bluuebunny/crossref_metadata_2025 huggingface dataset:
High-pressure minerals and new lunar mineral changesite-(Y) in Chang’e-5 regolith
Authors: Yang Jing , Du Wei
Published: February 2024

Forty-five years after the Apollo and Luna missions, China’s Chang’e-5 (CE-5) mission collected ∼1.73 kg of new lunar materials from one of the youngest basalt units on the Moon. The CE-5 lunar samples provide opportunities to address some key scientific questions related to the Moon, including the discovery of high-pressure silica polymorphs (seifertite and stishovite) and a new lunar mineral, changesite-(Y). Seifertite was found to be coexist with stishovite in a silica fragment from CE-5 lunar regolith. This is the first confirmed seifertite in returned lunar samples. Seifertite has two space group symmetries (Pnc2 and Pbcn) and formed from an α-cristobalite-like phase during “cold” compression during a shock event. The aftershock heating process changes some seifertite to stishovite. Thus, this silica fragment records different stages of an impact process, and the peak shock pressure is estimated to be ∼11 to 40 GPa, which is much lower than the pressure condition for coexistence of seifertite and stishovite on the phase diagram. Changesite-(Y), with ideal formula (Ca8Y)□Fe2+(PO4)7 (where □ denotes a vacancy) is the first new lunar mineral to be discovered in CE-5 regolith samples. This newly identified phosphate mineral is in the form of columnar crystals and was found in CE-5 basalt fragments. It contains high concentrations of Y and rare earth elements (REE), reaching up to ∼14 wt. % (Y,REE)2O3. The occurrence of changesite-(Y) marks the late-stage fractional crystallization processes of CE-5 basalts combined with silicate liquid immiscibility. These new findings demonstrate the significance of studies on high-pressure minerals in lunar materials and the special nature of lunar magmatic evolution.
Macromolecular crowding in chiral assembly of ellipsoidal nanoparticles
Authors: Hou Jiaxin , Sampson William , Dumanli Ahu Gümrah
Published: February 2024

Anisotropic colloidal particles have the ability to self-assemble into cholesteric structures. We used molecular dynamics to simulate the self-assembly of ellipsoidal particles with the objective to establish a general framework to reveal the primary factors driving chiral interactions. To characterize these interactions, we introduce a characteristic parameter following the crowding factor (CF) theory. Our simulations and statistical analysis showed good agreement with the CF theory; at the early stages of the assembly process, the ellipsoidal particles go through a critical aggregation point followed by further clustering toward nematic order. Furthermore, we demonstrate that under high CF conditions, small initial clusters may induce a chiral twist, which subsequently forms a cholesteric structure with no directional preference in higher organization states.
Completeness of atomic structure representations
Authors: Nigam Jigyasa , Pozdnyakov Sergey N. , Huguenin-Dumittan Kevin K. , Ceriotti Michele
Published: February 2024

In this paper, we address the challenge of obtaining a comprehensive and symmetric representation of point particle groups, such as atoms in a molecule, which is crucial in physics and theoretical chemistry. The problem has become even more important with the widespread adoption of machine-learning techniques in science, as it underpins the capacity of models to accurately reproduce physical relationships while being consistent with fundamental symmetries and conservation laws. However, some of the descriptors that are commonly used to represent point clouds— notably those based on discretized correlations of the neighbor density that power most of the existing ML models of matter at the atomic scale—are unable to distinguish between special arrangements of particles in three dimensions. This makes it impossible to machine learn their properties. Atom-density correlations are provably complete in the limit in which they simultaneously describe the mutual relationship between all atoms, which is impractical. We present a novel approach to construct descriptors of finite correlations based on the relative arrangement of particle triplets, which can be employed to create symmetry-adapted models with universal approximation capabilities, and have the resolution of the neighbor discretization as the sole convergence parameter. Our strategy is demonstrated on a class of atomic arrangements that are specifically built to defy a broad class of conventional symmetric descriptors, showing its potential for addressing their limitations.
Generalised unitary group integrals of Ingham-Siegel and Fisher-Hartwig type
Authors: Akemann Gernot , Aygün Noah , Würfel Tim R.
Published: February 2024

We generalise well-known integrals of Ingham-Siegel and Fisher-Hartwig type over the unitary group U(N) with respect to Haar measure, for finite N and including fixed external matrices. When depending only on the eigenvalues of the unitary matrix, such integrals can be related to a Toeplitz determinant with jump singularities. After introducing fixed deterministic matrices as external sources, the integrals can no longer be solved using Andréiéf’s integration formula. Resorting to the character expansion as put forward by Balantekin, we derive explicit determinantal formulae containing Kummer’s confluent and Gauß’ hypergeometric function. They depend only on the eigenvalues of the deterministic matrices and are analytic in the parameters of the jump singularities. Furthermore, unitary two-matrix integrals of the same type are proposed and solved in the same manner. When making part of the deterministic matrices random and integrating over them, we obtain similar formulae in terms of Pfaffian determinants. This is reminiscent to a unitary group integral found recently by Kanazawa and Kieburg [J. Phys. A: Math. Theor. 51(34), 345202 (2018)].
An ICEEMDAN-based collaborative optimization control for wind-hydrogen-electrochemical energy storage under multiple application scenarios
Authors: Han Xiaojuan , Guo Siqi , Zhang Zhewen
Published: February 2024

An improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN)-based collaborative optimization control strategy of wind-hydrogen-electrochemical energy storage coupled system with the interconversion characteristics between hydrogen with electricity under multiple application scenarios is introduced in this paper. After identifying the grid-connected wind power based on the ICEEMDAN algorithm, the normalized maximum discrepancy of the modal functions divides the high-frequency modal components into the fluctuating power smoothed by lithium iron phosphate batteries and hydrogen storage, with wind power curtailment from grid connection being consumed by electrolysis of water for hydrogen in alkaline electrolyzers. Another novelty is a collaborative optimization strategy for hydrogen-electrochemical energy storage under two application scenarios, comparing the smoothing effect and the ability to eliminate wind curtailment with different energy storage schemes. Demonstrate the method's effectiveness through the certain operational data from a Chinese wind farm. Simulation results indicate that the coupled system results in 19.45% and 7.79% cost reduction compared to other schemes, and the collaborative optimization control strategy achieves complete wind curtailment, which further improves the capacity of consuming curtailed wind power while smoothing fluctuations and providing certain engineering application value.
Facilitating excited-state plasmonics and photochemical reaction dynamics
Authors: Warren Natalie L. , Yunusa Umar , Singhal Arnav B. , Sprague-Klein Emily A.
Published: February 2024

Continuously advancing technologies is crucial to tackling modern challenges such as efficient energy transfer, directing catalytic behavior, and better understanding of microscopic phenomena. At the heart of many of these problems is nanoscale chemistry. In previous decades, the scientific community has made significant progress in nanoscale structures and technologies, especially relating to their interactions with light. Plasmonic nanostructures have been extensively studied over the past decades because of their fascinating properties and vast technological applications. They can confine light into intense local electromagnetic fields, which has been exploited in the fields of spectroscopy, energy harvesting, optoelectronics, chemical sensing, and biomedicine. Recently, however, plasmonic nanostructures have shown great potential to trigger chemical transformations of proximal molecular species via hot carrier and thermally driven processes. In this review, we discuss the basic concepts governing nanoscale light–matter interactions, the immediate phenomena induced by them, and how we can use nanoscale light–matter interactions to our advantage with surface-enhanced spectroscopy techniques and chemical reactions in confined plasmonic environments.
Optimization and control strategy for wind turbine aerodynamic performance under uncertainties
Authors: Tian Hongyan , Tang Zhihao , Ouyang Heng , Wang Rong , Wang Fang , Duan Shuyong
Published: February 2024

Aerodynamic performance of wind turbine governs the overall energy efficiency, which has been an ever-lasting research focus in the field of wind power technology. Due to the coupling effect among the highly complex environmental and structural uncertainties, the practical aerodynamic performance may not be reliably predicted. To aggravate, this performance declines with time in service. It is of great significance to efficiently and reliably assess the impact of uncertain factors and reduce these influences on wind turbine aerodynamic performance. This paper establishes an uncertainty analysis and robustness optimization model of wind turbine aerodynamic performance considering wind speed and pitch angle error uncertainties. An approach combined the no-instrusive probabilistic collocation method is used, and the blade element momentum theory is applied to quantify influences of variable uncertainties on NREL 5 MW wind turbine aerodynamic performance. The optimization target is to reduce the sensitivity of wind turbine aerodynamic performance to uncertainties, as well as maintain capture power. The results show that the wind turbine aerodynamic and mechanical performance will be greatly affected with uncertain factors. By optimizing and adjusting wind turbine rotor speed and blade pitch angle, the wind turbine rotor power and thrust load variation can be reduced to 9.14% and 9.36%, respectively, which indeed reduces the uncertainty effects.
Electrostatically formed nanowire (EFN) transistor—An ultrasensitive VOC and gas sensor
Authors: Mukherjee Anwesha , Shem Tov Idan , Rosenwaks Yossi
Published: February 2024

The perpetual need for high-performance volatile organic compound (VOC) sensors remains prevalent across diverse sectors including environmental health monitoring, industrial operations, and medical diagnostics. Within this context, the electrostatically formed nanowire (EFN) sensor, a silicon-on-insulator-based multiple-gate field-effect transistor, is an ultrasensitive and selective VOC and gas sensing platform. Unlike conventional silicon nanowires (also known for their superior sensitivity to chemical species), in EFN, the nanowire is defined electrostatically post-fabrication through appropriate biasing of the surrounding gates. The fabrication of the EFN leverages established CMOS compatible silicon processing technologies, facilitating the production of inexpensive, scalable, and robust sensors. By precisely controlling gate biases, a conductive channel with a tunable diameter is formed, allowing for the formation of nanowire with diameter below 20 nm. The adjustable size and shape of the nanowire offer tunable sensing parameters, including sensitivity, limit of detection, and dynamic range. The multiple parameters also yield a unique fingerprint for each VOC, thus enabling selective detection of VOCs. By simply altering the biasing configuration, a single EFN sensor can achieve high sensitivity and a broad dynamic range, which is limited in the case of physically defined silicon NW sensors. This review provides a comprehensive overview encompassing the EFN sensor's design, fabrication considerations, process flow, electrical characterization methods, sensing performances to VOCs, and gases at room temperature. Moreover, the scope of advanced sensor designs with array of EFN sensors and integrated heaters is also discussed. Finally, some future perspectives of this technology are presented.
Effect of junction temperature on 1.3 µm InAs/GaAs quantum dot lasers directly grown on silicon
Authors: Wang Shuai , Lv Zun-Ren , Wang Sheng-Lin , Yang Xiao-Guang , Yang Tao
Published: February 2024

