bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of CoP@B,N,P co-doped porous carbon by a supramolecular gel self-assembly method for lithium–sulfur battery separator modification
Authors: Shi Zhenpu , Huang Yunqi , Xu Juhong , Pang Yudong , Wang Lan , Zhao Wanli , Yue Hongyun , Yang Zongxian , Yang Shuting , Yin Yanhong
Published: May 2023

The CoP@BNPC-modified separator effectively inhibited the shuttle effect of LiPSs with strong adsorption capacity.
The diverse chemistry of protoplanetary disks as revealed by JWST
Authors: van Dishoeck Ewine F. , Grant S. , Tabone B. , van Gelder M. , Francis L. , Tychoniec L. , Bettoni G. , Arabhavi A. M. , Gasman D. , Nazari P. , Vlasblom M. , Kavanagh P. , Christiaens V. , Klaassen P. , Beuther H. , Henning Th. , Kamp I.
Published: May 2023

Early results from JWST-MIRI programs on low- and high-mass protostars and disks show significant diversity in their mid-infrared spectra, most notably for CO2, H2O and C2H2. Benzene is detected in disks around very low mass stars.
Mechanochemical Simmons–Smith cyclopropanationviaball-milling-enabled activation of zinc(0)
Authors: Pontini Lorenzo , Leitch Jamie A. , Browne Duncan L.
Published: May 2023

The bulk solvent-free synthesis of cyclopropanesviaa ball-milling-enabled Simmons–Smith reaction is herein described.
Emerging integrated SERS-microfluidic devices for analysis of cancer-derived small extracellular vesicles
Authors: Ngo Long , Pham Le Que Anh , Tukova Anastasiia , Hassanzadeh-Barforoushi Amin , Zhang Wei , Wang Yuling
Published: May 2023

This tutorial review has comprehensively discussed the design of microfluidic device to integrate SERS with it, and addressed the key features and challenges of the integrated platform in the study of cancer-derived small extracellular vesicles (sEVs).
Synthesis of coral-like gold nanocrystals with the glutamic acid–cysteine–glycine–glutamic acid–cysteine–glycine hexapeptide for the electrochemical detection of α-amanitin in urine
Authors: Li Ruiyi , Zhu Qiyue , Sun Xiulan , Xu Pengwu , Li Zaijun
Published: May 2023

The paper reports a facile synthesis of oral-like gold nanocrystal using glutamic acid-cysteine-glycine-glutamic acid-cysteine-glycine hexapeptide as an shape inducer for highly sensitive electrochemical detection of α-amanitin.
Degradation processes of protic ionic liquids for NH3 separation
Authors: Duan Huifang , Liu Fan , Hussain Shahid , Dong Haifeng , Zhang Xiangping , Cheng Zhiyu
Published: May 2023

The long-term stabilities and degradation processes of protic ionic liquids with outstanding NH3 absorption capacities were explored.
A single site mutation can induce functional promiscuity in homoserine kinase
Authors: Tripathi Ankita , Dubey Kshatresh Dutta
Published: May 2023

l-Homoserine kinase is crucial in the biosynthesis of l-threonine, l-isoleucine, and l-methionine, where it catalyzes ATP-dependent phosphorylation of l-homoserine (Hse) to yield l-homoserine phosphate as its native activity.
Recent developments in the chemical biology of amyloid-β oligomer targeting
Authors: Wang Yalin , Chen Jiefang , Gao Furong , Hu Ming , Wang Xiaohui
Published: May 2023

This review discusses the recent advances in amyloid-β oligomer-targeting agents in terms of their structural design, recognition mechanisms, and potential applications in diagnostics, therapeutics, and pathogenesis studies of Alzheimer's disease.
Neutrophil membrane biomimetic delivery system (Ptdser‐NM‐Lipo/Fer‐1) designed for targeting atherosclerosis therapy
Authors: Li Wei , Liu Chang , Wang Sichuan , Liu Naifeng
Published: May 2023

Atherosclerosis is a progressive inflammatory disease characterised by excessive lipid accumulation and inflammatory cell infiltration and is the basis of most cardiovascular diseases and peripheral arterial diseases. Therefore, an effectively targeted delivery system is urgently needed to deliver ferroptosis‐specific inhibitors to the site of arterial plaque and the inflammatory microenvironment. Inspired by the fact that neutrophils can be recruited to arterial plaques under the action of adhesion molecules and chemokines, the authors developed a neutrophil membrane hybrid liposome nano‐mimetic system (Ptdser‐NM‐Lipo/Fer‐1) that delivers Ferrostatin‐1 (Fer‐1) to the atherosclerotic plaque effectively, which is composed of Fer‐1‐loaded Ptdser‐modified liposomes core and neutrophils shell. Fer‐1 was released at the AS plaque site to remove reactive oxygen species (ROS) and improve the inflammatory microenvironment. In vitro ROS clearance experiments have shown that 50 μmol/ml Fer‐1 can significantly remove ROS produced by H2O2‐induced MOVAS cells and Ptdser‐NM‐Lipo/Fer‐1 revealed a 3‐fold increase in the inhibition rate of ROS than free Fer‐1 in induced‐RAW264.7, demonstrating its superior ROS‐cleaning effect. Based on the interaction of adhesion molecules, such as vascular cell adhesion molecule 1, ICAM‐1, P‐selectin, E‐selectin, and chemokines released in the inflamed site, the aorta in NM‐Lipo‐treated mice displayed 1.3‐fold greater radiant efficiency than platelet membrane‐Lipo‐treated mice. Meanwhile, due to the modification of the Ptdser, the aorta in Ptdser‐NM‐Lipo/Fer‐1‐treated mice exhibited the highest fluorescence intensity, demonstrating its excellent targeting ability for atherosclerosis. Therefore, we present a specific formulation for the treatment of atherosclerosis with the potential for novel therapeutic uses.
Identification of bearing fault in induction motor using random forest algorithm
Authors: KaliappanSivakumar KrishnaVeni , Ganesan Gowsalya , Chermakani Gnana Soundari , Muthukumar Darsani
Published: May 2023

