacetophenones with diazomethylphosphonates is described. This protocol provided a series of 1‐phosphonate‐3‐benzoxepin analogs in yields of 39%–95%. The resulting benzoxepins featuring halogen and phosphonate could be further transformed into other derivatives.magnified image
Differentiating the Allyl and Propargyl Groups on α‐Quaternary Carboxylic Acids via Chiral Bifunctional Sulfide‐Catalyzed Kinetic Resolution
Authors: Okuno Ken , Chan Bun , Shirakawa Seiji 
Published: April 2023

AbstractCatalytic kinetic resolution of racemic organic compounds is a reliable method to enantioselectively prepare important chiral molecules. Substrates for the kinetic resolution, however, generally required significantly different substituents at a chiral center. Catalytic kinetic resolution of racemic molecules possessing two similar substituents at a chiral center has remained a formidable challenge. In this context, we became interested in the catalytic kinetic resolution of racemic compounds bearing both allyl and propargyl groups, which are similar but useful substituents, at a chiral center. Herein, we report a kinetic resolution of α‐allyl‐α‐propargyl carboxylic acids bearing an all‐carbon quaternary stereocenter via chiral bifunctional sulfide‐catalyzed bromolactonization. The synthetic utility of the resultant optically active compounds obtained via kinetic resolution was also demonstrated.magnified image
Quantification of Fundamental Weak Base and Ion Permeabilities in the Acidic pH Region Utilizing Conjugated Oregon Green in Liposome‐Based Assays
Authors: Barta Thomas , Seiser Lorenz , Horner Andreas 
Published: April 2023

AbstractAmmonia and ammonium play an essential role in the metabolism of almost all living organisms. Despite their importance for human health as well as plant growth, knowledge about passive NH3/NH4+ membrane permeabilities is scarce. Large unilamellar vesicles (LUVs), a popular model membrane system, have the potential to be a game changer. However, despite a variety of environmental sensitive dyes awaiting encapsulation into membrane vesicles, a pH sensor for the acidic pH region is currently missing. This gap is filled by introducing conjugated Oregon Green (OG) which can be encapsulated into lipid‐ or polymer‐based vesicles. This allows the quantification of proton or weak base permeabilities across the vesicular membrane and functionally characterizes pH sensitive membrane proteins at an acidic pH as low as pH 4.0. Furthermore, the expanded pH range enables simultaneous estimation of ion permeabilities without the use of membrane potential uncouplers due to an increased ion sensitivity. The utility of the sensor is demonstrated by quantifying passive NH3, NH4+, and Cl− permeabilities through vastly different lipid and polymer membranes. Moreover, its performance is benchmarked against carboxyfluorescein, an established pH‐sensor in the neutral pH‐range.
Electrophoretic Delivery of Clinically Approved Anesthetic Drug for Chronic Pain Therapy
Authors: Roy Arghyamalya , Bersellini Farinotti Alex , Arbring Sjöström Theresia , Abrahamsson Tobias , Cherian Dennis , Karaday Michal , Tybrandt Klas , Nilsson David , Berggren Magnus , Poxson David J. , Svensson Camilla I. , Simon Daniel T. 
Published: April 2023

AbstractDespite a range of available pain therapies, most patients report so‐called “breakthrough pain.” Coupled with global issues like opioid abuse, there is a clear need for advanced therapies and technologies for safe and effective pain management. Here the authors demonstrate a candidate for such an advanced therapy: precise and fluid‐flow‐free electrophoretic delivery via organic electronic ion pumps (OEIPs) of the commonly used anesthetic drug bupivacaine. Bupivacaine is delivered to dorsal root ganglion (DRG) neurons in vitro. DRG neurons are a good proxy for pain studies as they are responsible for relaying ascending sensory signals from nociceptors (pain receptors) in the peripheral nervous system to the central nervous system. Capillary based OEIPs are used due to their probe‐like and free‐standing form factor, ideal for interfacing with cells. By delivering bupivacaine with the OEIP and recording dose versus response (Ca2+ imaging), it is observed that only cells close to the OEIP outlet (≤75 µm) are affected (“anaesthetized”) and at concentrations up to 10s of thousands of times lower than with bulk/bolus delivery. These results demonstrate the first effective OEIP deliveryof a clinically approved and widely used analgesic pharmaceutical, and thus are a major translational milestone for this technology.
Unconstrained Machine Learning Screening for New Li‐Ion Cathode Materials Enhanced by Class Balancing
Authors: Dinic Filip , Voznyy Oleksandr 
Published: April 2023

