Importance In Many Applications Research Articles

Nonreciprocal Acoustic Devices with Asymmetric Peierls Phases.

Nonreciprocity in acoustics is of paramount importance in many practical applications and has been experimentally realized using nonlinear media, moving fluids, or time modulation, which regrettably suffer from large volumes and high-power consumption, difficulty in integration, and inevitable vibrations or phase noise. In modern Hamiltonian theory, the violation of system's reciprocity can be achieved via asymmetric Peierls phases, which typically involves with non-Hermiticity or time-reversal symmetry breaking. Here, we propose a framework for designing nonreciprocal acoustic devices based on the asymmetric Peierls phases that can be fully controlled via active acoustic components. The fully controlled Peierls phases enable various high-performance acoustic devices, including non-Hermitian extensions of isolators, gyrators, and circulators, which are otherwise impossible in previous approaches that are bound by Hermiticity or passivity. We reveal that the transmission phases in isolators are equivalent to the Peierls phase plus a constant. The nonreciprocal phase delay in gyrators and the unirotational transmission behavior in circulators result from the gauge-invariant Aharonov-Bohm phases determined by Peierls phases. Our work not only uncovers multiple intriguing physics related to Peierls phases but also provides a general approach to compact, integratable, nonreciprocal acoustic devices.

Role of strain softening and viscoelastic memory for the rolling friction of two tire tread compounds.

Rolling friction is of great importance for many applications, such as tires and conveyor belts. We study the rolling friction for hard cylinders rolling on flat rubber sheets. The rolling friction depends on the number of rolling cycles, the rolling speed, and the temperature. We show that when the rubber is cooled down below the glass transition temperature, the deformations of the rubber surface are frozen-in, resulting in a non-flat rolling track where uphill and downhill rolling movements strongly affect the rolling force. The experimental data are analyzed using the Persson rolling friction theory; good agreement with the experiments is obtained when the non-linear (strain-softening) properties of the viscoelastic modulus are taken into account.

A spectral approach for the dynamic Bradley–Terry model

SummaryThe dynamic ranking, due to its increasing importance in many applications, is becoming crucial, especially with the collection of voluminous time‐dependent data. One such application is sports statistics, where dynamic ranking aids in forecasting the performance of competitive teams, drawing on historical and current data. Despite its usefulness, predicting and inferring rankings pose challenges in environments necessitating time‐dependent modelling. This paper introduces a spectral ranker called Kernel Rank Centrality, designed to rank items based on pairwise comparisons over time. The ranker operates via kernel smoothing in the Bradley–Terry model, utilising a Markov chain model. Unlike the maximum likelihood approach, the spectral ranker is nonparametric, demands fewer model assumptions and computations and allows for real‐time ranking. We establish the asymptotic distribution of the ranker by applying an innovative group inverse technique, resulting in a uniform and precise entrywise expansion. This result allows us to devise a new inferential method for predictive inference, previously unavailable in existing approaches. Our numerical examples showcase the ranker's utility in predictive accuracy and constructing an uncertainty measure for prediction, leveraging data from the National Basketball Association (NBA). The results underscore our method's potential compared with the gold standard in sports, the Arpad Elo rating system.

Beyond Structural Stabilization of Highly‐Textured AlN Thin Films: The Role of Chemical Effects

AbstractThe crystalline quality and degree of c‐axis orientation of hexagonal AlN thin films correlate directly with their functional properties. Therefore, achieving AlN thin films of high crystalline quality and texture is of extraordinary importance for many applications, but particularly in electronic devices. This systematic study reveals, that the growth of c‐axis‐orientated AlN thin films can be governed by a chemical stabilization effect in addition to the conventionally known structural, strain‐induced, stabilization mechanism. The promotion of in‐plane growth of AlN grains with c‐axis out‐of‐plane orientation is demonstrated on Y, W, or Al seed layers with different thicknesses and crystallinity preliminary exposed to N2 at room temperature. It is established that the stabilization mechanism is chemical in nature: the formation of an N‐rich surface layer on the metal seed layers upon exposure to N2 pre‐determines the polarity of AlN islands at the initial stages of thin film growth while the low energy barrier for the subsequent coalescence of islands of the same polarity contributes to grain growth. These results suggest that the growth of c‐axis oriented AlN thin films can be optimized and controlled chemically, thus opening more pathways for energy‐efficient and controllable AlN thin film growth processes.

