bluuebunny/crossref_metadata_2025 huggingface dataset:
How does an organism extract relevant information from transcription factor concentrations?
Authors: Bauer Marianne
Published: September 2022

How does an organism regulate its genes? The involved regulation typically occurs in terms of a signal processing chain: an externally applied stimulus or a maternally supplied transcription factor leads to the expression of some downstream genes, which, in turn, are transcription factors for further genes. Especially during development, these transcription factors are frequently expressed in amounts where noise is still important; yet, the signals that they provide must not be lost in the noise. Thus, the organism needs to extract exactly relevant information in the signal. New experimental approaches involving single-molecule measurements at high temporal precision as well as increased precision in manipulations directly on the genome are allowing us to tackle this question anew. These new experimental advances mean that also from the theoretical side, theoretical advances should be possible. In this review, I will describe, specifically on the example of fly embryo gene regulation, how theoretical approaches, especially from inference and information theory, can help in understanding gene regulation. To do so, I will first review some more traditional theoretical models for gene regulation, followed by a brief discussion of information-theoretical approaches and when they can be applied. I will then introduce early fly development as an exemplary system where such information-theoretical approaches have traditionally been applied and can be applied; I will specifically focus on how one such method, namely the information bottleneck approach, has recently been used to infer structural features of enhancer architecture.
Context‐aware Siamese network for object tracking
Authors: Zhang Jianwei , Wang Jingchao , Zhang Huanlong , Miao Mengen , Wu Di
Published: September 2022

At present, temporal and spatial contexts are widely used to improve the adaptability of a tracker. However, most existing methods usually focus on one aspect of the temporal or spatial context and rarely exploit them simultaneously. In this paper, a context‐aware Siamese Network (CSNet) is proposed, which skilfully integrates the modelling of temporal and spatial context into the Siamese tracking framework. Specifically, CSNet consists of a context‐based channel attention module and a context‐based cross‐attention module. The former aggregates spatial context information from different channels and dynamically emphasizes target features, which makes it easier for the tracker to distinguish the target from the background. The latter propagates the temporal context from the previous frames to the current frame to establish the part‐level relationship between the search region and the historical target state, which enables the tracker better adapt to the target deformation. In addition, to further mine context information, the CSNet is equipped with a state‐aware strategy to control the contribution of different context information in tracking. Extensive experiments on OTB2015, UAV123, GOT‐10k, LaSOT, and TrackingNet show that the proposed tracking method achieves comparable performance to the advanced trackers.
Reshaping and ejection processes on rubble-pile asteroids from impacts
Authors: Raducan S. D. , Jutzi M. , Zhang Y. , Ormö J. , Michel P.
Published: September 2022

Context. Most small asteroids (< 50 km in diameter) are the result of the breakup of a larger parent body and are often considered to be rubble-pile objects. Similar structures are expected for the secondaries of small asteroid binaries, including Dimorphos, the smaller component of the 65 803 Didymos binary system and the target of NASA’s Double Asteroid Redirection Test (DART) and ESA’s Hera mission. The DART impact will occur on September 26, 2022, and will alter the orbital period of Dimorphos around Didymos.

Aims. In this work we assume Dimorphos-like bodies with a rubble-pile structure and quantify the effects of boulder packing in its interior on the post-impact morphology, degree of shape change, and material ejection processes.

Methods. We used the Bern smoothed particle hydrodynamics shock physics code to numerically model hypervelocity impacts on small, 160 m in diameter, rubble-pile asteroids with a variety of boulder distributions.

Results. We find that the post-impact target morphology is most sensitive to the mass fraction of boulders comprising the target, while the asteroid deflection efficiency depends on both the mass fraction of boulders on the target and on the boulder size distribution close to the impact point. Our results may also have important implications for the structure of small asteroids.
Post COVID and Apheresis – Where are we
Standing?
Authors: Steenblock Charlotte , Walther Romy , Tselmin Sergey , Jarzebska Natalia , Voit-Bak Karin , Toepfner Nicole , Siepmann Timo , Passauer Jens , Hugo Christian , Wintermann Gloria , Julius Ulrich , Barbir Mahmoud , Khan Tina Z. , Puhan Milo A. , Straube Richard , Hohenstein Bernd , Bornstein Stefan R. , Rodionov Roman N.
Published: September 2022

A continual increase in cases of Long/Post COVID constitutes a medical
and socioeconomic challenge to health systems around the globe. While the true
extent of this problem cannot yet be fully evaluated, recent data suggest that
up to 20% of people with confirmed SARS-CoV-2 suffer from clinically
relevant symptoms of Long/Post COVID several weeks to months after the
acute phase. The clinical presentation is highly variable with the main symptoms
being chronic fatigue, dyspnea, and cognitive symptoms. Extracorporeal apheresis
has been suggested to alleviate symptoms of Post/COVID. Thus, numerous
patients are currently treated with apheresis. However, at present there is no
data from randomized controlled trials available to confirm the efficacy.
Therefore, physicians rely on the experience of practitioners and centers
performing this treatment. Here, we summarize clinical experience on
extracorporeal apheresis in patients with Post/COVID from centers across
Germany.
Advances in the Management of Coagulopathy in Trauma: The Role of Viscoelastic Hemostatic Assays across All Phases of Trauma Care
Authors: Meizoso Jonathan P. , Barrett Christopher D. , Moore Ernest E. , Moore Hunter B.
Published: September 2022