In day-to-day life 90% of industries use induction motors due toless maintenance, high efficiency, good Power factor and low cost. Maintenance of the induction motor is important for continuous operation in industries.40-60% of the fault in Induction motors is due to bearing failure. Unexpected bearing failures could cause industries to spend money on repairing and replacing the bearing, along with that other nearby components might damaged. Failure in bearing, decrease the plant’s operating efficiency, increases downtime, raises operating costs and in the worst case, it may cause injuries to workers. The proposed method detects and diagnoses the bearing fault using vibration signals. The fault gets detected by using the Machine learning classifier. The proposed method achieves high accuracy in detecting and diagnosing the bearing fault. The proposed work is implemented using Google Colab (colaboratory) software. The result demonstrates the usefulness of the suggested of strategy enhancing the maintenance of bearing in good condition and safe operation in the induction motor.
Effects of Active Cooling Techniques to Improve The Overall Efficiency Of Photovoltaic Module- An Updated Review
Authors: Tiwari Mayank Kumar , Mishra Venktesh , Dev Rahul , Singh Nitin
Published: May 2023

Our scientists have struggled for the last few decades to save the nation from the harmful emission caused by burning fossil fuel and restore enormous solar radiation energy. Despite their hard labor in this field, only 12-16% of solar radiation is converted into electrical energy. The major part of it is wastage as heat that causes to rise of panel temperature and lowers its efficiency. The aim of the review is to find out the cost-effective and efficient active cooling methods of solar photovoltaic (SPV) cell to improve their overall performance. Therefore, thirty-two active cooling techniques are thoroughly studied, compared their results from more than a hundred papers. Cooling of the SPV panel is a function of optimum spraying timing, coolant flow rate, wind condition, the distance between flow points (nozzle) to the panel, and solar radiation. The major facts revealed that the efficiency of the PV panel is optimum within 25-300C, and the panel's performance decreases by 0.5% for each 10C rise of panel temperature from standard temperature. The best active cooling method revealed that the electrical efficiency of the PV module could be increased by 57% with a lowering of module temperature by 32% in hot summer.
Integrating Renewable Energy Sources with Micro Grid Using IOT and Machine Learning
Authors: R. Preetha , S. Ramesh Kumar , R. Srisainath , Divya P. Backiya
Published: May 2023

The integration of renewable energy sources with microgrids using IoT and energy management technologies has become a promising solution for achieving sustainable and efficient energy systems. In this paper, propose a methodology for integrating renewable energy sources with microgrids using IoT and energy management technologies, and apply an Artificial Neural Network (ANN) algorithm for energy demand prediction. The proposed methodology aims to optimize the energy consumption of the micro grid by utilizing renewable energy sources and energy storage devices. Validate the proposed methodology using a real-world dataset, and compare the performance with traditional forecasting methods. The results show that the proposed methodology outperforms traditional methods in terms of accuracy and efficiency. The proposed methodology can be utilized in various micro grid applications for load forecasting and energy consumption optimization.
Theorytical Approach on Application of Generalized Closed Sets Environmental Lifestyle Using r-Neighbourhood Idealspaces
Authors: S. Tharmar , R. Veerasivaji , R. Senthil kumar
Published: May 2023

We introduce in this paper, the new notion of RI-g-closed sets and obtain some of its characterizations in ideal r-Neighbourhood space and give nice results on RI-g-closed sets with examples. Finally, we discuss application of RI-g-closed sets.
Design and Development of a Solar- Powered UAV Using IoT and Machine Learning
Authors: S. Ananthi , Sirija N. , R. Shanmugapriya , M. Rajeswari
Published: May 2023

The proposed solar-powered UAV utilizes photovoltaic panels to convert solar energy into electrical power to supply the onboard electronic systems, including the propulsion system and sensors. To enhance the UAV's performance, loT technology is employed to enable the communication and coordination of the UAV with other connected devices, such as ground stations and sensors. This allows for real-time data collection and analysis, as well as improved situational awareness for the UAV. To optimize the performance of the UAV, SVM is used as a machine learning algorithm for object detection and classification. SVM has been widely used in UAVs to detect and classify objects in aerial images, and has been proven to be effective in a variety of applications. The proposed design utilizes SVM to detect and classify objects of interest, such as crops, buildings, and infrastructure, and to assist in the navigation and control of the UAV. The design and development of the proposed solar-powered UAV involves several key components, including the solar panels, propulsion system, control system, and communication system.
A Performance Comparison of Machine Learning Methods For Short-Range Wind Power Estimation
Authors: Selvi B. Dora Arul , S. Kannan
Published: May 2023