Highly defective ultra-small tetravalent MOF nanocrystals

The size and defects in crystalline inorganic materials are of importance in many applications, particularly catalysis, as it often results in enhanced/emerging properties. So far, applying the strategy of modulation chemistry has been unable to afford high-quality functional Metal–Organic Frameworks (MOFs) nanocrystals with minimized size while exhibiting maximized defects. We report here a general sustainable strategy for the design of highly defective and ultra-small tetravalent MOFs (Zr, Hf) crystals (ca. 35% missing linker, 4–6 nm). Advanced characterizations have been performed to shed light on the main factors governing the crystallization mechanism and to identify the nature of the defects. The ultra-small nanoMOFs showed exceptional performance in peptide hydrolysis reaction, including high reactivity, selectivity, diffusion, stability, and show emerging tailorable reactivity and selectivity towards peptide bond formation simply by changing the reaction solvent. Therefore, these highly defective ultra-small M(IV)-MOFs particles open new perspectives for the development of heterogeneous MOF catalysts with dual functions.

Analyzing Queueing Problems via Bandits With Linear Reward & Nonlinear Workload Fairness

Queueing models serve as important building blocks in many networking applications such as task scheduling in mobile edge computing nodes, traffic scheduling in networks, congestion control in Internet, etc. However, queueing theory often needs to make strong assumptions about the arrival process or service rewards at each queue. In addition, fairness in serving workload among all queues is of great importance in many applications. In this paper, we address how to optimize resource allocation among multiple queues with a fairness guarantee and without any a priori knowledge of these queues' parameters. To characterize queues with unknown parameters and the fairness requirement, we formulate an online learning model with a varying and continuous action space, as well as a nonlinear utility objective. We design an online learning algorithm to tackle the problem. We prove that our algorithm has a regret upper bound of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(\sqrt{T}\log T)$</tex-math></inline-formula> and our model has a regret lower bound of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Omega (\sqrt{T})$</tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$T$</tex-math></inline-formula> stands for the number of decision rounds. The asymptotic closeness of upper and lower bounds guarantees their near tightness and our algorithm's near optimality. We discuss our model's real-world applications in mobile edge computing, wireless networks, and crowdsourcing, and conduct simulations to validate our algorithm's effectiveness.

Data-driven solutions of ill-posed inverse problems arising from doping reconstruction in semiconductors

ABSTRACT The non-destructive estimation of doping concentrations in semiconductor devices is of paramount importance for many applications ranging from crystal growth to defect and inhomogeneity detection. A number of technologies (such as LBIC, EBIC and LPS) have been developed which allow the detection of doping variations via photovoltaic effects. The idea is to illuminate the sample at several positions and detect the resulting voltage drop or current at the contacts. We model a general class of such photovoltaic technologies by ill-posed global and local inverse problems based on a drift-diffusion system which describes charge transport in a self-consistent electrical field. The doping profile is included as a parametric field. To numerically solve a physically relevant local inverse problem, we present three approaches, based on least squares, multilayer perceptrons, and residual neural networks. Our data-driven methods reconstruct the doping profile for a given spatially varying voltage signal induced by a laser scan along the sample's surface. The methods are trained on synthetic data sets which are generated by finite volume solutions of the forward problem. While the linear least square method yields an average absolute error around 10%, the nonlinear networks roughly halve this error to 5%.

Random laser emission at 1064 and 1550 nm in a Er/Yb co-doped fiber-based dual-wavelength random fiber laser.

Dual-wavelength fiber lasers operating with a wide spectral separation are of considerable importance for many applications. In this study, we propose and experimentally explore an all-fiberized dual-wavelength random fiber laser with bi-directional laser output operating at 1064 and 1550 nm, respectively. A specially designed Er/Yb co-doped fiber, by optimizing the concentrations of the co-doped Er, Yb, Al and P, was developed for simultaneously providing Er ions gain and Yb ions gain for RFL. Two spans of single mode passive fibers are employed to providing random feedback for 1064 and 1550 nm random lasing, respectively. The RFL generates 5.35 W at 1064 nm and 6.61 W at 1550 nm random lasers. Two power amplifiers (PA) enhance the seed laser to 50 W at 1064 nm with a 3 dB bandwidth of 0.31 nm and 20 W at 1550 nm with a 3 dB bandwidth of 1.18 nm. Both the short- and long-term time domain stabilities are crucial for practical applications. The output lasers of 1064 and 1550 nm PAs are in the single transverse mode operating with a nearly Gaussian profile. To the best of our knowledge, this is the first demonstration of a dual-wavelength RFL, with a spectral separation as far as about 500 nm in an all-fiber configuration.

