bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single Atom Catalyst for Nitrate‐to‐Ammonia Electrochemistry
Authors: Subhadarshini Suvani , Pumera Martin 
Published: October 2024

AbstractVarious life forms suffer from the negative effects of nitrate when it accumulates in water bodies, which is a major concern in the present day. The removal of nitrate from water bodies is a critical challenge, and the most effective method to achieve that is to change it into ammonia. Ammonia is a clean energy source and a vital input for the fertilizer industry. The Haber–Bosch process, which dominates the industrial production of ammonia, requires a lot of energy. A more sustainable way to produce ammonia is to use nitrate‐contaminated water and reduce it to ammonia through electrocatalysis. This review is constituted of amalgamated articles featuring unique conditions that affect the productivity and activity of the transition metal single atom catalyst (TNMSAC) for the electrocatalytic nitrate reduction to ammonia (NRA) reaction. It explores factors such as nitrate ion adsorption, the characteristics of the central electroactive transition metal, the type of coordinating atoms, the impact of potential on stability, and the interplay among single atoms on the selectivity and yield of ammonia gas. In addition, this review also covers advanced concepts such as dual‐atom catalysts, dual single atom catalysts, and single atom alloys. The review will provide valuable guidance for enhanced comprehension and strategic designing of TNMSAC for the electrocatalytic conversion of NRA, which will contribute to achieving a green ammonia economy.
Dual‐Responsive MnO2‐Loaded Carbonaceous Nanobottle Motors Fabricated by Interfacial Superassembly for On‐The‐Fly MicroRNA Sensing
Authors: Ma Enhui , Wang Ke , Gou Yineng , Luo Wenqing , Wang Hong 
Published: October 2024

AbstractDiverse nanomotors with advanced motion manipulation have been proposed to revolutionize the way problems in many fields are solved. However, rational and controllable synthetic methods of multifunctional nanomotor are still limited. Herein, dual‐responsive MnO2‐loaded carbonaceous nanobottle motors (MnO2 NBMs) are developed through an interfacial superassembly strategy. Asymmetric carbonaceous nanobottles are first synthesized, and the reductive carbonaceous shell induces an oxidation‐reduction reaction with KMnO4 for in‐situ growth of MnO2 nanosheets, which enables the nanomotor to perform either self‐diffusiophoretic or self‐thermophoretic motion in response to H2O2 and near‐infrared light, respectively. Inspired by bioaffinity sensing, the nanomotors are sequentially assembled with functional nanoparticles and hairpin DNA to construct swimming functional MnO2 NBMs (MnO2 FNBMs) probes. The probes can move around complex samples to improve target miRNA transport and accelerate receptor‐target interaction. Coupling with the photocurrent‐signal amplification, the self‐assembly of photoelectrochemical (PEC) biosensors has been achieved for sensitive microRNA detection. Trace amounts of miRNA‐155 can be quickly detected with a wide detection range (100 fM to 100 nM). Moreover, the direct detection of microRNA in tumor cell lysates by the biosensor is demonstrated. Given the merits of automation and miniaturization, the proposed strategy provides a promising method for fast and effective self‐assembly of biosensors.
The Synthesis of Needle‐Like Monocrystalline Diamonds with a High Aspect Ratio up to 14
Authors: Hou Shuai , Hao Jinglin , Deng Lifen , Cui Xiwei , Mao Rongqi , Jiang Nan 
Published: October 2024

AbstractDiamond exhibits nontrivial hardness and abrasion, ultra‐high thermal conductivity, and light transmission over a wide wavelength range. All these properties are anisotropic. There is considerable literature on the synthesis of large‐sized monocrystalline diamonds but the synthesis of highly oriented monocrystalline diamonds is limited. Here, [100] oriented monocrystalline needle‐like diamonds are successfully synthesized with an aspect ratio of up to 14 by controlling the temperature gradient and carbon concentration gradient using FeCo alloy as the catalyst at ≈5.8 GPa and 1473 K. The distinctive morphology and microstructure of needle‐like diamonds are characterized using Scanning Electron Microscopy, X‐ray diffraction, and Focused Ion Beam‐Transmission Electron Microscopy. A four‐stage growth model is established to elucidate the growth mechanism along the [100], which sheds light on the synthesis of diamonds with predetermines crystal orientations. Increasing the aspect ratio of needle‐like diamonds further may enable the development of diamond fibers and assist in the fabrication of laser diamonds with specific orientation requirements.
Multi‐Phase Rotating Disk Triboelectric Nanogenerator with DC Output for Speed Monitoring
Authors: Luo Hongchun , Ni Xingyi , Zhang Chun , Cui Yingxuan , Yang Tao , Shao Juxiang , Jing Xingjian 
Published: October 2024