Renewable energy generation is increasingly employed nowadays for multitudes of reasons such as global warming, depletion of conventional sources of energy and emission constraints. Even though the wind generators constitute a potential source of energy, the uncertainties associated with them make the operation complex. As a consequence, the successful operation and planning of the present distributed generation dominated power systems requires exact estimate of wind power. Numerous wind power estimation techniques based on Machine Learning were available. This work attempts to compare the wind power estimation efficiency of a few machine learning approaches. At first, the performance of a Feed Forward Neural Network with different activation functions is considered. Next, Support Vector Regression Machine with different kernels is utilized for estimating the wind power. Then, deep Learning networks such as Long Short-Term Memory network, Convolutional Neural Network and Recurrent Neural Network are employed for assessing the future wind power and their ability is analyzed. Finally, a comparative chart is prepared to evaluate the efficacy and usefulness of the different machine learning techniques employed for estimating wind power.
Reduced order modeling for elliptic problems with high contrast diffusion coefficients
Authors: Cohen Albert , Dahmen Wolfgang , Dolbeault Matthieu , Somacal Agustin
Published: May 2023

We consider a parametric elliptic PDE with a scalar piecewise constant diffusion coefficient taking arbitrary positive values on fixed subdomains. This problem is not uniformly elliptic, as the contrast can be arbitrarily high, contrary to the Uniform Ellipticity Assumption (UEA) that is commonly made on parametric elliptic PDEs.We construct reduced model spaces that approximate uniformly well all solutions with estimates in relative error that are independent of the contrast level. These estimates are sub-exponential in the reduced model dimension, yet exhibiting the curse of dimensionality as the number of subdomains grows. Similar estimates are obtained for the Galerkin projection, as well as for the state estimation and parameter estimation inverse problems. A key ingredient in our construction and analysis is the study of the convergence towards limit solutions of stiff problems when diffusion tends to infinity in certain domains.
Human Derived Dermal Fibroblasts as in Vitro Research Tool to Study
Circadian Rhythmicity in Psychiatric Disorders
Authors: Palm Denise , Uzoni Adriana , Kronenberg Golo , Thome Johannes , Faltraco Frank
Published: May 2023

A number of psychiatric disorders are defined by persistent or recurrent
sleep-wake disturbances alongside disruptions in circadian rhythm and
altered clock gene expression. Circadian rhythms are present not only in the
hypothalamic suprachiasmatic nucleus but also in peripheral tissues. In this
respect, cultures of human derived dermal fibroblasts may serve as a
promising new tool to investigate cellular and molecular mechanisms
underlying the pathophysiology of mental illness. In this article, we
discuss the advantages of fibroblast cultures to study psychiatric disease.
More specifically, we provide an update on recent advances in modeling
circadian rhythm disorders using human fibroblasts.
Overexpression and RNAi-mediated Knockdown of Two 3β-hydroxy-Δ5-steroid dehydrogenase Genes in Digitalis lanata Shoot Cultures Reveal Their Role in Cardenolide
Biosynthesis
Authors: Leykauf Tim , Klein Jan , Ernst Mona , Dorfner Maja , Ignatova Anastasiia , Kreis Wolfgang , Lanig Harald , Munkert Jennifer
Published: May 2023

3β-hydroxy-Δ5-steroid dehydrogenases (3βHSDs) are supposed to be involved in 5β-cardenolide biosynthesis. Here, a novel 3βHSD (Dl3βHSD2) was isolated from Digitalis
lanata shoot cultures and expressed in E. coli. Recombinant Dl3βHSD1 and Dl3βHSD2 shared 70% amino acid identity, reduced various 3-oxopregnanes and oxidised
3-hydroxypregnanes, but only rDl3βHSD2 converted small ketones and secondary alcohols efficiently. To explain these differences in substrate specificity, we established homology
models using borneol dehydrogenase of Salvia rosmarinus (6zyz) as the template. Hydrophobicity and amino acid residues in the binding pocket may explain the difference in enzyme
activities and substrate preferences. Compared to Dl3βHSD1, Dl3βHSD2 is weakly expressed in D. lanata shoots. High constitutive expression of Dl3βHSDs was realised by
Agrobacterium-mediated transfer of Dl3βHSD genes fused to the CaMV-35S promotor into the genome of D. lanata wild type shoot cultures. Transformed shoots
(35S:Dl3βHSD1 and 35S:Dl3βHSD2) accumulated less cardenolides than controls. The levels of reduced glutathione (GSH), which is known to inhibit cardenolide formation, were
higher in the 35S:Dl3βHSD1 lines than in the controls. In the 35S:Dl3βHSD1 lines cardenolide levels were restored after adding of the substrate pregnane-3,20-dione in
combination with buthionine-sulfoximine (BSO), an inhibitor of GSH formation. RNAi-mediated knockdown of the Dl3βHSD1 yielded several shoot culture lines with strongly reduced
cardenolide levels. In these lines, cardenolide biosynthesis was fully restored after addition of the downstream precursor pregnan-3β-ol-20-one, whereas upstream precursors such as
progesterone had no effect, indicating that no shunt pathway could overcome the Dl3βHSD1 knockdown. These results can be taken as the first direct proof that Dl3βHSD1 is indeed
involved in 5β-cardenolide biosynthesis.
Fäkaler Mikrobiota-Transfer (FMT) in Deutschland – Status und Perspektive
Authors: Stallmach Andreas , von Müller Lutz , Storr Martin , Link Alexander , Konturek Peter C. , Solbach Philipp Christoph , Weiss Karl Heinz , Wahler Steffen , Vehreschild Maria J. G. T.
Published: May 2023