Uncontrolled bleeding is the leading cause of preventable death following injury. Trauma-induced coagulopathy can manifest as diverse phenotypes ranging from hypocoagulability to hypercoagulability, which can change quickly during the acute phase of trauma care. The major advances in understanding coagulation over the past 25 years have resulted from the cell-based concept, emphasizing the key role of platelets and their interaction with the damaged endothelium. Consequently, conventional plasma-based coagulation testing is not accurate in predicting bleeding and does not provide an assessment of which blood products are indicated. Viscoelastic hemostatic assays (VHA), conducted in whole blood, have emerged as a superior method to guide goal-directed transfusion. The major change in resuscitation has been the shift from unbridled crystalloid loading to judicious balanced blood product administration. Furthermore, the recognition of the rapid changes from hypocoagulability to hypercoagulability has underscored the importance of ongoing surveillance beyond emergent surgery. While the benefits of VHA testing are maximized when used as early as possible, current technology limits use in the pre-hospital setting and the time to results compromises its utility in the emergency department. Thus, most of the reported experience with VHA in trauma is in the operating room and intensive care unit, where there is compelling data to support its value. This overview will address the current and potential role of VHA in the seriously injured patient, throughout the continuum of trauma management.
Single versus Three Doses of Intraarticular Platelet-Rich Plasma Injection in Treatment of Early Osteoarthritis Knee Joint—A Prospective Comparative Study
Authors: Varma Hashmukh Shantilal , Lodhi Jeetendra Singh , Vidyarthi Ashok , Jayaprakasan Vishnu
Published: September 2022

Background

Autologous platelet-rich plasma (PRP), which contains a pool of growth factors, appears to offer an easy solution for delivering multiple growth factors needed for tissue repair. The objective of the study is to compare between single versus three doses of intraarticular platelet-rich plasma injection in the treatment of early osteoarthritis knee joint.

Materials and Methods

A prospective comparative study was done on 100 patients with early osteoarthritis knee who were randomized into two groups in an alternating fashion—single-dose injection and triple-dose injection groups. PRP (5 mL) obtained by double-spin method was injected per knee and followed up at 1, 3, and 6 months and outcomes measured using WOMAC (Western Ontario and McMaster universities osteoarthritis index) and VAS (visual analog scale) scores.

Results

VAS scores showed a statistically significant difference in triple-dose group at all follow-ups. In WOMAC, such a difference was observed for stiffness subscore at all the follow-ups, but the pain subscore and total score showed an improvement only at the final follow-up with the functional assessment subscore showing no statistical difference at any follow-ups.

Conclusion

PRP injection appears to be effective in early symptomatic osteoarthritis with better clinical results using a triple-dose regimen.
Reliable change in parent-rated scores on the Brown Attention-Deficit Disorder Scales® from pre- to post-participation in the Brain Balance® program
Authors: Jackson Rebecca , Jordan Joshua T.
Published: September 2022

The development of attention can be influenced through various nonpharmacologic approaches such as training and practice. More research is needed on these approaches in children and adolescents with attentional difficulties. To this end, we investigated the effect of 3 months of participation in the Brain Balance® (BB) program (a multimodal childhood training program) on attentional issues in children and adolescents, using the Brown Attention-Deficit Disorder Scales® (BADDS) administered as a parental questionnaire before and after program participation. At baseline, participants (N = 71; aged 4–18 years; 69% male) had BADDS scores that were approximately 1.5 standard deviations above the normative BADDS sample. A Wilcoxon test indicated that scores differed significantly from pre- to post-program, with an average decline of 7 T-score points. The probability of a BB participant improving from pre- to post-program was 81%. The Reliable Change Index (RCI) indicated that 36 participants (49.3%) observed a large enough change to meet the criteria for reliable change, 34 participants (46.6%) did not meet the criteria for reliable change, and three participants (4.1%) observed reliable deterioration. Finally, logistic regression showed that baseline BADDS scores significantly predicted reliable change, such that a one-unit increase in baseline BADDS T-score was associated with a 15% odds increase in reliable change. This suggests that children with more severe ADHD symptoms at baseline are more likely to observe a decrease in symptoms over the course of the BB program than are children with less severe symptoms. Age (but not gender) was also a significant predictor, such that younger participants were more likely to observe reliable change. These data provide evidence of statistically significant reliable change in attentional functioning in BB participants from pre- to post-program, especially for participants who are younger in age or have more pronounced attentional issues at baseline.
s- and p-superfluidity of Fermi atoms in Bose–Fermi mixtures
Authors: Gorbar E. V. , Nikolaieva Y. O. , Oleinikova I. V. , Vilchinskii S. I. , Yakimenko A. I.
Published: September 2022