Bending and Stretching‐Insensitive, Crosstalk‐Free, Flexible Pressure Sensor Arrays for Human‐Machine Interactions

AbstractAccurate data acquisition from flexible sensors placed on deformable 3D freeform surfaces is of critical importance for many applications, such as wearable electronics, human‐machine interfaces, and soft robotics. However, the mechanical coupling between the sensor and the deformable subject surface to bending and stretching deformations can significantly reduce the accuracy of the acquired data. This study combines a polyimide (PI) micropore isolation layer (PIL) and serpentine electrodes with a flexible piezoresistive sensor to mitigate the issue of mechanical coupling. As a mechanical buffer to distribute the external pressure and reduce the strain concentration, the PIL can avoid the bending interference for bending curvature up to 256 m−1, while maintaining a high sensitivity of S &gt; 21.5 kPa−1. The serpentine electrode design further allows the sensor to reliably acquire data in the presence of stretching up to 45% without cross‐talk. The versatility of the developed sensor is demonstrated in several human‐machine interaction scenarios, including gesture recognition and motion detection. The design strategies on materials and structures from this study can also be applied for the development of other flexible sensors with high sensitivity and low deformation interference to avoid the mechanical coupling between the sensor and the deformable surface.

How spin state and oxidation number of transition metal atoms determine molecular adsorption: a first-principles case study for NH3.

Understanding how the electronic state of transition metal atoms can influence molecular adsorption on a substrate is of great importance for many applications. Choosing NH3 as a model molecule, its adsorption behavior on defected SnS2 monolayers is investigated. The number of valence electrons n is controlled by decorating the monolayer with different transition metal atoms, ranging from Sc to Zn. Density-Functional Theory based calculations show that the adsorption energy of NH3 molecules oscillates with n and shows a clear odd-even pattern. There is also a mirror symmetry of the adsorption energies for large and low electron numbers. This unique behavior is mainly governed by the oxidation state of the TM ions. We trace back the observed trends of the adsorption energy to the orbital symmetries and ligand effects which affect the interaction between the 3σ orbitals (NH3) and the 3d orbitals of the transition metals. This result unravels the role which the spin state of TM ions plays in different crystal fields for the adsorption behavior of molecules. This new understanding of the role of the electronic structure on molecular adsorption can be useful for the design of high efficiency nanodevices in areas such as sensing and photocatalysis.

Interactive Visual Analysis of Spatial Sensitivities.

Sensitivity analyses of simulation ensembles determine how simulation parameters influence the simulation's outcome. Commonly, one global numerical sensitivity value is computed per simulation parameter. However, when considering 3D spatial simulations, the analysis of localized sensitivities in different spatial regions is of importance in many applications. For analyzing the spatial variation of parameter sensitivity, one needs to compute a spatial sensitivity scalar field per simulation parameter. Given n simulation parameters, we obtain multi-field data consisting of n scalar fields when considering all simulation parameters. We propose an interactive visual analytics solution to analyze the multi-field sensitivity data. It supports the investigation of how strongly and in what way individual parameters influence the simulation outcome, in which spatial regions this is happening, and what the interplay of the simulation parameters is. Its central component is an overview visualization of all sensitivity fields that avoids 3D occlusions by linearizing the data using an adapted scheme of data-driven space-filling curves. The spatial sensitivity values are visualized in a combination of a Horizon Graph and a line chart. We validate our approach by applying it to synthetic and real-world ensemble data.

Evaluation of methods to determine the surface mixing layer height of the atmospheric boundary layer in the central Arctic during polar night and transition to polar day in cloudless and cloudy conditions

Abstract. This study evaluates methods to derive the surface mixing layer (SML) height of the Arctic atmospheric boundary layer (ABL) using in situ measurements inside the Arctic ABL during winter and the transition period to spring. An instrumental payload carried by a tethered balloon was used for the measurements between December 2019 and May 2020 during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Vertically highly resolved (centimeter scale) in situ profile measurements of mean and turbulent parameters were obtained, reaching from the sea ice to several hundred meters above ground. Two typical conditions of the Arctic ABL over sea ice were identified: cloudless situations with a shallow surface-based inversion and cloudy conditions with an elevated inversion. Both conditions are associated with significantly different SML heights whose determination as accurately as possible is of great importance for many applications. We used the measured turbulence profile data to define a reference of the SML height. With this reference, a more precise critical bulk Richardson number of 0.12 was derived, which allows an extension of the SML height determination to regular radiosoundings. Furthermore, we have tested the applicability of the Monin–Obukhov similarity theory to derive SML heights based on measured turbulent surface fluxes. The application of the different approaches and their advantages and disadvantages are discussed.