AbstractModeling and predicting battery cathode material voltage requires accurate structural information regarding the binding sites of lithium within a target structure. Obtaining these optimized structures requires some form of structural optimization. The ensuing complexity impedes the rapid screening of new materials for their suitability in energy storage. Previous machine learning (ML) models use structures of both lithiated and nonlithiated forms for training; essentially, reproducing what is already known, but failing to generalize to structures whose lithiated form is not available. To avoid this limitation, an ML model capable of predicting the voltage associated with the material's lithiation without explicitly requiring the lithiated structure is trained. The model's predictive power is improved by adding newly calculated data points, with the most impactful being materials with unfavorable Li binding, which are lacking in the original dataset. Using this model, new cathode candidates among an order of magnitude more materials than in previous studies are screened and the most promising ones are validated with density functional theory calculations. Considering additional stability and conductivity constraints, 572 materials with voltages greater than 3.5 V are predicted. Unexpectedly, some of them are not based on conventional transition metals, highlighting the power of an unbiased search.
Machine Learning‐Assisted Clustering of Nanoparticle‐Binding Peptides and Prediction of Their Properties
Authors: Kenry  
Published: April 2023

AbstractBioinspired and biomimetic nanostructures have attracted tremendous interest for theranostic and nanomedicine applications. Among the strategies employed to synthesize these nanostructures, surface functionalization and biomineralization of nanomaterials using peptides stand out due to the wide availability of peptides and their variations as well as the ease of modification process. Effective peptide‐based modification of nanomaterials relies on preferential and strong binding between peptides and target nanomaterials. Therefore, the discovery and design of specific peptides with high binding affinity to nanomaterials are essential. Unfortunately, conventional peptide screening methods suffer from shortcomings which render peptide discovery time‐consuming, expensive, and cumbersome. Herein, leveraging unsupervised and supervised machine learning, a framework to accelerate peptide analysis is presented. Specifically, more than 1700 nanoparticle‐binding peptides are classified into peptide clusters to identify important peptide features to realize higher‐affinity binding. In addition, the binding and biomineralization properties of peptides are predicted with high classification accuracy, precision, and recall. This work then proposes the use of unsupervised k‐means clustering and supervised k‐nearest neighbors algorithms for grouping peptides and predicting their properties, respectively. It is anticipated that the framework originated from this study will further facilitate the rational selection and design of peptides for engineering functional bioinspired and biomimetic nanostructures.
Neuregulin4 Acts on Hypothalamic ErBb4 to Excite Oxytocin Neurons and Preserve Metabolic Homeostasis
Authors: Zhang Yi , Zhu Yangyang , Wang Jinghui , Jin Li , Guo Mingwei , Chen Liwei , Zhang Lina , Li Yangyang , Wan Baocheng , Zhang Rong , Jia Weiping , Hu Cheng 
Published: April 2023