AbstractTriboelectric nanogenerators (TENGs) are highly efficient devices for harvesting mechanical energy. Nevertheless, conventional TENGs often produce AC output, which, coupled with their high crest factor and pulsed output characteristics, poses limitations on their widespread adoption in real scenarios. In this paper, a multi‐phase rotating disk triboelectric nanogenerator (MPRD‐TENG) characterized by a low crest factor and DC output is prepared through the method of phase superposition. The findings reveal that by enhancing these parameters, namely, increasing the number of rotating disk TENGs, augmenting the number of grids, and elevating the rotational speed, the crest factor of the MPRD‐TENG can be effectively reduced. Furthermore, this innovative MPRD‐TENG demonstrates its versatility by successfully powering a fire alarm system, thereby offering a promising solution for early warning and monitoring of offshore oil exploration fires. Ultimately, the implementation of machine learning algorithms to train the DC output data collected by the MPRD‐TENG significantly enhances the capability to predict and classify signals corresponding to varying speeds with greater precision. Consequently, the integration of machine learning methods not only facilitates a more effective warning system but also bolsters monitoring capabilities for unforeseen situations encountered in real‐world engineering projects.
Tailoring Ni‐Fe‐B Electronic Effects in Layered Double Hydroxides for Enhanced Oxygen Evolution Activity
Authors: Bai Yuke , Liu Zhaojun , Wang Xiaoxiao , Zhang Zhixue , Liu Kai , Gao Chuanbo 
Published: October 2024

AbstractNiFe layered double hydroxides (LDHs) are state‐of‐the‐art catalysts for the oxygen evolution reaction (OER) in alkaline media, yet they still face significant overpotentials. Here, quantitative boron (B) doping is introduced in NiFe LDHs (ranging from 0% to 20.3%) to effectively tailor the Ni‐Fe‐B electronic interactions for enhanced OER performance. The co‐hydrolysis synthesis approach synchronizes the hydrolysis rates of Ni and Fe precursors with the formation rate of B─O─M (M: Ni, Fe) bonds, ensuring precise B doping into the NiFe LDHs. It is demonstrated that B, as an electron‐deficient element, acts as an “electron sink” at doping levels from 0% to 13.5%, facilitating the transition of Ni2+ to the active Ni3+δ, thereby accelerating OER kinetics. However, excessive B doping (13.5–20.3%) effectively generates oxygen vacancies in the LDHs, which increases electron density at Ni2+ sites and hinders their transition to Ni3+δ, thereby reducing OER activity. Optimal OER performance is achieved at a B doping level of 13.5%, with an overpotential of only 208 mV to reach a current density of 500 mA cm−2, placing it among the most effective OER catalysts to date. This Ni‐Fe‐B electronic engineering opens new avenues for developing highly efficient anode catalysts for water‐splitting hydrogen production.
Biomimetic Channels Design in Metal‐Organic Framework Enabling Highly Lithium‐Ion Conduction for Lithium‐Metal Batteries
Authors: Wang Xin , Jin Sheng , Shi Lu , Zhang Nan , Guo Jia , Zhang Dianqu , Liu Zhiliang 
Published: October 2024