Einführung Der Fäkale Mikrobiota-Transfer (FMT) ist eine
Behandlung zur Modulation der gastrointestinalen Mikrobiota. Der Einsatz bei rezidivierender
Clostridioides-difficile-Infektion (rCDI) ist europaweit etabliert und wird in nationalen und internationalen Leitlinien
empfohlen. Der FMT ist in Deutschland im Fallpauschalensystem der Krankenhäuser kodierfähig.
Eine auf dieser Kodierung basierende umfassende Erhebung zur Häufigkeit des Einsatzes fehlt
bislang.

Material und Methodik Berichte des Instituts für das
Entgeltsystem im Krankenhaus (InEK), des Statistischen Bundesamtes (DESTATIS) und
Qualitätsberichte der Krankenhäuser 2015–2021 wurden auf FMT-Kodierung hin untersucht und im
Rahmen einer strukturierten Expertenkonsultation bewertet.

Ergebnisse Zwischen 2015 und 2021 wurden von 175 Krankenhäusern
1.645 FMT-Verfahren kodiert. Von 2016 bis 2018 waren dies jährlich im Median 293 (274–313)
FMT, gefolgt von einem konstanten Rückgang in den folgenden Jahren auf 119 FMT im Jahr 2021.
Patienten/-innen mit FMT waren zu 57,7% weiblich, im Median 74 Jahre alt und der FMT wurde zu
72,2% koloskopisch appliziert. Bei 86,8 % der Fälle wurde eine CDI
als Hauptdiagnose genannt, gefolgt von 7,6% eine Colitis ulcerosa.

Diskussion In Deutschland wird der FMT seltener eingesetzt als im
europäischen Vergleich. Eine Anwendungshürde ist die behördliche Einordnung des FMT als nicht
zugelassenes Arzneimittel, die zu erheblich höherem Aufwand bei Herstellung und Verabreichung
führt und eine Erstattung erschwert. Die Europäische Kommission hat kürzlich eine Verordnung
vorgeschlagen, den FMT als Transplantation einzuordnen. Dies könnte die regulatorische
Situation des FMT in Deutschland perspektivisch verändern und so zu einem flächendeckenden
Angebot eines in Leitlinien empfohlenen Therapieverfahrens beitragen.
The Role of Circadian Rhythmicity and CLOCK Genes in Psychiatry
Authors: Palm Denise , Thome Johannes
Published: May 2023

Circadian rhythms are biological oscillations, that perpetuate themselves even in the absence of “zeitgebers” (external time cues), with a period of approximately 24 hours. The master pacemaker is the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is entrained by environmental factors, particularly light, to the 24-hour light-dark cycle by the Earth’s rotation. Peripheral circadian oscillators, located in multiple cell types and tissues, are controlled by signals arising from the SCN and from the environment, particularly food intake, hormonal signals and body-temperature fluctuations. Circadian rhythmicity is observable in almost every cell of living organisms including humans and, for example in cell cultures, these rhythms persist even without the SCN 1 2.
Palladium-Catalyzed Synthesis of Benzofuran Spiroketals Derived from Cholesterol; NMR and X-ray Characterization
Authors: Iglesias-Arteaga Martin A. , García-Santos William H. , Quiroz-Mendoza Ariadna M. , Mayorquín-Torres Martha C. , Flores-Álamo Marcos
Published: May 2023

The synthesis of two diastereomeric steroid spiroketals bearing a 2,3-dihydrobenzofuran moiety is described. The structure of the obtained compounds was elucidated by combined 1D and 2D NMR techniques and corroborated by X-ray crystallography studies.
Domain tethering impacts dimerization and DNA-mediated allostery in the human transcription factor FoxP1
Authors: Cruz Perla , Paredes Nicolás , Asela Isabel , Kolimi Narendar , Molina José Alejandro , Ramírez-Sarmiento César A. , Goutam Rajen , Huang Gangton , Medina Exequiel , Sanabria Hugo
Published: May 2023

Transcription factors are multidomain proteins with specific DNA binding and regulatory domains. In the human FoxP subfamily (FoxP1, FoxP2, FoxP3, and FoxP4) of transcription factors, a 90 residue-long disordered region links a Leucine Zipper (ZIP)—known to form coiled-coil dimers—and a Forkhead (FKH) domain—known to form domain swapping dimers. We used replica exchange discrete molecular dynamics simulations, single-molecule fluorescence experiments, and other biophysical tools to understand how domain tethering in FoxP1 impacts dimerization at ZIP and FKH domains and how DNA binding allosterically regulates their dimerization. We found that domain tethering promotes FoxP1 dimerization but inhibits a FKH domain-swapped structure. Furthermore, our findings indicate that the linker mediates the mutual organization and dynamics of ZIP and FKH domains, forming closed and open states with and without interdomain contacts, thus highlighting the role of the linkers in multidomain proteins. Finally, we found that DNA allosterically promotes structural changes that decrease the dimerization propensity of FoxP1. We postulate that, upon DNA binding, the interdomain linker plays a crucial role in the gene regulatory function of FoxP1.
Unimolecular dissociation of C6H6–C6H5Cl, C6H6–C6H3Cl3, and C6H6–C6Cl6 complexes using machine learning approach
Authors: Deb Basudha , Anal S. R. Ngamwal , Mahanta Himashree , Yogita  , Paul Amit Kumar
Published: May 2023