Laser junction temperature (Tj) is an essential parameter that directly affects the light power and lifetime of semiconductor lasers. Here, we investigate the effect of Tj on an InAs/GaAs quantum dot (QD) laser grown on a Si(001) substrate. Under 1% low pulsed current (1 µs pulse width and 100 µs period), the pure temperature-induced mode shift rate is 0.084 nm/°C. By increasing the duty cycle and measuring the corresponding mode wavelength shift, the laser’s Tj under the continuous-wave (Tj-CW) mode is predicted to be from 31.1 to 81.6 °C when the injection current increases from 100 to 550 mA. Next, the average thermal resistance is 36.2 °C/W. Moreover, the non-negligible increase in Tj-CW is analyzed to significantly reduce the mean-time-to-failure of Si-based QD laser, especially for cases under high CW injection currents. These results provide an accurate reference for the thermal analysis of silicon-based QD lasers and point the way to high performance on-chip light sources by improving the laser heat accumulation.
Towards ultrathin metal-organic frameworks membranes for high-performance separation
Authors: Liu Qi , Chi Heng-Yu , Song Shuqing , Goswami Ranadip , Agrawal Kumar Varoon
Published: February 2024

Research on metal-organic frameworks (MOFs) based membranes has gained a lot of attention in the last decade thanks to the unique and highly versatile chemistry of MOFs, which allows one to synthesize a variety of structural dimensions, topologies, pore sizes, pore shapes, functional groups, and chemical environments. For membrane application, the field is rapidly progressing, with the focus shifting from the synthesis of pinhole-free polycrystalline films to the synthesis of ultrathin MOF films on scalable support to surpass the performance of polymeric membranes. In this research update, we review promising methodologies for the synthesis of ultrathin MOF membranes. We then discuss the application of these ultrathin MOF films in gas separation, ion transport and ion–ion separation, and desalination. We then provide our perspective on opportunities and challenges for the future development of ultrathin MOF membranes.
Hasimoto frames and the Gibbs measure of the periodic nonlinear Schrödinger equation
Authors: Blower Gordon , Khaleghi Azadeh , Kuchemann-Scales Moe
Published: February 2024

The paper interprets the cubic nonlinear Schrödinger equation as a Hamiltonian system with infinite dimensional phase space. There exists a Gibbs measure which is invariant under the flow associated with the canonical equations of motion. The logarithmic Sobolev and concentration of measure inequalities hold for the Gibbs measures, and here are extended to the k-point correlation function and distributions of related empirical measures. By Hasimoto’s theorem, the nonlinear Schrödinger equation gives a Lax pair of coupled ordinary differential equations for which the solutions give a system of moving frames. The paper studies the evolution of the measure induced on the moving frames by the Gibbs measure; the results are illustrated by numerical simulations. The paper contains quantitative estimates with well-controlled constants on the rate of convergence of the empirical distribution in Wasserstein metric.
Active oscillatory associative memory
Authors: Du Matthew , Behera Agnish Kumar , Vaikuntanathan Suriyanarayanan
Published: February 2024

Traditionally, physical models of associative memory assume conditions of equilibrium. Here, we consider a prototypical oscillator model of associative memory and study how active noise sources that drive the system out of equilibrium, as well as nonlinearities in the interactions between the oscillators, affect the associative memory properties of the system. Our simulations show that pattern retrieval under active noise is more robust to the number of learned patterns and noise intensity than under passive noise. To understand this phenomenon, we analytically derive an effective energy correction due to the temporal correlations of active noise in the limit of short correlation decay time. We find that active noise deepens the energy wells corresponding to the patterns by strengthening the oscillator couplings, where the more nonlinear interactions are preferentially enhanced. Using replica theory, we demonstrate qualitative agreement between this effective picture and the retrieval simulations. Our work suggests that the nonlinearity in the oscillator couplings can improve memory under nonequilibrium conditions.
On the upscaling of the diffusion equation in a heterogeneous medium by the two different methods
Authors: Shapiro Alexander A.
Published: February 2024