AbstractSolid‐state electrolytes (SSEs) based on metal‐organic frameworks (MOFs) are an ideal material for constructing high‐performance lithium metal batteries (LMBs). However, the low ion conductivity and poor interface contact (especially at low temperatures) still seriously hinder its further application. Herein, inspired by the Na+/K+ conduction in biology systems, a series (NH2, OH, NH‐(CH2)3‐SO3H)‐modified MIL‐53‐X as SSEs is reported. These functional groups are similar to anions suspended in biological ion channels, partially repelling anions while allowing cations to be effectively transported through pore channels. Subsequently, MIL‐53‐X with hierarchical pore structure (H‐MIL‐53‐X) is obtained by introducing lauric acid as a regulator, and then the effects of structural design and morphology control on its performance are explored. The conductivity of H‐MIL‐53‐NH‐SO3Li with multi‐level pore structure and modified by sulfonic acid groups reached 2.2 × 10−3 S cm−1 at 25 °C, lithium‐ion transference number of 0.78. Besides, the H‐MIL‐53‐NH‐SO3Li still has an excellent conductivity of 10−4 S cm−1 at −40 °C. Additionally, LiFePO4/Li batteries equipped with H‐MIL‐53‐NH‐SO3Li SSEs could operate stably for over 200 cycles at 0.1 C. The strategy of combining structural and morphological design of MOFs with biomimetic ion channels opens new avenues for the design of high‐performance SSEs.
Computational design of energy‐related materials: From first‐principles calculations to machine learning
Authors: Xue Haibo , Cheng Guanjian , Yin Wan‐Jian 
Published: October 2024

AbstractEnergy‐related materials are crucial for advancing energy technologies, improving efficiency, reducing environmental impacts, and supporting sustainable development. Designing and discovering these materials through computational techniques necessitates a comprehensive understanding of the material space, which is defined by the constituent atoms, composition, and structure. Depending on the search space involved in the investigation, the computational materials design can be categorized into four primary approaches: atomic substitution in fixed prototype structures, crystal structure prediction (CSP), variable‐composition CSP, and inverse design across the entire materials space. This review provides an overview of these paradigms, detailing the concepts, strategies, and applications pertinent to energy‐related materials. The progression from first‐principles calculations to machine learning techniques is emphasized, with the aim of enhancing understanding and elucidating new advancements in computationally design of energy‐related materials.This article is categorized under:
Structure and Mechanism > Computational Materials Science
Data Science > Artificial Intelligence/Machine Learning
Electronic Structure Theory > Density Functional Theory
Single‐stapled colorectal anastomotic techniques: Do not cross the line
Authors: Cavallaro Paul , Holubar Stefan D. 
Published: October 2024

AbstractThe double‐stapled technique is the most common method of colorectal anastomosis. Despite its widespread use, emerging data suggests that this technique may be a risk factor for anastomotic complications, as it is believed that crossing staple lines and resultant dog‐ears are potentially weak points that are prone to ischemia and anastomotic leak. Herein, we describe technical variations of single‐stapled colorectal anastomoses which surgeons can readily adopt and integrate into their armamentarium of anastomotic techniques.
Clinical significance of the CALLY index in patients with gastric cancer undergoing gastrectomy
Authors: Sakurai Katsunobu , Kubo Naoshi , Hasegawa Tsuyoshi , Nishimura Junya , Iseki Yasuhito , Nishii Takafumi , Inoue Toru , Yashiro Masakazu , Nishiguchi Yukio , Maeda Kiyoshi 
Published: October 2024

AbstractBackgroundThe aim of this study was to elucidate the clinical impact of the CALLY index in patients with gastric cancer (GC) undergoing gastrectomy.MethodsBetween January 2014 and December 2020, 617 patients who underwent gastrectomy for GC at the Osaka City General Hospital were enrolled in this study. The CALLY index was calculated using the following formula: [albumin (g/dL) × lymphocytes (/μl)]/[CRP (mg/dL) × 104]. We compared the predictive value of four biomarkers [CALLY index, modified Glasgow prognostic score (mGPS), neutrophil‐lymphocyte ratio (NLR), and platelet‐lymphocyte ratio (PLR)] for short‐ and long‐term outcomes and focused on the CALLY index to elucidate its clinical value.ResultsReceiver operating characteristic analysis showed that the area under the curve for the CALLY index was the highest among the four biomarkers. The 5‐year overall survival (OS) and cancer‐specific survival (CSS) rates in the low and the high CALLY groups were statistically significant. Multivariate analysis identified the CALLY index as an independent factor for OS and CSS but not NLR or PLR. The mGPS was an independent factor for OS but not for CSS in multivariate analysis. Regarding complications, only the CALLY index was an independent predictor of major complications (≧ Clavien–Dindo grade 3) in multivariate analysis but not others.ConclusionsThe CALLY index may have a clinical value in predicting OS, CSS, and major complications in GC patients undergoing gastrectomy.
Numerical Simulations
Authors: Méot François 
Published: October 2024