The application of Machine Learning (ML) algorithms in chemical sciences, particularly computational chemistry, is a vastly emerging area of modern research. While many applications of ML techniques have already been in place to use ML based potential energies in various dynamical simulation studies, specific applications are also being successfully tested. In this work, the ML algorithms are tested to calculate the unimolecular dissociation time of benzene–hexachlorobenzene, benzene–trichlorobenzene, and benzene–monochlorobenzene complexes. Three ML algorithms, namely, Decision-Tree-Regression (DTR), Multi-Layer Perceptron, and Support Vector Regression are considered. The algorithms are trained with simulated dissociation times as functions (attributes) of complexes’ intramolecular and intermolecular vibrational energies. The simulation data are used for an excitation temperature of 1500 K. Considering that the converged result is obtained with 1500 trajectories, an ML algorithm trained with 700 simulation points provides the same dissociation rate constant within statistical uncertainty as obtained from the converged 1500 trajectory result. The DTR algorithm is also used to predict 1000 K simulation results using 1500 K simulation data.
Rapid sedimentation of microparticles by vertically asymmetric acoustofluidics in an equilateral triangular channel
Authors: Lei Junjun , Zheng Gaokun , Cheng Feng , Li Kemin
Published: May 2023

The ability to settle particles in a fluid has a significant impact on many applications in fields like biology, chemistry, environment, and industrial processing. Here, we set up an acoustofluidics framework, based on an equilateral-triangular-channel design, which can generate vertically asymmetric acoustic pressure profiles and can result in unidirectionally downward acoustic radiation force and acoustic streaming-induced drag force on the pressure nodal plane, enabling rapid agglomeration and sedimentation of microparticles toward the channel wall. This approach is verified in an acoustofluidic device, mainly composed of an equilateral triangular glass capillary (with outer and inner side lengths of 2 and 1 mm, respectively) and two piezoelectric transducers (15 × 1.4 × 2 mm3), both experimentally and numerically and a good agreement is obtained. Specifically, ultrasound enhanced sedimentation of 10 μm polystyrene particles was used to demonstrate the efficiency of the system, which shows that, with the additional acoustic force fields, the acoustofluidic resonator had much higher sedimentation efficiency in comparison to the gravity-induced sedimentation in a fluid (which is about 7 min). The ultrasound enhanced settling efficiency (i.e., the settling time) in such a system is strongly dependent on the pressure magnitudes and the configuration of the acoustofluidic device. It was demonstrated that, at a driving voltage of 25 Vpp, the present device enables settling of 95% of the microparticles to the channel wall within 30 s and 100% at about 1 min.
Optimization of transformer ratio and beam loading in a plasma wakefield accelerator with a structure-exploiting algorithm
Authors: Su Q. , Larson J. , Dalichaouch T. N. , Li F. , An W. , Hildebrand L. , Zhao Y. , Decyk V. , Alves P. , Wild S. M. , Mori W. B.
Published: May 2023

Plasma-based acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a next-generation light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewise-linear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. The current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the relativistic limit of the nonlinear theory.
A machine learning based computational approach for prediction of cation distribution in spinel crystal
Authors: Fang Ying , Ohodnicki Paul R. , Wang Guofeng
Published: May 2023

In this study, a machine learning based computational approach has been developed to investigate the cation distribution in spinel crystals. The computational approach integrates the construction of datasets consisting of the energies calculated from density functional theory, the training of machine learning models to derive the relationship between system energy and structural features, and atomistic Monte Carlo simulations to sample the thermodynamic equilibrium structures of spinel crystals. It is found that the support vector machine model yields excellent performance in energy predictions based on spinel crystal structures. Furthermore, the developed computational approach has been applied to predict the cation distribution in single spinel MgAl2O4 and MgFe2O4 and double spinel MgAl2-aFeaO4. Agreeing with the available experimental data, the computational approach correctly predicts that the equilibrium degree of inversion of MgAl2O4 increases with temperature, whereas the degree of inversion of MgFe2O4 decreases with temperature. Additionally, it is predicted that the equilibrium occupancy of Mg cations at the tetrahedral and octahedral sites in MgAl2-aFeaO4 could be tuned as a function of chemical composition. Therefore, this study presents a reliable computational approach that can be extended to study the variation of cation distribution with processing temperature and chemical composition in a wide range of complex multi-cation spinel oxides with numerous applications.
Depletion-driven antiferromagnetic, paramagnetic, and ferromagnetic behavior in quasi-two-dimensional buckled colloidal solids
Authors: Hill Analisa , Tanaka Michio , Aptowicz Kevin B. , Mishra Chandan K. , Yodh A. G. , Ma Xiaoguang
Published: May 2023