Upscaling the flow equations appears in many studies related to diffusion, heat conductivity, and flows in porous media. Variable coefficients of the original fine-scale process description are substituted by averaged constant values. The different upscaling procedures have been suggested in the literature. The question arises, whether they result in the same or different upscaled models; moreover, whether the solutions of the coarse-scale equations provide a reasonably accurate description of the fine scale. In this work, we consider three sample 1D diffusion problems with periodic coefficients: diffusion with or without the external source, as well as diffusion with advection. These problems are upscaled by the two methods. The method of direct upscaling selects the averaged coefficients to provide the minimum difference between the solutions of the coarse-scale and fine-scale models. The method of continuous upscaling, developed previously, consists of the continuous averaging transformation between the distant scales. New expressions for the upscaled diffusion coefficients were derived for this case. It turns out that the direct upscaling results in multiple optimum parameters of the upscaled model. Meanwhile, continuous upscaling points at one of them. The coarse-scale approximation of a fine-scale solution may be unsatisfactory, even for the best choice of the upscaled coefficient. A numerical study demonstrates a nontrivial behavior of the diffusion coefficient under continuous upscaling, while it converges to an asymptotic value.
Laser-enabled dual-state transformation on PANI:PSS/Si for wavelength-selective detection
Authors: Xu Kun , Su Nan , Liu Shuai , Hu Su , Xie Nandi , Wang Hui
Published: February 2024

Position-sensitive detectors are widely used in industry due to accurate sensing of changes in light position. The introduction of additional wavelength selectors can cause deviations in light position and affect the performance of the devices. In this work, an organic–inorganic heterojunction of polyaniline-poly (p-styrenesulfonic acid) (PANI:PSS)/p-Si is proposed to achieve selective detection at optical wavelengths using the lateral photovoltaic effect. The maximum reduction of sensitivity in the detection of 405 nm laser can reach up to 127.59 mV/mm, with a decrease in about 99%. When the device is exposed to blue-violet light, the absorption layer changes from a Si layer to a PANI:PSS layer, which weakens the photon utilization efficiency and charges carrier transport. The self-generated longitudinal voltage further enhances the absorption of the PANI:PSS layer for blue-violet light. PANI absorbs photon energy to generate electron–hole pairs and transitions from the reduced state to the oxidized state in the depletion region at the contact interface. The oxide layer hinders carrier separation and increases carrier recombination. Due to the inherent properties of the structure, the wavelength selection function is realized by the detector itself, enriching its original single function. The sensitivity in other light bands has been improved, including more than three times at 520 nm compared to p-Si. These results have provided the theoretical foundation for highly selective and tunable optoelectronic devices while helping to overcome the challenges of high manufacturing costs and customized application scenarios. They provide a viable solution for the intelligent development of optoelectronic devices.
A brief review of integrated tempering sampling molecular simulation
Authors: Han Xu , Lei Yao-Kun , Li Maodong , Gao Yi Qin
Published: February 2024

With the fast development of computation techniques, molecular dynamics (MD) simulations are becoming increasingly important in molecular studies. Numerous enhanced sampling methods were proposed to further increase the applicability of MD simulation to complex systems of slow dynamics. In this review, we briefly review some of these methods concerned with integrated enhanced sampling (ITS), which introduces an effective potential energy expressed as an integral of Boltzmann distributions over a range of temperatures. We, in particular, focus on ITS and its derived methods, such as selected ITS and the combination of ITS with other enhanced sampling methods, especially metadynamics (MetaITS). These methods show great sampling efficiency, and the hybrid methods represent a future direction of enhanced sampling. Applications of these methods, including but not limited to protein folding, phase transition, and chemical reactions, will be summarized. At the end of this review, we briefly introduce a number of other methods related to ITS, including partitioned ITS, integrated Hamiltonian sampling, integrated accelerated molecule dynamics, and infinite switch simulated tempering.
Non-Bayesian and Bayesian estimation for Lomax distribution under randomly censored with application
Authors: Hasaballah Mustafa M. , Balogun Oluwafemi Samson , Bakr M. E.
Published: February 2024

This paper centers on the examination of the Lomax distribution in the context of randomly censored data. Our primary objectives include deriving maximum likelihood estimators and constructing confidence intervals based on the Fisher information matrix for the unknown parameters in the context of randomly censored data. Furthermore, we develop Bayes estimators utilizing gamma priors, considering both squared error and general entropy loss functions. We also calculate Bayesian credible intervals for the parameters. To offer practical insights, we apply these methods to a real-world dataset subject to random censorship. Finally, for comparative purposes, we conduct a Monte Carlo simulation to assess the various estimation techniques introduced in this study.
Charge trapping-induced current–voltage hysteresis in a squaraine nanowire mesh enables synaptic memristive functionality
Authors: Griffin Karl , Redmond Gareth
Published: February 2024