Limitations to the energy resolution of single-photon sensitive microwave kinetic inductance detectors

This paper describes the energy resolution of microwave kinetic inductance detectors and models some limiting factors to it. Energy resolution is a measure of the smallest possible difference in energy of the impinging photons, ΔE, that the detector can identify and, as such, is of critical importance for many applications. Limits to the energy resolution caused by the Fano effect, amplifier noise, current inhomogeneities, and readout sampling frequency are taken into consideration for this model. This paper describes an approach to combine all of these limitations and predict a wavelength dependency of the upper limit to the resolving power.

Amorphous matters: Heterogeneity and defects of nanopore silica surfaces enhance CO[formula omitted] adsorption

Despite its importance for many applications (such as catalysis and structure ripening), adsorption on amorphous silica remains poorly understood as most studies focus on crystalline surfaces. Here, we investigate the adsorption of carbon dioxide, CO2, on hydroxylated silica nanopores by means of molecular dynamics (MD) simulations that compare amorphous and crystalline surfaces. We find that adsorption onto amorphous surfaces is enhanced by the heterogeneity of the structure and by the presence of under-coordinated defects (non-bridging oxygen and threefold coordinated silicon). We identify two classes of adsorption features: (i) a continuous region characterized by an intermediate density of adsorbed CO2 molecules, which is generated by weak interactions with hydroxyl groups and forms a network that allows molecules to diffuse through the surface adsorption layer; (ii) high-density cage-like features (embedded into the network and induced by the presence of defects) in which CO2 molecules form multiple short- and long-lived bonds with surrounding atoms and remain adsorbed for a longer time. The rich variety of adsorption features enhances physisorption and leads to longer mean adsorption time than onto the crystalline surfaces. The adsorption time onto amorphous surfaces deviates from the exponential distribution observed in silica crystals and displays a characteristic fat tail. Our findings support the experimental discovery of the potential of defected silica surfaces for CO2 adsorption and subsequent catalytic conversion to methane, suggesting the possibility of designing and manufacturing specific adsorption features for tailored heterogeneous catalysis.

5-bit all-optical quantum random number generator based on a time-multiplexed optical parametric oscillator.

Random numbers are of critical importance in many applications, including secure communication, photonics computing and cryptography. Due to the non-deterministic nature of the quantum processes, a degenerate optical parametric oscillator (DOPO) constitutes a solution to produce true randomness. Nevertheless, one of the existing challenges for DOPO in this field is bit sequence scalability. Here, we experimentally report on the generation of 5-bit random number streams in a time-multiplexed femtosecond DOPO system. A multi-pass cell is added to elongate the OPO cavity to scale up the bit sequences. To this end, for a ∼15 m long all free space OPO cavity, resonating 5 signal pulses with a repetition rate of 50 MHz is demonstrated. The above-threshold binary phase nature originates from vacuum fluctuations of a DOPO ensuring the randomness of the system. The phase state of the output is characterized by the interference pattern between the output pulses and the fundamental pump pulses. Different bit sequences are presented here by turning on and off the OPO. Conditional probability is performed to verify the randomness of the output for 1200 bits. Our scheme provides a new direction for an all-optical random number generator.

Evaluation of sea surface roughness parameterization in meso-to-micro scale simulation of the offshore wind field

Accurate parameterization of the wind-induced effects on the Marine Atmospheric Boundary Layer (MABL) is of fundamental importance for many applications including weather forecasting and offshore wind energy. Roughness parameterizations derived from different datasets are widely used but their performance is not sufficiently assessed under realistic marine environmental conditions. To this end, a multi-scale atmosphere–wave coupled model is constructed for the first time and used in the simulation of the MABL flow over the North Sea. Results show that our model is able to capture the large-scale variation of the mean wind meanwhile reproducing the appropriate turbulence energy cascade in the frequency domain. The performance of different roughness parameterizations is evaluated in comparison with the measurement data from the FINO1 platform. The Taylor-Yelland method outperforms the others on statistics of the mean wind while yielding the highest bias of the Turbulence Kinetic Energy (TKE) from the observations. However, we find that the discrepancy between our simulation and observation mainly depends on the meso-scale model. The magnitude of the differences caused by roughness parameterizations is negligible, especially in low wind speed conditions. The micro-scale simulation is demonstrated as not sensible to the roughness input in the considered wind–wave condition.