AbstractSeveral of the numerical simulation exercises proposed in the following chapters require step-by-step raytracing through the optical elements concerned, for diverse reasons, depending on the problem. The raytracing code Zgoubi is used and provides the necessary tooling for this numerical solution of particle and spin motion in electric and/or magnetic fields, and to account for random events such as in-flight decay or photon emission. Generalities regarding the interest of the stepwise integration method, as well as the code and its input and output data files, are introduced here.
Beam Lines
Authors: Méot François 
Published: October 2024

AbstractThis chapter introduces beam transport and manipulations in beam lines. It provides the theoretical material resorted to in the simulation exercises, leaning on charged particle optics and beam manipulation concepts introduced in earlier Chapters. The simulation of beam lines and specific functionalities they ensure require new optical elements, such as WIENFILTER, EBMULT, high order multipoles, etc. Particle monitoring resorts to keywords introduced in the previous Chapters, including FAISCEAU, FAISTORE, possibly PICKUPS, and some others. Spin motion computation and monitoring resort to SPNTRK, SPNPRT, FAISTORE. Optics matching and optimization use FIT[2]. INCLUDE is sometimes resorted to, mostly in order to modularize and/or simplify the input data files. SYSTEM is used to, mostly, call gnuplot scripts so as to end simulations with some specific graphs, or animations. These scripts read their data from output files filled up during the execution of the code, such as zgoubi.fai (resulting from the use of FAISTORE), zgoubi.plt (resulting from IL $$=$$
=
2 flag), or other zgoubi.*.out files resulting from a PRINT command.
The Local Picard Group of a Ring Extension
Authors: Spirito Dario 
Published: October 2024

AbstractGiven an integral domain D and a D-algebra R, we introduce the local Picard group $$\textrm{LPic}(R,D)$$

LPic
(
R
,
D
)

as the quotient between the Picard group $$\textrm{Pic}(R)$$

Pic
(
R
)

and the canonical image of $$\textrm{Pic}(D)$$

Pic
(
D
)

in $$\textrm{Pic}(R)$$

Pic
(
R
)

, and its subgroup $$\textrm{LPic}_u(R,D)$$

LPic
u

(
R
,
D
)

generated by the the integral ideals of R that are unitary with respect to D. We show that, when $$D\subseteq R$$

D
⊆
R

is a ring extension that satisfies certain properties (for example, when R is the ring of polynomial D[X] or the ring of integer-valued polynomials $$\textrm{Int}(D)$$

Int
(
D
)

), it is possible to decompose $$\textrm{LPic}(R,D)$$

LPic
(
R
,
D
)

as the direct sum $$\bigoplus \textrm{LPic}(RT,T)$$

⨁
LPic
(
R
T
,
T
)

, where T ranges in a Jaffard family of D. We also study under what hypothesis this isomorphism holds for pre-Jaffard families of D.
A classification of generalized root systems
Authors: Cuntz Michael , Mühlherr Bernhard 
Published: October 2024

AbstractDimitrov and Fioresi introduced an object that they call a generalized root system. This is a finite set of vectors in a Euclidean space satisfying certain compatibilities between angles and sums and differences of elements. They conjecture that every generalized root system is equivalent to one associated to a restriction of a Weyl arrangement. In this note, we prove the conjecture and provide a complete classification of generalized root systems up to equivalence.
Reduced-dimensional modelling for nonlinear convection-dominated flow in cylindric domains
Authors: Mel’nyk Taras , Rohde Christian 
Published: October 2024

Abstract
The aim of the paper is to construct and justify asymptotic approximations for solutions to quasilinear convection–diffusion problems with a predominance of nonlinear convective flow in a thin cylinder, where an inhomogeneous nonlinear Robin-type boundary condition involving convective and diffusive fluxes is imposed on the lateral surface. The limit problem for vanishing diffusion and the cylinder shrinking to an interval is a nonlinear first-order conservation law. For a time span that allows for a classical solution of this limit problem corresponding uniform pointwise and energy estimates are proven. They provide precise model error estimates with respect to the small parameter that controls the double viscosity-geometric limit. In addition, other problems with more higher Péclet numbers are also considered.
Passive dispersal potential of medaka eggs by attaching to waterbirds
Authors: Yao Akifumi , Mashiko Miyuki , Toquenaga Yukihiko 
Published: October 2024