The p-wave superfluid is characterized by nontrivial topological characteristics essential for fault-tolerant quantum state manipulation. However, the practical realization of the p-wave state remains a challenging problem. We study the s- and p-wave superfluidity in mixtures of fermionic and spinor bosonic gases and derive a general set of the gap equations for these superfluid states. Numerically solving the gap equations for the s-wave state, we quantify the physical conditions for the realization of the pure p-wave state in a well-controlled environment of atomic physics in the absence of an admixture of the s-wave state.
Development of a technology for manufacturing a heat-shielding structure on nitrogen cryocontainers, excluding heat transfer through gas
Authors: Zhun H. H. , Starikov V. V. , Koverya V. P.
Published: September 2022

One of the important stages in the creation of the scientific and technical foundations for the calculation, design and manufacturing technology of the lowest heat-conductivity thermal protection from screen-vacuum thermal insulation (SVTI) is the development of a process for achieving the optimal vacuum P0 ≤ 10−3 Pa in the SVTI layers, since at this pressure, thermal conductivity (λeff) through the SVTI is carried out only due to the radiant (λrad) and contact-conductive (λk,k) components. It is proposed to obtain such a pressure in thermal insulation by using cushioning material in it, which was previously degassed in a separate vacuum chamber at 370−380 K for 12 h in order to remove water molecules from its structure and then replace them with nitrogen molecules. These molecules have 3−4 times less heat of adsorption; therefore they are pumped out faster. As a result, it becomes possible to accelerate (by ∼20 h) to achieve optimal vacuum in thermal insulation, as well as 11% lower effective thermal conductivity [equal to (14.1−14.3)⋅10−5 W/(m⋅K)]. The analysis carried out (according to the developed methodology) showed that the achieved optimal effective thermal conductivity of thermal insulation in a cryocontainers is determined by 33% of radiant thermal conductivity [4.7⋅10−5 W/(m⋅K)] and 67% of the contact-conductive component [9.4⋅10−5 W/(m⋅K)].
Integrating revolutionary sensor technology with Magneto-optic Kerr effect microscopy
Authors: Ikenson Ben
Published: September 2022

New “add-on” mimics human eye, elevates traditional microscopy technology.
Comparison of multi-task approaches on molecular property prediction
Authors: Han Chao , Wang Hao , Zhu Jianbao , Liu Qi , Zhu Wenguang
Published: September 2022

With the bloom of deep learning algorithms, various models have been widely utilized in quantum chemistry calculation to design new molecules and explore molecular properties. However, limited studies focus on multi-task molecular property prediction, which offers more efficient ways to simultaneously learn different but related properties by leveraging the inter-task relationship. In this work, we apply the hard parameter sharing framework and advanced loss weighting methods to multi-task molecular property prediction. Based on the performance comparison between single-task baseline and multi-task models on several task sets, we find that the prediction accuracy largely depends on the inter-task relationship, and hard parameter sharing improves the performance when the correlation becomes complex. In addition, we show that proper loss weighting methods help achieve more balanced multi-task optimization and enhance the prediction accuracy. Our additional experiments on varying amount of training data further validate the multi-task advantages and show that multi-task models with proper loss weighting methods can achieve more accurate prediction of molecular properties with much less computational cost.
Be2H3L2− (L=CH3 and F–I): Hyperhalogen anions with ultrashort beryllium-beryllium distances
Authors: Zhao Xuefeng , Jin Bo , Zhou Chengyong , Yuan Caixia , Wu Yanbo
Published: September 2022

The superalkali cations and superhalogen anions commonly have different type of core moieties. Based on the previous reports that Be2H3L′2+ (L′=NH3 and noble gases Ne–Xe) are superalkali cations, in the present work, we designed the superhalogen anions Be2H3L2− (L=CH3 and halogens F–I), and both superalkali cations and superhalgen anions can be constructed using Be2H3 as the core moiety. The newly designed Be2H3L2− species are much more stable than their isoelectronic cationic counterparts Be2H3L′2+, as can be reflected by the highly exergonic substitution reaction of L′ ligand in Be2H3L′2+ with isoelectronic L− to give Be2H3L2−. These anionic species possess the well-defined electronic structure, which can be proven by their large HO-MO–LUMO gaps of 4.69 eV to 5.38 eV. It is remarkable that Be2H3L2− can be regarded as the hyperhalogen anions due to the extremely high vertical detachment energies (5.38 eV to 6.06 eV) and the Be–Be distances in these species (1.776 Å to 1.826 Å) are short in ultrashort metal-metal distances (defined as dM–M<1.900 Å) between main group metals. In the designed five small model species, three of them, i.e. Be2H3L2− (L=CH3, Cl, and Br), are kinetical viable global energy minima, which are the promising target for generation and characterization in anion photoelectron spectroscopy. The analogue molecule [t-Bu–Be2H3–t-Bu]− with bulky protecting tert-butyl (t-Bu) groups is designed as a possible target for synthesis and isolation in condensed states.
Molecular dynamics simulation of typical molecular ferroelectrics based on polarized crystal charge model
Authors: Wang Ruining , Xu Feng , Gui Xiongfei , Li Yongle
Published: September 2022