AbstractNeuregulin 4 (Nrg4) is an adipose tissue‐enriched secreted factor that modulates glucose and lipid metabolism. Nrg4 is closely associated with obesity and preserves diet‐induced metabolic disorders. However, the specific mechanisms via which Nrg4 regulates metabolic homeostasis remain incompletely understood. Here, this work finds that the Nrg4 receptor, ErbB4, is highly expressed in the hypothalamus, and the phosphorylation of hypothalamic ErbB4 is reduced in diet‐induced obesity (DIO) mice. Peripheral Nrg4 can act on ErbB4 via blood circulation and excite neurons in the paraventricular nucleus of hypothalamus (PVN). Central administration of recombinant Nrg4 protein (rNrg4) reduces obesity and related metabolic disorders by influencing energy expenditure and intake. Overexpression of ErbB4 in the PVN protects against obesity, whereas its knock down in oxytocin (Oxt) neuron accelerates obesity. Furthermore, Nrg4‐ErbB4 signaling excites Oxt release, and ablation of Oxt neuron considerably attenuates the effect of Nrg4 on energy balance. These data suggest that the hypothalamus is a key target of Nrg4, which partially explains the multifaceted roles of Nrg4 in metabolism.
Structure Transformation and Morphologic Modulation of Supramolecular Frameworks for Nanoseparation and Enzyme Loading
Authors: Wei Mingfeng , Li Bao , Wu Lixin 
Published: April 2023

AbstractSupramolecular framework (SF) encourages the emergence of porous structures with molecular flexibility while the dimension and morphology controls are less involved even though critical factors are vital for various utilizations. Targeting this purpose, two isolated components are designed and their stepped combinations via ionic interaction, metal coordination, and hydrogen bond into framework assembly with two morphologic states are realized. The zinc coordination to an ionic complex of polyoxometalate with three cationic terpyridine ligands constructs 2D hexagonal SF structure. A further growth along perpendicular direction driven by hydrogen bonding between grafted mannose groups leads to 3D SF assemblies, providing a modulation superiority in one framework for multiple utilizations. The large area of multilayered SF sheet affords a filtration membrane for strict separation of nanoparticles/proteins under gently reduced pressures while the granular SF assembly demonstrates an efficient carrier to load and fix horse radish peroxidase with maintained activity for enzymatic catalysis.
Operando Interaction and Transformation of Metastable Defects in Layered Oxides for Na‐Ion Batteries
Authors: Gorobtsov Oleg Yu. , Hirsh Hayley , Zhang Minghao , Sheyfer Dina , Nguyen Long Hoang Bao , Matson Stephanie D. , Weinstock Daniel , Bouck Ryan , Wang Ziyi , Cha Wonsuk , Maser Jörg , Harder Ross , Meng Ying Shirley , Singer Andrej 
Published: April 2023

AbstractNon‐equilibrium defects often dictate the macroscopic properties of materials. They largely define the reversibility and kinetics of processes in intercalation hosts in rechargeable batteries. Recently, imaging methods have demonstrated that transient dislocations briefly appear in intercalation hosts during ion diffusion. Despite new discoveries, the understanding of impact, formation and self‐healing mechanisms of transient defects, including and beyond dislocations, is lacking. Here, operando X‐ray Bragg Coherent Diffractive Imaging (BCDI) and diffraction peak analysis capture the stages of formation of a unique metastable domain boundary, defect self‐healing, and resolve the local impact of defects on ionic diffusion in NaxNi1−yMnyO2 intercalation hosts in a charging sodium‐ion battery. Results, applicable to a wide range of layered intercalation materials due to the shared nature of framework layers, elucidate new dynamics of transient defects and their connection to macroscopic properties, and suggest how to control the nanostructure dynamics.
Achieving Ultra‐High Voltage (≈10 kV) Triboelectric Nanogenerators
Authors: Liu Jiaqi , Zhou Linglin , Gao Yikui , Yang Peiyuan , Liu Di , Qiao Wenyan , Zhang Baofeng , Zhao Zhihao , Wang Zhong Lin , Wang Jie 
Published: April 2023