We investigate quasi-two-dimensional buckled colloidal monolayers on a triangular lattice with tunable depletion interactions. Without depletion attraction, the experimental system provides a colloidal analog of the well-known geometrically frustrated Ising antiferromagnet [Y. Han et al., Nature 456, 898–903 (2008)]. In this contribution, we show that the added depletion attraction can influence both the magnitude and sign of an Ising spin coupling constant. As a result, the nearest-neighbor Ising “spin” interactions can be made to vary from antiferromagnetic to para- and ferromagnetic. Using a simple theory, we compute an effective Ising nearest-neighbor coupling constant, and we show how competition between entropic effects permits for the modification of the coupling constant. We then experimentally demonstrate depletion-induced modification of the coupling constant, including its sign, and other behaviors. Depletion interactions are induced by rod-like surfactant micelles that change length with temperature and thus offer means for tuning the depletion attraction in situ. Buckled colloidal suspensions exhibit a crossover from an Ising antiferromagnetic to paramagnetic phase as a function of increasing depletion attraction. Additional dynamical experiments reveal structural arrest in various regimes of the coupling-constant, driven by different mechanisms. In total, this work introduces novel colloidal matter with “magnetic” features and complex dynamics rarely observed in traditional spin systems.
Implementation of the self-consistent phonons method with ab initio potentials (AI-SCP)
Authors: Schiltz Colin , Rappoport Dmitrij , Mandelshtam Vladimir A.
Published: May 2023

The self-consistent phonon (SCP) method allows one to include anharmonic effects when treating a many-body quantum system at thermal equilibrium. The system is then described by an effective temperature-dependent harmonic Hamiltonian, which can be used to estimate its various dynamic and static properties. In this paper, we combine SCP with ab initio (AI) potential energy evaluation in which case the numerical bottleneck of AI-SCP is the evaluation of Gaussian averages of the AI potential energy and its derivatives. These averages are computed efficiently by the quasi-Monte Carlo method utilizing low-discrepancy sequences leading to a fast convergence with respect to the number, S, of the AI energy evaluations. Moreover, a further substantial (an-order-of-magnitude) improvement in efficiency is achieved once a numerically cheap approximation of the AI potential is available. This is based on using a perturbation theory-like (the two-grid) approach in which it is the average of the difference between the AI and the approximate potential that is computed. The corresponding codes and scripts are provided.
Machine learning interatomic potential for silicon-nitride (Si3N4) by active learning
Authors: Milardovich Diego , Wilhelmer Christoph , Waldhoer Dominic , Cvitkovich Lukas , Sivaraman Ganesh , Grasser Tibor
Published: May 2023

Silicon nitride (Si3N4) is an extensively used material in the automotive, aerospace, and semiconductor industries. However, its widespread use is in contrast to the scarce availability of reliable interatomic potentials that can be employed to study various aspects of this material on an atomistic scale, particularly its amorphous phase. In this work, we developed a machine learning interatomic potential, using an efficient active learning technique, combined with the Gaussian approximation potential (GAP) method. Our strategy is based on using an inexpensive empirical potential to generate an initial dataset of atomic configurations, for which energies and forces were recalculated with density functional theory (DFT); thereafter, a GAP was trained on these data and an iterative re-training algorithm was used to improve it by learning on-the-fly. When compared to DFT, our potential yielded a mean absolute error of 8 meV/atom in energy calculations for a variety of liquid and amorphous structures and a speed-up of molecular dynamics simulations by 3–4 orders of magnitude, while achieving a first-rate agreement with experimental results. Our potential is publicly available in an open-access repository.
High breakdown electric field diamond Schottky barrier diode with HfO2 field plate
Authors: Li Qi , Zhang Shumiao , Shao Guoqing , Wang Juan , Wang Ruozheng , Zhang Qianwen , Chen Genqiang , He Shi , Fan Shuwei , Wang Hong-Xing
Published: May 2023

In this work, we fabricated a vertical diamond Schottky barrier diode (SBD) with a high breakdown electric field of 4.8 MV/cm and a forward current density of 2361 A/cm2. Compared with a regular diamond SBD, the breakdown electric field of SBD with a HfO2 field plate (FP) increased from 183 to 302 V, the current swing (ION/IOFF) was on the order of 1011. As the thickness of the HfO2 FP increased from 200 to 400 nm, the breakdown voltage of the SBD increased from 280 to 314 V, and the corresponding breakdown electric field increased from 4.5 to 5 MV/cm. We also measured the current–voltage characteristics at different temperatures to investigate the cause of the high on-resistance. As the measured temperature increased from 25 to 150 °C, the on-resistance of the device decreased from 4.7 to 1.7 mΩ·cm2. By studying the interface between HfO2 and the diamond, we found that HfO2 can reduce the interface state density of the Schottky contact. The interface state density of Zr/HfO2/diamond was lower than 1.5 × 1013 eV−1·cm−2. This work provides a simple strategy for realizing high-performance diamond SBDs.
Further cautionary tales on thermostatting in molecular dynamics: Energy equipartitioning and non-equilibrium processes in gas-phase simulations
Authors: Halonen Roope , Neefjes Ivo , Reischl Bernhard
Published: May 2023