Molecular ferroelectrics are a promising class of ferro-electrics, with environmental friendliness, flexibility and low cost. In this work, a set of characteristic molecular ferroelectrics are simulated by molecular dynamics (MD) with polarized crystal charge (PCC). From the simulated results, their ferroelectric switching mechanisms are elucidated, with their ferroelectric hysteresis loops. The PCC charge model, recently developed by our group, containing the quantum electric polarization effect, is suitable in nature for studying molecular ferroelectrics. The simulated systems include the typical molecular ionic ferroelectrics, di-isopropyl-ammonium halide (DIPAX, X=C (Cl), B (Br), and I), as well as a pair of newly validated organic molecular ferroelectrics, salicylideneaniline and (-)-camphanic acid. In total, there are five systems under investigation. Results demonstrate that the PCC MD method is efficient and reliable. It not only elucidates the ferroelectric switching mechanism of the studied molecular ferroelectrics, but also extends the application range of the PCC MD. In conclusion, PCC MD provides an efficient protocol for extensive computer simulations of molecular ferroelectrics, with reliable ferroelectric properties and associated mechanisms, and would promote further exploration of novel molecular ferroelectrics.
Fe-Ni co-doping strategy in perovskite for developing an efficient oxygen evolution electrocatalyst
Authors: Liu Huimin , Wei Lianwei , Zheng Hui , Tang Kaibin
Published: September 2022

The high reaction barrier of the oxygen evolution reaction (OER) has always been the bottleneck of the water decomposition reaction, so low-cost, high-performance and stable catalysts are urgently needed currently. Herein, we designed an effective OER electrocatalyst BaCo0.6Fe0.2Ni0.2O3−δ (BCFN) by a codoping strategy. The overpotential of BCFN at a current density of 10 mA/cm2 reaches 310 mV, and possesses a Tafel slope of 50.2 mV/dec. The catalytic capability of BCFN is much stronger than that of Fe-doped BaCo0.8Fe0.2O3−δ (360 mV), Ni-doped BaCo0.8Ni0.2O3−δ (375 mV), and benchmark IrO2 with excellent performance (329 mV). At the same time, BCFN is also a fairly stable alkaline OER catalyst. After 500-cycle scans, BCFN still shows high catalytic activity without significant decrease in catalytic performance. Electrochemical experiments show that BCFN has the fastest reaction kinetics and the lowest charge transfer resistance among the materials in this work. In addition, a large amount of highly oxidative oxygen O22−/O− and hydroxyl groups OH− on the surface of BCFN are conducive to the occurrence of OER, thereby increasing the reaction rate. This work provides a universal strategy to develop high-performance electrocatalysts for electrochemical energy conversion technology.
Thermoelectric properties of γ-graphyne and its derivatives: First-principles calculations
Authors: Sun Zijuan , Hu Jun
Published: September 2022

Two-dimensional thermoelectric materials is of special interest in recent years. Here, we studied the electronic and thermoelectric properties of two semiconducting carbon allotropes, γ-graphyne and its derivative, based on first-principles calculations. The small band gaps and long relaxation times of carriers benefit the thermal transport. We found that the thermoelectric efficiency in both materials is quite large, and reaches the maximum value around 900 K, with carrier concentration in the order of 1021 cm−3. Our research suggests that these two allotropes are promising candidates for the thermoelectric materials applications.
Identifying the spatiotemporal organization of high-traffic events in a mobile communication system using event synchronization and complex networks
Authors: Wang L. N. , Tan G. M. , Zang C. R.
Published: September 2022

In mobile communication systems, congestion is related to high-traffic events (HTEs) that occur in the coverage areas of base stations. Understanding, recognizing, and predicting these HTEs and researching their occurrence rules provides theoretical and decision-making support for preventing system congestion. Communication sectors are regarded as nodes, and if HTEs occur synchronously among sectors, then the corresponding nodes are connected. The total number of synchronous HTEs determines the edge weights. The mobile-communication spatiotemporal data are mapped to a weighted network, with the occurrence locations of HTEs as the basic elements. Network analysis provides a structure for representing the interaction of HTEs. By analyzing the topological features of the event synchronization network, the associations among the occurrence times of HTEs can be mined. We find that the event synchronization network is a small-world network, the cumulative strength distribution is exponential, and the edge weight obeys a power law. Moreover, the node clustering coefficient is negatively correlated with the node degree. A congestion coefficient based on several topological parameters is proposed, and the system congestion is visualized. The congestion coefficient contains information about the synchronous occurrence of HTEs between a sector and its neighbors and information about the synchronous occurrence of HTEs among its neighbors. For the mobile communication system considered in this study, the congestion coefficient of a large number of sectors is small and the risk of system congestion is low.
Stability result for the surface quasi-geostropic equations with horizontal dissipation in anisotropic Sobolev space
Authors: Jin Hong Sung , Kwak Minkyu , Lkhagvasuren Bataa
Published: September 2022

The stability of smooth solutions of an anisotropic surface quasi-geostrophic equation with horizontal dissipation remains an open problem. In this work, we present a partial answer to this problem in a rougher function space. More precisely, if the initial data θ0 belong to anisotropic Sobolev space H0,s with 12<s<1, then there exists a global small solution, provided that the initial data are small in H0,s. The stability problem in the space H0,1 or more regular spaces remains open. The main tools used are the Littlewood–Paley theory and standard techniques.
Riemann–Hilbert approach to two-component modified short-pulse system and its nonlocal reductions
Authors: Lv Cong , Qiu Deqin , Liu Q. P.
Published: September 2022