AbstractWith the intrinsic characters of high voltage and low current, triboelectric nanogenerators (TENGs) serving as green high voltage (HV) power source exhibit excellent practicability and safety compared to traditional HV power sources. To further simplify the TENG‐based HV power source system, a single electrode mode TENG (SE‐TENG) with simple wiring is first employed to generate ultra‐high voltage power in this work. By optimizing surface charge density and the thickness of packing layer between the primary electrode and reference electrode, a record value of 12.7 kV is achieved for SE‐TENGs. Furthermore, a calculation method based on a capacitance model is proposed to accurately measure the open voltage of TENG with a wide range (over 10 kV). The SE‐TENG‐based HV power source is successfully applied to power electronics and generates negative air ions for air cleaning. This work significantly simplifies TENG‐based HV power sources, and is expected to enrich the diversity of high‐voltage applications based on the reach of existing technologies.
Flexible Hierarchical Co‐Doped NiS2@CNF‐CNT Electron Deficient Interlayer with Grass‐Roots Structure for Li–S Batteries
Authors: Dai Xin , Lv Guangjun , Wu Zhen , Wang Xu , Liu Yan , Sun Junjie , Wang Qichao , Xiong Xuyang , Liu Yongning , Zhang Chaofeng , Xin Sen , Chen Yuanzhen , Zhou Tengfei 
Published: April 2023

AbstractThe key means to improve the performance of lithium–sulfur batteries (LSBs) is to reduce the internal resistance by building an electronic/ionic pathway and to accelerate the conversion kinetics of lithium polysulfides (LiPSs) through modulation of interface functions. Herein, inspired by a grass root system, a flexible hierarchical CNF‐CNT (carbon nanofiber‐carbon nanotube) membrane decorated with Co‐doped NiS2nanoparticles (Co‐NiS2@CNF‐CNT) is designed as an interlayer for LSBs, in which the in situ grown CNTs (root hairs) are wound on CNF (roots). Density functional theory (DFT) calculations show that Co doping introduces electron‐deficient regions at the doping sites in NiS2, thus improving chemical adsorption and catalytic activities toward LiPSs. The cell pairs with the Co‐NiS2@CNF‐CNT interlayer exhibit a high rate performance of 951.4 mAh g−1at 3 C, a reversible capacity of 944.1 mAh g−1after 500 cycles at 0.2 C, and a prolonged cycle life of 3000 cycles at 5 C. More importantly, an areal capacity of 7.96 mAh cm−2is achieved with a sulfur loading of 9.6 mg cm−2. This work provides a strategy for enhancing the electrochemical performance of LSBs by combining 3D hierarchical conductive skeletons and electron‐deficient functional adsorption and catalysis materials.
Prediction of soybean yield cultivated under subtropical conditions using artificial neural networks
Authors: Moreira Adônis , Bonini Neto Alfredo , Bonini Carolina dos Santos Batista , Moraes Larissa A. C. , Heinrichs Reges 
Published: April 2023

AbstractMathematical models that incorporate biotic and abiotic attributes are important tools for improving fertilizer use efficiency and reducing production costs for soybean [Glycine max (L.) Merrill] crop. In this study, artificial neural networks (ANNs) were used to estimate soybean grain yield (GY) under subtropical conditions in Brazil from plant morphological and nutritional data collected from 16 cultivars in two growing seasons. The ANNs were adequately trained, with a mean squared error of approximately 10−5 between the outputs obtained (via ANN) and desired (via experimental field), equivalent to a mean percentage error of 70.1 kg ha−1 (1.6%), confirming their efficacy as a tool to estimate GY. Smaller plant height, higher foliar calcium, magnesium and chlorophyll concentrations, and greater numbers of grains per pod and branches per plant were associated with higher GY, whereas oil content, crude protein content, and foliar manganese and potassium concentrations had no predicted effects on GY.
Peers and the choice of irrigation practices in the Arkansas Delta
Authors: Kovacs Kent , Henry Christopher , Huang Qiuqiong , Krutz Larry Jason 
Published: April 2023