Dolomitisation favoured by Lewis acidic background compounds in saline fluids

Predicting the type and rate of reactions between minerals and fluids is of utmost importance in many applications. Due to the presence of background ions, natural environments are often much more complex than laboratory experimental conditions that are used to derive mineral dissolution or precipitation rates. Dolomitisation is one of the most important diagenetic processes affecting carbonate rocks. Still, its underlying mechanisms are not yet completely unraveled. Here, we test the impact of background ions in saline solutions on the dolomitisation rate. Using batch reactor experiments at 200 °C and mineralogical characterisation, we demonstrate that the presence of background ions influences the fluid starting pH and specific ion effect, both impacting the dolomitisation rate. The results indicate that ions with a stronger hydration enthalpy correlate with a shorter dolomitisation induction time, and that Lewis acid AlCl3 is more effective than Brønsted acid HCl. Importantly, dolomitisation occurred at a slightly acidic pH, and carbon speciation modelling showed that carbonate ions did not dominate in any of the experiments. Hence, dolomitisation in our experiments is faster in saline, slightly acidic rather than alkaline solutions and the rate is influenced by the solution composition, with specific ion effects influencing dolomite surface charge, interfacial tension and the structure of water. These new insights have implications for interpretations on natural environments, such as deep reservoirs with saline, slightly acidic formation water, and predictions related to geological carbon dioxide storage.

Global energy-preserving local mesh-refined S-FDTD schemes for two dimensional Maxwell's equations in Drude metamaterials

Modeling electromagnetic propagation in metamaterials is of importance in many applications. Designing efficient local mesh refinements is crucial to improve the resolution capacity of solution for solving Maxwell's equations within metamaterials and it is a difficult task to develop local mesh-refined schemes for preserving global energy across the interfaces between coarse and fine meshes. In this paper, we develop two global energy-preserving local mesh-refined splitting FDTD schemes for Maxwell's equations with Drude model. By combining with the energy-conserved splitting FDTD methods, the local mesh-refined interface schemes are established on the interfaces of coarse and fine meshes, which ensure global energy preserving. We prove that the developed GEP-LMR-S-FDTD schemes satisfy global energy conservation and are unconditionally stable. Meanwhile, fast implementation of the GEP-LMR-S-FDTD schemes is investigated to compute the metamaterial electromagnetic problems. Numerical experiments show the excellent performance of the schemes.

Quasi-Newton methods for topology optimization using a level-set method

The ability to efficiently solve topology optimization problems is of great importance for many practical applications. Hence, there is a demand for efficient solution algorithms. In this paper, we propose novel quasi-Newton methods for solving PDE-constrained topology optimization problems. Our approach is based on and extends the popular solution algorithm of Amstutz and Andrä (J Comput Phys 216: 573–588, 2006). To do so, we introduce a new perspective on the commonly used evolution equation for the level-set method, which allows us to derive our quasi-Newton methods for topology optimization. We investigate the performance of the proposed methods numerically for the following examples: Inverse topology optimization problems constrained by linear and semilinear elliptic Poisson problems, compliance minimization in linear elasticity, and the optimization of fluids in Navier–Stokes flow, where we compare them to current state-of-the-art methods. Our results show that the proposed solution algorithms significantly outperform the other considered methods: They require substantially less iterations to find a optimizer while demanding only slightly more resources per iteration. This shows that our proposed methods are highly attractive solution methods in the field of topology optimization.

On the Synchronous Ethernet for a Massive Networking Deployment: Insight Into a Tailored Cosimulated Testbed

Digital communications have a minimum synchronization requirement: the end user of a telecommunication system has to lock into the right bit rhythm sent by the other connection partner. Nevertheless, synchronization in the telecommunication context turns out to be broader than two connection partners locally linked: the suitable feed of a standard time, within many telecommunication domains, has vital importance for many applications to properly handle the demanded network functionalities. The time feed in multidomain scenarios makes a time path, which becomes a nested built-in network. Generally, the data distribution follows the time path in many telecommunication systems. However, the data path may not follow the time path for all scenarios and could partially follow some network branches, usually at the network border. To ensure efficient and controllable synchronization, we focus on the study of time paths. This article provides a first insight into a tailored cosimulated testbed, implemented to determine the time path behavior in terms of jitter and to supervise the drift from the primary reference clock (PRC) with more than 20 cascaded nodes, the maximum achievable cascaded depth within the current G.8262 standard. This cascading must meet the requirements of the International Telecommunication Union (ITU-T) standards G.8262/G.8261 in terms of long-term jitter (wander) and short-term jitter (jitter) to ensure a tolerable drift compared with the central clock. In particular, for Synchronous Ethernet (SyncE), the standard does not provide possible limits for the jitter beyond 20 synchronized nodes. The numerical results, with the extended number of nodes, show that this scenario remains feasible, the parameters being below the masks proposed by the standards.