In this paper, a Riemann–Hilbert approach to a two-component modified short-pulse (mSP) system on the line with zero boundary conditions is developed. A parametric representation of the solution to the related Cauchy problem is obtained. Four nonlocal integrable reductions, namely, the real reverse space-time nonlocal focusing and defocusing mSP equations and the complex reverse space-time nonlocal focusing and defocusing mSP equations, are studied in detail. For each case, soliton solutions are presented, and, unlike their local counterparts, the nonlocal equations exhibit certain novel properties induced by the impact of nonlocality.
Tin removal by an annular surface wave plasma antenna in an extreme ultraviolet lithography source
Authors: Qerimi Dren , Herschberg Andrew C. , Panici Gianluca , Hays Parker , Pohlman Tyler , Ruzic David N.
Published: September 2022

Tin contamination of the collector mirror surface remains one of the crucial issues of EUV (Extreme Ultraviolet) sources, directly impacting the availability of the tool. Hydrogen plasma-based tin removal processes employ hydrogen radicals and ions to interact with tin deposits to form gaseous tin hydride (SnH4), which can be removed through pumping. An annular surface wave plasma (SWP) source developed at the University of Illinois—Urbana Champaign is integrated into the cone and perimeter of the collection mirror for in situ tin removal. The SWP is characterized by high ion and radical densities, low electron temperature, and local generation where etching is needed. This method has the potential to significantly reduce downtime and increase mirror lifetime. Radical probe measurements show hydrogen radical densities in the order of 1019 m−3, while Langmuir probe measurements show electron temperatures of up to 6 eV and plasma densities on the order of 1017–18 m−3. The generated ions are essential to the tin cleaning and have sufficiently low energy to cause no damage to the collector capping layer. Tin etch rates of up to 270 nm/min were observed in a variety of experimental conditions, including various powers, pressures, flowrates, and temperatures. The high etch rates demonstrated in this study exceed the expected contamination rate of the EUV source.
Enhanced analysis of experimental x-ray spectra through deep learning
Authors: Mariscal D. A. , Krauland C. M. , Djordjević B. Z. , Scott G. G. , Simpson R. A. , Grace E. S. , Swanson K. , Ma T.
Published: September 2022

X-ray spectroscopic data from high-energy-density laser-produced plasmas has long required thorough, time-consuming analysis to extract meaningful source conditions. There are often confounding factors due to rapidly evolving states and finite spatial gradients (e.g., the existence of multi-temperature, multi-density, multi-ionization states, etc.) that make spectral measurements and analysis difficult. Here, we demonstrate how deep learning can be applied to enhance x-ray spectral data analysis in both speed and intricacy. Neural networks (NNs) are trained on ensemble atomic physics simulations so that they can subsequently construct a model capable of extracting plasma parameters directly from experimental spectra. Through deep learning, the models can extract temperature distributions as opposed to single or dual temperature/density fits from standard trial-and-error atomic modeling at a significantly reduced computational cost compared to traditional trial-and-error methods. These NNs are envisioned to be deployed with high repetition rate x-ray spectrometers in order to provide detailed real-time analysis of experimental spectra.
High-density racetrack memory based on magnetic skyrmion bags controlled by voltage gates
Authors: Zhang Zhiyu , Xu Min , Jiang Guiqian , Zhang Jinyu , Meng Dexiang , Chen Wenlong , Chen Yuliang , Hu Changjing
Published: September 2022

Skyrmion bags are spin structures with arbitrary topological degrees. They are expected to be promising next-generation information carriers due to their inherent high topological degrees. Here, we report the dynamics of the topological transition process when a skyrmion bag passes through a voltage gate driven by spin current in a synthetic antiferromagnetic racetrack with voltage-controlled magnetic anisotropy. The topological degrees of skyrmion bags controlled by voltage gate and driving current density are investigated. It is found that the different topological degrees of skyrmion bags transformed in this process are related to the interaction between antiskyrmions inside skyrmion bags, and the energy of each inner antiskyrmion after topological transformation is on the order of $10^{{-}19}\;J$. Furthermore, we have realized the successive transition of a skyrmion bag from a high topological degree to a low topological degree on a racetrack with three voltage gates. This work is helpful for designing high-density racetrack memory and logical devices based on skyrmion bags.
A knock-on deuteron imager for measurements of fuel and hotspot asymmetry in direct-drive inertial confinement fusion implosions (invited)
Authors: Rinderknecht H. G. , Heuer P. V. , Kunimune J. , Adrian P. J. , Knauer J. P. , Theobald W. , Fairbanks R. , Brannon B. , Ceurvorst L. , Gopalaswamy V. , Williams C. A. , Radha P. B. , Regan S. P. , Johnson M. Gatu , Séguin F. H. , Frenje J. A.
Published: September 2022