Nanowires (NWs) composed of 2,4-bis[(4-diethylamino)-2-hydroxyphenyl] squaraine were prepared by evaporation-induced self-assembly (EISA). NWs were ∼560 nm wide (aspect ratios: 10–90). X-ray diffraction analysis indicated polymorphism (monoclinic/triclinic). Optical data reported the triclinic phase with energetic disorder. Given the favorable alignment of the Au work function and squaraine HOMO energy, symmetric, unipolar metal–insulator–metal devices were formed by the EISA of NW meshes on inter-digitated Au electrodes. Room temperature DC I–V characteristics displayed hysteretic I–V loops, indicating memristive behavior. At low bias, data indicated Ohmic transport with carrier extraction facilitated by thermionic emission. At high biases, devices exhibited space-charge-limited conduction in the presence of shallow traps. At 77 K, data indicated Ohmic transport at low bias with carrier extraction by thermionic emission while, at high biases, trap-limited space-charge-limited conduction in the presence of traps distributed in energy, with carrier extraction by Fowler–Nordheim tunneling, was observed. The I–V hysteresis was eliminated at 77 K and attenuated by fast scan rates at room temperature, suggesting that carrier trapping/de-trapping underpinned the hysteresis. In impedance measurements, the device response fitted a Randles equivalent circuit indicating purely electronic conduction. By applying voltage waveforms, I–V hysteresis and analog resistive switching (memristive) functionality were observed. Device conductance could be increased sweep by sweep, giving conductance tuning through distinct states, with wait time- or voltage-erase options, consistent with trap filling/emptying effects. Repeated erase–write–read of multiple distinct states over many voltage cycles during continuous use in air was demonstrated. Finally, synaptic functions, e.g., pulse-dependent plasticity, and short- to long-term memory transition, were successfully emulated.
Sustainable space technologies—Strategies toward a predictive aerothermal design of re-useable space transportation systems
Authors: Karl Sebastian , Bykerk Tamas
Published: February 2024

This paper presents a review of current aerothermal design and analysis methodologies for spacecraft. It briefly introduces the most important system architectures, including rockets, gliders, and capsule-based configurations, and gives an overview of the specific aerothermal and thermo-chemical effects that are encountered during their different flight phases and trajectories. Numerical and experimental design tools of different fidelity levels are reviewed and discussed, with a specific focus placed on the present limitations and uncertainty sources of models for the wide range of physical phenomena that are encountered in the analyses. This includes high temperature thermodynamics, chemical effects, turbulence, radiation, and gasdynamic effects. This is followed by a summary of current predictive capabilities and research foci, with missing capabilities identified. Finally, a future strategy toward an efficient and predictive aerothermal design of re-useable space transportation systems is proposed.
Benchmarking inverse optimization algorithms for materials design
Authors: Zhai Hanfeng , Hao Hongxia , Yeo Jingjie
Published: February 2024

Machine learning-based inverse materials discovery has attracted enormous attention recently due to its flexibility in dealing with black box models. Yet, many metaheuristic algorithms are not as widely applied to materials discovery applications as machine learning methods. There are ongoing challenges in applying different optimization algorithms to discover materials with single- or multi-elemental compositions and how these algorithms differ in mining the ideal materials. We comprehensively compare 11 different optimization algorithms for the design of single- and multi-elemental crystals with targeted properties. By maximizing the bulk modulus and minimizing the Fermi energy through perturbing the parameterized elemental composition representations, we estimated the unique counts of elemental compositions, mean density scan of the objectives space, mean objectives, and frequency distributed over the materials’ representations and objectives. We found that nature-inspired algorithms contain more uncertainties in the defined elemental composition design tasks, which correspond to their dependency on multiple hyperparameters. Runge–Kutta optimization (RUN) exhibits higher mean objectives, whereas Bayesian optimization (BO) displayed low mean objectives compared with other methods. Combined with materials count and density scan, we propose that BO strives to approximate a more accurate surrogate of the design space by sampling more elemental compositions and hence have lower mean objectives, yet RUN will repeatedly sample the targeted elemental compositions with higher objective values. Our work sheds light on the automated digital design of materials with single- and multi-elemental compositions and is expected to elicit future studies on materials optimization, such as composite and alloy design based on specific desired properties.
On the coupling between magnetoelastic waves and nitrogen vacancy centers in diamond
Authors: Jung Adi , Margueron Samuel , Bartasyte Ausrine , Salahuddin Sayeef
Published: February 2024

We show that a coupling exists between nitrogen vacancy (NV) centers in diamond in proximity to magnetoelastic spin waves generated by a voltage driven surface acoustic wave. Experimental measurements show the presence of coupling driven by both dipolar fields induced by a spin wave-like excitation and off-resonant coupling of the NV energy levels driven by acoustically driven ferromagnetic resonance dynamics. A model is proposed based on chiral coupling of the NV centers to the stray field that originates from a propagating magnetoelastic wave in a thin magnet, and model predictions are validated by experimental observations. Understanding of the coupling enables a direct measurement of the stray field polarization, which in turn provides a detailed picture of the resonantly coupled magnon–phonon interaction.
THz quantum well photodetector based on LO-phonon scattering-assisted extraction
Authors: Pérez-Urquizo J. , Gacemi D. , Zhang Z. Z. , Liu B. B. , But D. B. , Yavorskiy D. , Łusakowski J. , Knap W. , Li H. , Todorov Y.
Published: February 2024