AbstractThere are a range of demographic, climatic, and economic factors that influence the use of irrigation practices, along with the effect of peers and Extension agents on agricultural technologies. This research was conducted to determine how a peer's use of multiple irrigation practices influences the use of common irrigation practices in the Delta region of Arkansas. Using data from a producer survey conducted by telephone in 2015, we identify the determinants of the use and the share of an irrigated farm with five common irrigation practices in the Arkansas Delta. The role of peers for irrigation practice use depends on where a farmer is and the current farm practices in the region. A finding of the own practice peer effect is that a producer with a peer that uses flow meters is 29% more likely to use flow meters themselves. A cross practice peer effect we observe is that a producer with a peer that uses scientific scheduling is 30% less likely to use center pivot.
Tubular MXene/SS membranes for highly efficient H2/CO2 separation
Authors: Luo Mide , Lu Zong , Zhao Yali , Wang Yufei , Wei Yanying , Wang Haihui 
Published: April 2023

AbstractAccurately constructing membranes based on two‐dimensional (2D) materials on commercial porous substrates remains a significant challenge for H2 purification. In this work, a series of tubular 2D MXene membranes are prepared on commercial porous stainless steel substrates via fast electrophoretic deposition. Compared with other methods, such as filtration or drop coating, and so on. such preparation route shows the advantages of simple operation, high efficiency for membrane assembly (within 5 min) with attractive reproducibility, and ease for scale‐up. The tubular MXene membranes present excellent gas separation performance with hydrogen permeance of 1290 GPU and H2/CO2 selectivity of 55. Furthermore, the membrane displays extremely stable performance during the long‐term test for more than 1250 h, and about 93% of the membranes from one batch have exceeded the DOE target for CO2 capture. Most importantly, this work provides valuable referential significance for other 2D materials‐based membranes for future application development.
Morphology, evolution, and the whole organism imperative: Why evolutionary questions need multi‐trait evolutionary quantitative genetics
Authors: Auerbach Benjamin M. , Savell Kristen R. R. , Agosto Elizabeth R. 
Published: April 2023

AbstractSince Washburn's New Physical Anthropology, researchers have sought to understand the complexities of morphological evolution among anatomical regions in human and non‐human primates. Researchers continue, however, to preferentially use comparative and functional approaches to examine complex traits, but these methods cannot address questions about evolutionary process and often conflate function with fitness. Moreover, researchers also tend to examine anatomical elements in isolation, which implicitly assumes independent evolution among different body regions. In this paper, we argue that questions asked in primate evolution are best examined using multiple anatomical regions subjected to model‐bound methods built from an understanding of evolutionary quantitative genetics. A nascent but expanding number of studies over the last two decades use this approach, examining morphological integration, evolvability, and selection modeling. To help readers learn how to use these methods, we review fundamentals of evolutionary processes within a quantitative genetic framework, explore the importance of neutral evolutionary theory, and explain the basics of evolutionary quantitative genetics, namely the calculation of evolutionary potential for multiple traits in response to selection. Leveraging these methods, we demonstrate their use to understand non‐independence in possible evolutionary responses across the limbs, limb girdles, and basicranium of humans. Our results show that model‐bound quantitative genetic methods can reveal unexpected genetic covariances among traits that create a novel but measurable understanding of evolutionary complexity among multiple traits. We advocate for evolutionary quantitative genetic methods to be a standard whenever appropriate to keep studies of primate morphological evolution relevant for the next seventy years and beyond.
Minimizing Temperature Bias through Reliable Temperature Determination in Gas‐Solid Photothermal Catalytic Reactions
Authors: Bian Xuanang , Zhao Yunxuan , Zhou Chao , Zhang Tierui 
Published: April 2023

AbstractEnormous advances in photothermal catalysis have been made over the years, whereas the temperature assessment still remains controversial in the majority of photothermal catalytic systems. Herein, we methodically uncovered the phenomenon of temperature determination bias arising from prominent temperature differences in gas‐solid photothermal catalytic systems, which extensively existed yet has been overlooked in most relevant cases. To avoid the interference of temperature bias, we developed a universal protocol for reliable temperature evaluation of gas‐solid photothermal catalytic reactions, with emphasis on eliminating the temperature gradient and temperature fluctuation of catalyst layer via optimizing the reaction system. This work presents a functional and credible practice for temperature detection, calling attention to addressing the effects of temperature differences, and reassessing the actual temperature‐based performances in gas‐solid photothermal catalysis.