A knock-on deuteron imager (KoDI) has been implemented to measure the fuel and hotspot asymmetry of cryogenic inertial confinement fusion implosions on OMEGA. Energetic neutrons produced by D–T fusion elastically scatter (“knock on”) deuterons from the fuel layer with a probability that depends on ρR. Deuterons above 10 MeV are produced by near-forward scattering, and imaging them is equivalent to time-integrated neutron imaging of the hotspot. Deuterons below 6 MeV are produced by a combination of side scattering and ranging in the fuel, and encode information about the spatial distribution of the dense fuel. The KoDI instrument consists of a multi-penumbral aperture positioned 10–20 cm from the implosion using a ten-inch manipulator and a detector pack at 350 cm from the implosion to record penumbral images with magnification of up to 35×. Range filters and the intrinsic properties of CR-39 are used to distinguish different charged-particle images by energy along the same line of sight. Image plates fielded behind the CR-39 record a 10 keV x-ray image using the same aperture. A maximum-likelihood reconstruction algorithm has been implemented to infer the source from the projected penumbral images. The effects of scattering and aperture charging on the instrument point-spread function are assessed. Synthetic data are used to validate the reconstruction algorithm and assess an appropriate termination criterion. Significant aperture charging has been observed in the initial experimental dataset, and increases with aperture distance from the implosion, consistent with a simple model of charging by laser-driven EMP.
Benchmarking of spin–orbit torque vs spin-transfer torque devices
Authors: Kumar Piyush , Naeemi Azad
Published: September 2022

We present a comprehensive benchmarking for spin-transfer torque (STT) and spin–orbit torque (SOT) based random-access memories. Based on experimentally validated micromagnetic simulations along with the use of rare event enhancement techniques, we show various tradeoffs among the write error rate, write time, and write current. We consider both in-plane and perpendicular devices. For SOT driven perpendicular devices, we include various write mechanisms, such as field-assisted, STT-assisted, and switching due to out-of-plane spin torque, usually present in low symmetry materials.
Scaled σ-functionals for the Kohn–Sham correlation energy with scaling functions from the homogeneous electron gas
Authors: Erhard Jannis , Fauser Steffen , Trushin Egor , Görling Andreas
Published: September 2022

The recently introduced σ-functionals constitute a new type of functionals for the Kohn–Sham (KS) correlation energy. σ-Functionals are based on the adiabatic-connection fluctuation–dissipation theorem, are computationally closely related to the well-known direct random phase approximation (dRPA), and are formally rooted in many-body perturbation theory along the adiabatic connection. In σ-functionals, the function of the eigenvalues σ of the Kohn–Sham response matrix that enters the coupling constant and frequency integration in the dRPA is replaced by another function optimized with the help of reference sets of atomization, reaction, transition state, and non-covalent interaction energies. σ-Functionals are highly accurate and yield chemical accuracy of 1 kcal/mol in reaction or transition state energies, in main group chemistry. A shortcoming of σ-functionals is their inability to accurately describe processes involving a change of the electron number, such as ionizations or electron attachments. This problem is attributed to unphysical self-interactions caused by the neglect of the exchange kernel in the dRPA and σ-functionals. Here, we tackle this problem by introducing a frequency- and σ-dependent scaling of the eigenvalues σ of the KS response function that models the effect of the exchange kernel. The scaling factors are determined with the help of the homogeneous electron gas. The resulting scaled σ-functionals retain the accuracy of their unscaled parent functionals but in addition yield very accurate ionization potentials and electron affinities. Moreover, atomization and total energies are found to be exceptionally accurate. Scaled σ-functionals are computationally highly efficient like their unscaled counterparts.
Development of a soft x-ray (SXR) array diagnostic system on versatile experiment spherical torus (VEST)
Authors: Jang Jae Young , Lim Soobin , Kim Seongcheol , Lee M. W. , Kim Young-Gi , Sung C. , Hwang Y. S.
Published: September 2022

A new soft x-ray (SXR) array diagnostic system has been developed on versatile experiment spherical torus (VEST) for measurements of 2D SXR emissivity profile and identification of poloidal mode structure. Through tomographic inversion techniques, 2D SXR emissivity profile can be acquired from the line-integrated SXR data, which enables the visualization of mode structure of plasma instability, such as the magnetohydrodynamics mode. The SXR array diagnostic system consists of two 20-channel arrays positioned at the middle and the top on the same poloidal plane for horizontal and vertical lines of sight, respectively. Each array of the diagnostic system uses absolute extreme ultraviolet photodiode array as the detector. To apply appropriate filters (up to four) for different energy regimes without breaking the vacuum, a filter wheel and its rotatable vacuum feed-through are installed behind the pinhole. SXR data are acquired with a digitizer at the sampling rate of up to 125 MHz. Finally, we discuss initial measurement data obtained from Ohmic plasma in VEST.
Spatiotemporal-scale neutron studies on lithium-ion batteries and beyond
Authors: Zhao Enyue , Wang Howard , Yin Wen , He Lunhua , Ke Yubin , Wang Fangwei , Zhao Jinkui
Published: September 2022