Molecular dynamics (MD) simulations of gas-phase chemical reactions are typically carried out on a small number of molecules near thermal equilibrium by means of various thermostatting algorithms. Correct equipartitioning of kinetic energy among translations, rotations, and vibrations of the simulated reactants is critical for many processes occurring in the gas phase. As thermalizing collisions are infrequent in gas-phase simulations, the thermostat has to efficiently reach equipartitioning in the system during equilibration and maintain it throughout the actual simulation. Furthermore, in non-equilibrium simulations where heat is released locally, the action of the thermostat should not lead to unphysical changes in the overall dynamics of the system. Here, we explore issues related to both obtaining and maintaining thermal equilibrium in MD simulations of an exemplary ion–molecule dimerization reaction. We first compare the efficiency of global (Nosé–Hoover and Canonical Sampling through Velocity Rescaling) and local (Langevin) thermostats for equilibrating a system of flexible compounds and find that of these three only the Langevin thermostat achieves equipartition in a reasonable simulation time. We then study the effect of the unphysical removal of latent heat released during simulations involving multiple dimerization events. As the Langevin thermostat does not produce the correct dynamics in the free molecular regime, we only consider the commonly used Nosé–Hoover thermostat, which is shown to effectively cool down the reactants, leading to an overestimation of the dimerization rate. Our findings underscore the importance of thermostatting for the proper thermal initialization of gas-phase systems and the consequences of global thermostatting in non-equilibrium simulations.
Twofold increase in the sensitivity of Er3+/Yb3+ Boltzmann thermometer
Authors: Ćirić Aleksandar , van Swieten Thomas , Periša Jovana , Meijerink Andries , Dramićanin Miroslav D.
Published: May 2023

Luminescence thermometry is the most versatile remote temperature sensing technique and can be employed from living cells to large surfaces and from cryogenic temperatures to the melting points of metals. Ongoing research aims to optimize the sensitivity of the ratio between the emission intensity from two coupled excited states. However, this approach is inherently limited to temperature-dependent processes involving only the excited states. Here, we develop a novel measurement technique, called luminescence intensity ratio squared (LIR2) for the Yb3+/Er3+ pair, that combines the temperature sensitivity of ground- and excited-state populations. We use Y3Al5O12:Er3+,Yb3+ nanoparticles as a promising model system with both visible and infrared emissions. To apply our method, we record two luminescence spectra at different excitation wavelengths and determine the LIR2 using one emission in each of the two spectra. The LIR2 testing with Y3Al5O12 nanoparticles showed a sensitivity increase of 70% in the visible region and an impressive 230% increase in the NIR region compared to the conventional LIR method. This enhances the measurement precision by a factor of 1.5–2.5. The LIR2 based on the visible upconversion emission is particularly useful for measurements of high temperatures, while the LIR2 based on the downshifted ∼1.5 μm emission may revolutionize temperature measurements of biological samples in the range of physiological temperatures.
Diffusion of knots in nanochannel-confined DNA molecules
Authors: Mao Runfang , Dorfman Kevin D.
Published: May 2023

We used Langevin dynamics simulations without hydrodynamic interactions to probe knot diffusion mechanisms and the time scales governing the evolution and the spontaneous untying of trefoil knots in nanochannel-confined DNA molecules in the extended de Gennes regime. The knot untying follows an “opening up process,” wherein the initially tight knot continues growing and fluctuating in size as it moves toward the end of the DNA molecule before its annihilation at the chain end. The mean knot size increases significantly and sub-linearly with increasing chain contour length. The knot diffusion in nanochannel-confined DNA molecules is subdiffusive, with the unknotting time scaling with chain contour length with an exponent of 2.64 ± 0.23 to within a 95% confidence interval. The scaling exponent for the mean unknotting time vs chain contour length, along with visual inspection of the knot conformations, suggests that the knot diffusion mechanism is a combination of self-reptation and knot region breathing for the simulated parameters.
Power law in a bounded range: Estimating the lower and upper bounds from sample data
Authors: Zhou Huan-Xiang
Published: May 2023

Power law distributions are widely observed in chemical physics, geophysics, biology, and beyond. The independent variable x of these distributions has an obligatory lower bound and, in many cases, also an upper bound. Estimating these bounds from sample data is notoriously difficult, with a recent method involving O(N3) operations, where N denotes sample size. Here I develop an approach for estimating the lower and upper bounds that involve O(N) operations. The approach centers on calculating the mean values, x̂min and x̂max, of the smallest x and the largest x in N-point samples. A fit of x̂min or x̂max as a function of N yields the estimate for the lower or upper bound. Application to synthetic data demonstrates the accuracy and reliability of this approach.
High-electron mobility P-doped polycrystalline GeSn layers formed on insulators at low temperatures
Authors: Nozawa K. , Ishiyama T. , Nishida T. , Saitoh N. , Yoshizawa N. , Suemasu T. , Toko K.
Published: May 2023

Despite its long history, synthesizing n-type polycrystalline Ge layers with high-electron mobility on insulating substrates has been difficult. Based on our recently developed solid-phase crystallization technology, here, we have demonstrated the highest recorded electron mobility (450 cm2 V−1 s−1) for Ge-based polycrystalline thin films on insulating substrates. The underlayer type and small amount of Sn addition were the key parameters controlling both the density and barrier height of the grain boundaries in the P-doped polycrystalline Ge layers. The low growth temperature (≤400 °C) allowed us to develop a GeSn layer on a heat-resistant polyimide film, which exhibited the highest electron mobility (200 cm2 V−1 s−1), as a semiconductor thin film synthesized directly on a flexible substrate. These achievements herald the development of high-performance polycrystalline Ge-based devices on inexpensive glass and flexible plastic substrates.
Diet of the finescale triggerfish, Balistes polylepis (Steindachner), in the Gulf of California
Authors: Acosta-Pachón Tatiana A. , López-Vivas Juan Manuel , Mazariegos-Villarreal Alejandra , León-Cisneros Karla , Medina-López Marco A. , Barjau González Emelio , Serviere-Zaragoza Elisa
Published: May 2023