We present a design for a quantum photodetector operating in the terahertz range, at 3.45 THz (15 meV, 87 μm). Our device relies on biased GaAs/AlGaAs heterostructure, designed to exploit LO phonon scattering as an extraction mechanism. In our design, the external potential due to the applied bias forms an extraction miniband and allows accommodating an LO phonon transition (36 meV) and use it as an extraction mechanism, even though its energy exceeds the detector's absorbing transition at 15 meV. Spectral-resolved measurements performed on arrays of patch antenna microcavities reveal a peak photocurrent at the designed photon energy with a responsivity of 80 mA/W at 20 K. The maximum operating temperature of the photodetector is found to be 40 K. Detector characterizations were performed both with a black-body source as well as with a terahertz quantum cascade laser emitting at 3.5 THz.
Generalized kinetic equation for tokamak plasma equilibrium distribution function
Authors: Dudkovskaia A. V. , Wilson H. R.
Published: February 2024

A generalized kinetic equation for the equilibrium distribution function in a finite beta, arbitrary tokamak plasma is derived. The equation is correct to second order in ρ/L (ρ is the particle Larmor radius and L is the system size). Resolving the finite Larmor radius length scales with no restriction on the ratio of poloidal to total equilibrium magnetic field, Bϑ/B, it generalizes the drift kinetic theory of Hazeltine [Phys. Plasmas 15, 77 (1973)] to the limit of Bϑ/B∼1 (e.g., to ensure validity for spherical tokamaks). Two cases are considered. The first provides the equilibrium distribution function, consistent with the generalized gyrokinetic formalism of Dudkovskaia et al. [Plasma Phys. Controlled Fusion 65, 045010 (2023)], derived specifically to capture neoclassical equilibrium currents in the gyrokinetic stability analyses in strong gradient regions. The second assumes short length scales in the direction perpendicular to the magnetic field, which can occur as a result of small coherent magnetic structures in the plasma, such as neoclassical tearing mode magnetic islands close to threshold. This then extends the drift island equations of Dudkovskaia et al. [Nucl. Fusion 63, 016020 (2023)] for the plasma response to magnetic islands to a spherical tokamak plasma configuration. Resolving ρ∼ρϑ (or Bϑ∼B), where ρϑ is the particle poloidal Larmor radius, is also expected to influence calculations of the magnetic island propagation frequency and the associated contributions to the island onset conditions.
Mixing behavior equations created by a buoyant jet in wavy crossflow environments
Authors: Fang Shuqiao , Chen Yongping , Shi Weiyong , Xu Zhenshan , Zhou Xin , Xu Xuefeng
Published: February 2024

The understanding of mixing behaviors of submerged effluent discharge in buoyant jet flows within coastal dynamic environments remains incomprehensive. This study explores the mixing behaviors of buoyant jets in wavy crossflow environments by utilizing dimensional analysis and an integral model. We examine physical mechanisms underlying the linear uplift of buoyant jets and establish three semi-empirical equations pertaining to the vertical location of the cross-sectional minimum dilution, cross-sectional minimum dilution, and visible diffusion area. These equations quantify the influence of waves and buoyancy on the mixing behaviors of buoyant effluent discharge in wavy crossflow environments. The dimensional analysis demonstrates that the proposed mixing behavior equations are closely related to the buoyant characteristic length scale. We validate the reliability of these equations with that of existing ones for non-buoyant jets in wavy crossflow environments. Furthermore, this study extends the application of buoyant jet equations, evaluating their suitability by comparing them with data from cases involving buoyant jets in wavy crossflow environments. This study highlights the positive effect of wave height and buoyancy on the initial dilution of effluent discharge. Future studies can implement our semi-empirical equations on the near and far zone coupling simulations of wastewater and thermal discharges.
Linear analysis and crossphase dynamics in the CTEM fluid model
Authors: Leconte M. , Qi Lei , Anderson J.
Published: February 2024

Collisionless trapped-electron mode (CTEM) turbulence is an important contributor to heat and particle transport in fusion devices. The ion-temperature gradient (ITG)/trapped-electron mode (TEM) fluid models are rarely treated analytically, due to the large number of transport channels involved, e.g., particle and ion/electron heat transport. The CTEM fluid model [Anderson et al., Plasma Phys. Controlled Fusion 48, 651 (2006)] provides a simplified model, in the regime where the density gradient drive (∇n) is negligible compared to the electron temperature gradient drive (∇Te). This provides a starting point to study mechanisms associated with linear waves, such as crossphase dynamics, and its possible role in the formation of E × B staircase. Here, an extended CTEM fluid model (with both ∇n and ∇Te drive) is derived from the more general ITG/TEM model, using a simplified ion density response, and its linear dynamics is first analyzed and compared with CTEM gyrokinetic simulations with bounce-averaged kinetic electrons, while nonlinear analysis is left for future work. The wave action density is derived for this CTEM model. Comparisons of linear ITG spectrum are also made with other analytical models.
Effect of boron concentration on local structure and spontaneous polarization in AlBN thin films
Authors: Calderon V S. , Hayden John , Delower M. , Maria Jon-Paul , Dickey Elizabeth C.
Published: February 2024