Lithium-ion batteries (LIBs) are remarkable electrochemical energy storage systems, which play a critical role in modern society. Demanding new applications have been pushing for further battery advancements, such as developments of all-solid-state and sodium-ion batteries. However, both the LIBs and these new technologies still face challenges that limit their full realization. These include irreversible electrochemical reactions, electrode structure degradations, and surface/interface side reactions. Solving them requires comprehensive characterizations of battery systems over multiple length and time scales. Among the advanced probing techniques, neutron-based ones have unique advantages in exploring battery material structures, ionic diffusions, electrochemical reactions, and cell failure mechanisms, information that will aid the development of next-generation high-performance battery systems. In this Perspective, we briefly review the principles and characteristics of various neutron techniques and their recent applications in battery system studies. Operando neutron characterizations of batteries on spatiotemporal scales and prospects of their future designs and applications are discussed.
A machine learning approach to nonlinear ultrasonics for classifying annealing conditions in austenitic stainless steel
Authors: Abraham Saju T. , Mohan Manju , Chelliah Pandian , Balasubramaniam Krishnan , Venkatraman B
Published: September 2022

This paper explores the feasibility of machine learning algorithms on nonlinear ultrasonics for classification of the austenitic stainless-steel material subjected to different annealing conditions. The material that is isothermally annealed at 1323 K for different soaking times showed a marginal variation in its nonlinearity parameter at larger mean grain sizes. The grain growth during annealing followed the Arrhenius type equation fairly well, which has been verified using a genetic algorithm approach. The machine learning algorithms are trained using features such as the ratio of the harmonic amplitudes, root-mean-square value, and the phase difference between the fundamental and second harmonic components derived from the nonlinear ultrasonic response. Upon evaluating the performance of decision tree and ensemble learning algorithms in the classification of annealed materials, it was observed that the LPBoost classifier has the highest accuracy of 97%. According to the results, it is concluded that a machine learning strategy based on a minimal number of features can effectively classify specimens that are otherwise indistinguishable in their nonlinear response. This research takes a step forward to the automation of non-destructive testing toward Industrial Revolution 4.0. The results also pointed out the necessity of parameter fusion in non-destructive decision making.
Generation of collimated vortex gamma-rays from intense Poincaré beam–plasma interaction
Authors: Younis D. , Hafizi B. , Gordon D. F.
Published: September 2022

We report on numerical calculations in which a multi-petawatt γ-ray beam is generated using a novel configuration based on fully structured light irradiating an overdense plasma waveguide. We analyze how the relativistic laser pulse efficiently confines and accelerates plasma electrons to GeV-scale energies and drives a quasi-static field that induces magneto-bremsstrahlung radiation. Multiphoton Compton scattering of electrons in the intense part of the laser also occurs although the radiated energy-density is comparatively lower. The emitted γ-rays carry orbital angular momentum, are highly collimated, and account for upwards of 15% of the incident field energy in one particular case. A comparison of the laser-to-particle angular momentum and energy transfer efficiencies is made between the cases of irradiation by a circularly polarized Laguerre–Gauss mode and one type of full Poincaré beam, and it is found that the latter yields an order-of-magnitude enhancement. The essential characteristics of the interaction are validated with three-dimensional particle-in-cell simulations that include quantum electrodynamical effects.
The effects of polarization on the rotational diffusion of ions in organic ionic plastic crystals
Authors: Park Seowoo , Park Hyungshick , Park Chung Bin , Sung Bong June
Published: September 2022

Organic ionic plastic crystals (OIPCs), which consist of organic molecular ions, are considered excellent candidates for solid electrolytes due to their high ionic conductivity in solid phases. Molecular ions undergo either rotational or conformational relaxation at certain temperatures in OIPCs. There have been molecular simulations to understand the rotational motion. The polarizability of ions was, however, often ignored in simulations due to the high computational cost. Since the polarizability may affect the translational diffusion, the ionic conductivity, and the phase transition of ionic liquids, it should be of interest to investigate how the polarizability would affect the rotational diffusion of ions in solid phases. In this work, we perform extensive atomistic molecular dynamics simulations for two different kinds of OIPCs, 1-methyl-3-methylimidazolium hexafluorophosphate ([MMIM][PF6]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6]). We employ various simulation models for ions by turning on and off the polarization in their interaction potentials. We find that the polarizability hardly affects the density, the crystalline structure, and the phase transition of both OIPCs. However, a certain rotational motion, especially the rotational diffusion of PF6− in [MMIM][PF6] OIPCs, is enhanced by a factor of up to four when the polarizability is turned on. The PF6− in [MMIM][PF6] OIPCs undergoes rotational hopping motions more significantly due to polarizability. We find that the rotational diffusion of a certain ion can be enhanced only when the polarization results in a significant change in the dipole moment of the neighboring ions around the ion.
Numerical analysis of floating wind turbines stability control strategy based on a novel tuned mass damper
Authors: Huang Zebo , Qian Ye , Wang Yuan , Mu Anle , Yang Bin , Wang Jiahui
Published: September 2022