Context Establishing the roles that different species play within ecosystems is key to understanding how ecosystems function and determining the feeding relationships among species. Aims This study analysed the stomach contents of finescale triggerfish, Balistes polylepis, at two sites in the southern Gulf of California, in order to describe its diet. Methods The prey-specific index of relative importance (%PSIRIi) was determined, diet width was calculated with Levins’ index and the Costello method, and the trophic position was estimated using the R package dietr. Key results B. polylepis is an omnivorous species with a preference for animal material (TL = 3.1) that feeds on a wide range of prey. It is categorised as a generalist predator (Levins’ index, Bi = 0.99). The most important items in the diet were the colonial ascidian Lissoclinum fragile (%PSIRIi = 13.52) at Las Ánimas, and the Xanthidae family (%PSIRIi = 13.24) at San Juan de la Costa. Implications B. polylepis plays an important role. Because it can exploit a broad variety of resources, it participates in trophic interactions with several other species. It is essential to determine the trophic habits of this species in other areas of its distribution.
Supporting complex care in general practice via an eConsultant model of care: the Australian specialist perspective
Authors: Petre Joel , Donald Maria , Jackson Claire
Published: May 2023

Background Accessing timely specialist physician advice and guidance is of critical importance to both Australian GP specialists (GPs) and their patients. The traditional method of referral, triage and subsequent face-to-face (FTF) consultation is facing challenges from an ever increasing volume of referrals and the needs of underserved populations. In response to such issues, electronic consults (eConsults) have been successfully used internationally to provide GPs with a means of asynchronously accessing specialist physician advice and guidance within 72 h. Few studies have addressed the potential impact of eConsults from the view of the non-GP specialist receiving the request, and none specifically related to specialist adult medicine physicians. The aim of this study was to determine the perceptions of current Royal Australasian College of Physicians (RACP) adult medicine Fellows towards establishing an eConsult model of care within their own clinical practice. Methods Semi-structured interviews were conducted with 14 RACP adult medicine Fellows between December 2019 and February 2020. Purposive and snowball sampling strategies were used to recruit physicians of differing ages and gender from diverse specialties and healthcare settings. The data were subjected to a descriptive thematic analysis. Results We describe five key themes of relevance to study participants: (1) improved access to non-GP specialist care; (2) the business model in relation to remuneration and time; (3) enhanced GP–Physician relationships; (4) impact on physician work–life balance; and (5) the need for a structured model of care. There was broad consensus that a significant number of outpatient referrals to adult medicine physicians would be more appropriately addressed in primary care with support via an asynchronous eConsult arrangement. RACP Fellows agreed this could improve access to timely specialist advice, place downward pressure on outpatient FTF clinic waiting times and reduce unnecessary patient travel. Conclusion These findings identify the drivers and barriers to the establishment of an Australian eConsultant model of care from the adult medicine physician’s perspective.
Improving HIV pre-exposure prophylaxis (PrEP) uptake and initiation: process evaluation and recommendation development from a national PrEP program†
Authors: Estcourt Claudia S. , MacDonald Jennifer , Saunders John , Nandwani Rak , Young Ingrid , Frankis Jamie , Clutterbuck Dan , Steedman Nicola , McDaid Lisa , Dalrymple Jenny , Flowers Paul
Published: May 2023

Background HIV pre-exposure prophylaxis (PrEP) is key to HIV transmission elimination but implementation is challenging and under-researched. We undertook a process evaluation of the first 2 years of a national PrEP program to explore barriers and facilitators to implementation and to develop recommendations to improve implementation, focusing on PrEP uptake and initiation. Methods Stage 1 involved semi-structured telephone interviews and focus groups (September 2018–July 2019) with geographically and demographically diverse patients seeking/using/declining/stopping PrEP (n = 39), sexual healthcare professionals (n = 54), community-based organisation service users (n = 9) and staff (n = 15) across Scotland. We used deductive thematic analysis, to derive and then map key barriers and facilitators to priority areas that experts agreed would enhance uptake and initiation. In Stage 2, we used analytic tools from implementation science to systematically generate evidence-based, theoretically-informed recommendations to enhance uptake and initiation of PrEP. Results Barriers and facilitators were multi-levelled and interdependent. Barriers included the rapid pace of implementation without additional resource, and a lack of familiarity with PrEP prescribing. Facilitators included opportunities for acquisition of practice-based knowledge and normalisation of initiation activities. We refined our 68 ‘long-list’ recommendations to 41 using expert input and the APEASE (Acceptability, Practicability, Effectiveness, Affordability, Side-effects, and Equity) criteria. Examples include: provision of PrEP in diverse settings to reach all in need; co-produced, culturally sensitive training resources for healthcare professionals, with focused content on non-daily dosing; meaningful collaborative working across all stakeholders. Conclusions These evidence-based, theory informed recommendations provide a robust framework for optimising PrEP uptake and initiation in diverse settings to ensure PrEP reaches all who may benefit.