The discovery of ferroelectricity in polar wurtzite-based ternary materials, such as Al1−xBxN, has attracted attention due to their compatibility with complementary metal–oxide–semiconductor processes and potential use in integrated non-volatile memory devices. However, the origin of ferroelectricity and the fundamental control of the polarization switching in these materials are still under intensive investigation but appear to be related to local disorder induced from the alloying. In this work, we report the effect of boron alloying on the local structure of Al1−xBxN films deposited by magnetron sputtering. Our results reveal a diminished crystalline order as a function of boron concentration, accompanied by a reduction in the spontaneous polarization. The film disorder is primarily associated with the dissimilar bond lengths between Al–N and B–N and the formation of threading dislocations induced by B incorporation in the structure.
Order parameter dynamics in complex systems: From models to data
Authors: Zheng Zhigang , Xu Can , Fan Jingfang , Liu Maoxin , Chen Xiaosong
Published: February 2024

Collective ordering behaviors are typical macroscopic manifestations embedded in complex systems and can be ubiquitously observed across various physical backgrounds. Elements in complex systems may self-organize via mutual or external couplings to achieve diverse spatiotemporal coordinations. The order parameter, as a powerful quantity in describing the transition to collective states, may emerge spontaneously from large numbers of degrees of freedom through competitions. In this minireview, we extensively discussed the collective dynamics of complex systems from the viewpoint of order-parameter dynamics. A synergetic theory is adopted as the foundation of order-parameter dynamics, and it focuses on the self-organization and collective behaviors of complex systems. At the onset of macroscopic transitions, slow modes are distinguished from fast modes and act as order parameters, whose evolution can be established in terms of the slaving principle. We explore order-parameter dynamics in both model-based and data-based scenarios. For situations where microscopic dynamics modeling is available, as prototype examples, synchronization of coupled phase oscillators, chimera states, and neuron network dynamics are analytically studied, and the order-parameter dynamics is constructed in terms of reduction procedures such as the Ott–Antonsen ansatz, the Lorentz ansatz, and so on. For complicated systems highly challenging to be well modeled, we proposed the eigen-microstate approach (EMP) to reconstruct the macroscopic order-parameter dynamics, where the spatiotemporal evolution brought by big data can be well decomposed into eigenmodes, and the macroscopic collective behavior can be traced by Bose–Einstein condensation-like transitions and the emergence of dominant eigenmodes. The EMP is successfully applied to some typical examples, such as phase transitions in the Ising model, climate dynamics in earth systems, fluctuation patterns in stock markets, and collective motion in living systems.
Gradual weakening down to complete disappearance of the velocity correlated cluster emission effect in keV collisions of C60 with light metallic targets: Microscopic insights via molecular dynamics simulations
Authors: Bernstein V. , Bekkerman A. , Kolodney E.
Published: February 2024

The so-called velocity correlated cluster emission (VCCE) effect is the recently reported emission of large clusters with nearly the same velocity from an atomically heavy target (such as coinage metals) following a single C60− impact at the keV kinetic energy range. The effect was observed to get weaker for a meaningfully lighter target (Al) down to its complete disappearance for C60–Be impact. Microscopic insight into the subpicosecond evolution and thermalization of the impact induced energy spike (driving the effect) is achieved using molecular dynamics simulations. It is shown that the weakening of the VCCE effect for aluminum (toward its complete disappearance for Be) is due to ultrafast decay of the atomic number density within the spike nanovolume, thus not enabling the buildup of sufficient subsurface pressure as required for driving the correlated emission. For the Be target, an extremely rapid decay of nearly 90% of the initial density within 200 fs from impact is observed. This finding provides further support for the conclusion that the emission of the velocity correlated clusters as observed for the heavier targets takes place within an ultra-short time window of only a few hundreds of femtoseconds, roughly extending from 200 to 500 fs from impact. The lower bound is dictated by the requirement for a relatively slow rate of decay of number density, enabling the buildup of a sufficiently intense pressure spike. The upper bound is dictated by the cooling rate of the spike (still maintaining an extremely high temperature of kT ≥ 1 eV, as experimentally observed) and the onset of the evolution of the impact crater.
Inferring energy–composition relationships with Bayesian optimization enhances exploration of inorganic materials
Authors: Vasylenko Andrij , Asher Benjamin M. , Collins Christopher M. , Gaultois Michael W. , Darling George R. , Dyer Matthew S. , Rosseinsky Matthew J.
Published: February 2024

Computational exploration of the compositional spaces of materials can provide guidance for synthetic research and thus accelerate the discovery of novel materials. Most approaches employ high-throughput sampling and focus on reducing the time for energy evaluation for individual compositions, often at the cost of accuracy. Here, we present an alternative approach focusing on effective sampling of the compositional space. The learning algorithm PhaseBO optimizes the stoichiometry of the potential target material while improving the probability of and accelerating its discovery without compromising the accuracy of energy evaluation.
On the coupling effect in the RF-biased inductively coupled plasma with the synchronous control
Authors: He Yi , Lu Manting , Liu Xue , Huang Jiamin , Zhang Jiawei , Ma Xiaoping , Huang Lei , Xu Liang , Xin Yu
Published: February 2024