Floating wind turbines (FWTs) are affected by wind, wave, and flow loads, and hence, their its stability is difficult to be guaranteed. The traditional tuned mass damper (TMD) damping effect increases with the increase in its mass ratio, but increasing the TMD mass will cause an instability of the structure. In this paper, to improve the damping performance of TMD, a novel negative stiffness tuned mass damper (TMD-NS) is proposed to reduce the amplitude ratio and increase the tuning bandwidth. The dimensionless optimal parameters of the dynamic damper are obtained by a fixed-point theory. The dynamic model of an FWT with TMD-NS added to the nacelle is established, and the surge response of the nacelle under the random wind action based on cut-in wind speed, rated wind speed, and cutout wind speed is analyzed. Numerical simulation results show that the maximum damping rates of TMD-NS to nacelle displacement, velocity, and acceleration are 55.87%, 48.18%, and 7.19%, respectively. The results show that TMD-NS is better than the traditional TMD in decreasing the amplitude ratio of the main structure and increasing the tuning bandwidth.
Oxygen vacancy-enriched ALD NiO sub-50 nm thin films for enhanced triethylamine detection
Authors: Pan Hongyin , Wang Chenyu , Zhang Zexu , Li Yingying , Hou Xinke , Zheng Wei , Liu Xianghong , Wan Yong , Zhang Jun
Published: September 2022

p-type metal oxide semiconductors have received significant interest in the field of gas sensors; however, it is quite challenging to achieve high sensor response because of inferior surface and electronic properties. Herein, we report a high-performance gas sensor fabricated by plasma-etching an NiO thin film deposited by atomic layer deposition. Ar plasma treatment is found to introduce a large number of oxygen vacancies, which effectively adjusts the electronic and chemical characteristics of the p-type NiO films to afford improved response to toxic triethylamine. The effects of the thickness of the sensing layer on sensor properties are also studied, which reveals that the NiO film with a thickness of 40 nm has the greatest gas sensing performance. After Ar plasma treatment, the response of the NiO thin films is significantly enhanced to enable an excellent limit of detection of 27.4 ppb, which is much lower than the threshold limit of 1 ppm proposed by American Conference of Governmental Industrial Hygienists. The demonstrated strategy and excellent sensor properties suggest a pathway to high performance gas sensors.
Linearly scaling computation of ddPCM solvation energy and forces using the fast multipole method
Authors: Mikhalev A. , Nottoli M. , Stamm B.
Published: September 2022

This paper proposes the first linear scaling implementation for the domain decomposition approach of the polarizable continuum model (ddPCM) for the computation of the solvation energy and forces. The ddPCM-equation consists of a (non-local) integral equation on the van der Waals or solvent accessible surface of the solute’s cavity resulting in a dense solution matrix, and, in turn, one matrix–vector multiplication has a quadratic arithmetic complexity with respect to the number of atoms of the solute molecule. The use of spherical harmonics as basis functions makes it natural to employ the fast multipole method (FMM) in order to provide an asymptotically linear scaling method. In this paper, we employ the FMM in a non-uniform manner with a clusterization based on a recursive inertial bisection. We present some numerical tests illustrating the accuracy and scaling of our implementation.
Detection of magnetohydrodynamic waves by using convolutional neural networks
Authors: Chen Fang , Samtaney Ravi
Published: September 2022

Nonlinear wave interactions in magnetohydrodynamics (MHD), such as shock refraction at an inclined density interface, lead to a plethora of wave patterns with numerous wave types. Identification of different types of MHD waves is an important and challenging task in such complex wave patterns. Moreover, owing to the multiplicity of solutions and their admissibility for different systems, especially for intermediate-type MHD shock waves, the identification of MHD wave types is complicated if one relies on the Rankine–Hugoniot jump conditions. MHD wave detection is further exacerbated by nonphysical smearing of discontinuous shock waves in numerical simulations. This paper proposes two MHD wave detection methods based on convolutional neural network to enable wave classification and identify their locations. The first method separates the output into regression (location prediction) and classification problems, assuming the number of waves for each training data is fixed. In contrast, the second method does not specify the number of waves a priori, and the algorithm predicts wave locations and classifies types using only regression. We use one-dimensional input data (density, velocity, and magnetic fields) to train the two models that successfully reproduce a complex two-dimensional MHD shock refraction structure. The first fixed output model efficiently provides high precision and recall, achieving total neural network accuracy up to 99%, and the classification accuracy of some waves approaches unity. The second detection model has relatively low performance, with more sensitivity to the setting of parameters, such as the number of grid cells Ngrid and the thresholds of confidence score and class probability, etc. The detection model achieves better than 90% accuracy with F1 score >0.95. The proposed two methods demonstrate very strong potential for MHD wave detection in complex wave structures and interactions.
Patched patterns and emergence of chaotic interfaces in arrays of nonlocally coupled excitable systems
Authors: Franović Igor , Eydam Sebastian
Published: September 2022

We disclose a new class of patterns, called patched patterns, in arrays of non-locally coupled excitable units with attractive and repulsive interactions. The self-organization process involves the formation of two types of patches, majority and minority ones, characterized by uniform average spiking frequencies. Patched patterns may be temporally periodic, quasiperiodic, or chaotic, whereby chaotic patterns may further develop interfaces comprised of units with average frequencies in between those of majority and minority patches. Using chaos and bifurcation theory, we demonstrate that chaos typically emerges via a torus breakup and identify the secondary bifurcation that gives rise to chaotic interfaces. It is shown that the maximal Lyapunov exponent of chaotic patched patterns does not decay, but rather converges to a finite value with system size. Patched patterns with a smaller wavenumber may exhibit diffusive motion of chaotic interfaces, similar to that of the incoherent part of chimeras.