AbstractColonization of new habitats is a key event in forming current distributions in organisms. It has been speculated that freshwater fish eggs can be dispersed passively by attaching to or egestion from waterbirds that arrive in wetland habitats. Recent research showed that some freshwater fish eggs could be excreted alive from birds and then successfully hatch, but scientific evidence of bird-mediated fish dispersal is still limited to endozoochory (internal transport through a bird’s digestive tract). Here, we experimentally suggest the dispersal potential in another way or epizoochory (external dispersal by attaching to waterbirds), using medaka Oryzias latipes, which spawns on aquatic plants. Our field experiment showed that waterbirds could carry artificial aquatic plants among waterbodies. Medaka eggs attached to aquatic plants could survive in the air for up to 18 h with a median lethal period of 16.3 h. Those two findings raise the possibility of the epizoochory of medaka in nature.
Galactica’s dis-assemblage: Meta’s beta and the omega of post-human science
Authors: Chartier-Edwards Nicolas , Grenier Etienne , Goujon Valentin 
Published: October 2024

AbstractReleased mid-November 2022, Galactica is a set of six large language models (LLMs) of different sizes (from 125 M to 120B parameters) designed by Meta AI to achieve the ultimate ambition of “a single neural network for powering scientific tasks”, according to its accompanying whitepaper. It aims to carry out knowledge-intensive tasks, such as publication summarization, information ordering and protein annotation. However, just a few days after the release, Meta had to pull back the demo due to the strong hallucinatory tendencies or underwhelming performances of the model. This article aims to study, through a critical threefold argument, the potential impacts of LLMs once deployed in the scientific value chain. Our first argument is a technical one. By examining the technicity of Galactica, it is possible to explain the descripancies between its promotional corporate discourse and abysmal outputs. Second, by going back to debates in both computer science and computational philosophy on the automation of abduction, we argue from the epistemological front that LLMs indeed cannot produce strong abductions and, therefore, claims about the automation of hypothesis generation remains chambering. Finally, our third argument is a sociological one. By conceptualizing the scientific field through Nancy Katherine Hayles’ cognitive assemblage theory, we aim to outline the potential steering of science by LLMs, mainly through information ordering. The core of our argument rests on the assertion that excessive control on information risks contravening a certain serendipitous aspect inherent to scientific discoveries.
Increasing the prediction quality of artificial neural network–based optimisation approaches for the sheet moulding compound compression moulding process by means of targeted expansion of training data
Authors: Hopmann Christian , Hadenfeldt Marie , Neuhaus Jonas , Foerges Dominik 
Published: October 2024

AbstractThe resulting fibre orientation when pressing Sheet Moulding Compound (SMC) is essentially dependent on the position and geometry of the resin mat in the mould. It is desirable to adapt the fibre orientation as best as possible to best withstand the applied load. The relationship between the position and geometry of the resin mat and the deflection of the final part under a specific load can be mapped using a numerical simulation; nevertheless, an optimisation is not feasible based on the simulation in an economically reasonable time frame due to the required computing time. For this reason, a metamodel based on an ensemble of artificial neural networks (ANN) was created on the basis of the simulation data, and an optimisation based on these ANN was set up. However, the investigations show that the minimal deflections found on the basis of the metamodel through optimisation have large deviations compared to the simulation. This leads to the hypothesis that the applied optimisation finds weak points of the metamodel instead of actual minima. From this hypothesis, an extension approach of the data set on which the metamodel is based by the weak points found is derived and implemented. This is done in an iterative process. The results show that the goal of increasing the prediction quality of the optimisation approach is achieved by the developed approach. The root mean square error (RMSE) could be reduced from the original deflection of 25 to 7 mm, which corresponds to a reduction of 72%. It is shown that the presented approach is successful in increasing prediction quality; nevertheless, further measures are needed to reach decent prediction quality.