The coupling effects between the bias power and the inductive power in the RF-biased inductively coupled plasma with synchronous control are investigated by measuring electron energy distribution function using a compensated Langmuir probe. With synchronous control, the inductive power and the bias power are driven at an identical phase and frequency. The experimental results show that the inductive power lowers the self-bias voltage, while the bias power changes the plasma density by introducing extra power absorption and dissipation. The bias power also enhances the electron beam confinement, leading to an increase in electron density at a low pressure. Furthermore, in the E and H mode transition, with the bias power increasing, the hysteresis power reduces, and the electron density jump decreases.
Characterization of bright betatron radiation generated by direct laser acceleration of electrons in plasma of near critical density
Authors: Cikhardt J. , Gyrdymov M. , Zähter S. , Tavana P. , Günther M. M. , Bukharskii N. , Borisenko N. , Jacoby J. , Shen X. F. , Pukhov A. , Andreev N. E. , Rosmej O. N.
Published: February 2024

Directed x-rays produced in the interaction of sub-picosecond laser pulses of moderate relativistic intensity with plasma of near-critical density are investigated. Synchrotron-like (betatron) radiation occurs in the process of direct laser acceleration (DLA) of electrons in a relativistic laser channel when the electrons undergo transverse betatron oscillations in self-generated quasi-static electric and magnetic fields. In an experiment at the PHELIX laser system, high-current directed beams of DLA electrons with a mean energy ten times higher than the ponderomotive potential and maximum energy up to 100 MeV were measured at 1019 W/cm2 laser intensity. The spectrum of directed x-rays in the range of 5–60 keV was evaluated using two sets of Ross filters placed at 0° and 10° to the laser pulse propagation axis. The differential x-ray absorption method allowed for absolute measurements of the angular-dependent photon fluence. We report 1013 photons/sr with energies >5 keV measured at 0° to the laser axis and a brilliance of 1021 photons s−1 mm−2 mrad−2 (0.1%BW)−1. The angular distribution of the emission has an FWHM of 14°–16°. Thanks to the ultra-high photon fluence, point-like radiation source, and ultra-short emission time, DLA-based keV backlighters are promising for various applications in high-energy-density research with kilojoule petawatt-class laser facilities.
Flow characteristics in a semi-confined circular-pipe impinging jet
Authors: Chen Ming , Yang Lanbin , Huang Haijin , Zhou Xusheng , Zhang Wenming , Wang Duoyin
Published: February 2024

The impinging jet is a complex heat and mass transfer technique that involves several process variables, such as the jet Reynolds number, impingement distance, and jet configuration. In this study, the flow characteristics of a semi-confined circular-pipe impinging jet over different Reynolds numbers and impingement distances were experimentally investigated using a two-dimensional particle image velocimetry technique. The confinement was achieved by positioning a plate parallel to the impinging plate at the nozzle exit. The time-averaged velocity field exhibited a recirculation structure that gradually shifted downstream with increasing Reynolds numbers or impingement distances. Notably, at H/d = 2, this downstream shift of the structure was accompanied by an increase in the vortex intensity. Moreover, the confined plate induced alterations in the overall flow pattern within the confined region, significantly reducing the wall jet decay rate compared with both unconfined and confined radial wall jets for H/d ≥ 3. Conversely, the confinement did not affect the expansion of the wall jet. Unlike the free (unconfined) impinging jets, the semi-confined circular-pipe impinging jet did not exhibit self-similar behavior in the conventional outer-scaled coordinates, particularly concerning the turbulence intensity and Reynolds shear stress. Finally, self-similarity in the time-averaged velocity and various turbulence parameters was achieved using the parameter scale proposed in this study, thereby obtaining the corresponding scaling laws in the wall jet region. Our study results can deepen the current understanding of the flow characteristics of semi-confined circular-pipe impinging jets and are significant for optimizing the performance and efficiency of compact electronic packaging equipment.
Path planning of water surface garbage cleaning robot based on improved immune particle swarm algorithm
Authors: Wang Yuqin , Hernandez Alexander , Shen Lixiang , Zhang Haodong
Published: February 2024

In order to effectively improve the efficiency of surface garbage cleaning robot, an intelligent control algorithm was applied to plan the robot path. To do so, an improved immune particle swarm algorithm was developed based on the robot model. This algorithm introduced the adaptive information dynamic adjustment strategy to dynamically adjust the main link indices, which improved the global searchability and convergence of particles and facilitated the quick identification of the optimal path by the robot. Through comparative simulation experiments with the particle swarm optimization algorithm, genetic algorithm, and immune particle swarm optimization algorithm, it was found that the robot based on the Adaptive Immune Particle Swarm Optimization (AIPSO) algorithm had the shortest planning path and search time, the lowest energy consumption, and the highest efficiency. A robot prototype platform was built. Compared to other algorithms, the efficiency of the robot space search based on the AIPSO algorithm was the highest, the search time was the shortest, and the energy consumption was also the lowest. Especially in the complex level 4 wave water environment, the AIPSO algorithm had the best adaptability and robustness, and the robot had the highest working efficiency and comprehensive performance. The experimental results revealed that the AIPSO algorithm effectively improved the path search and garbage cleaning efficiency of the robots and reduced the working time, which further verified the reliability and accuracy of the designed algorithm.