Time Domain Research Articles

Dissecting Allosteric Mutations for Antibiotic Resistance by Time-Dependent Linear Response Theory.

We report a new approach that combines molecular dynamics trajectories with time-dependent linear response theory to compute the time evolution of residue fluctuation responses to force perturbations exerted at functional sites. Applying this new approach to TEM-1 beta-lactamase, we observe that the time-resolved response profiles of allosteric sites to perturbations of TEM-1 active sites are distinct from those of non-allosteric residues. Using Fourier transformations, we convert the time domain response profiles to the frequency domain and demonstrate that the frequency space representation of the perturbation response can capture the mutational behavior of each site when applied to deep sequencing mutational data. Furthermore, we show that classification models built on perturbation responses can accurately identify distal positions that regulate antibiotic resistance. These findings provide insights into the contributions of specific residues to resistance-encoded in time-resolved perturbation response behavior and highlight the importance of this new approach in identifying allosteric mutations, opening avenues for the potential characterization of additional allosteric positions without extensive computational simulations.

Imaging LNAPL distribution at a former chemical plant with time-domain induced polarization

Light non-aqueous phase liquids (LNAPLs) that infiltrate into the subsurface are commonly described in two distinct zones: the source zone and the plume zone. A precise differentiation between these zones is essential for constraining further migration and selecting an effective remediation method. In this study, we employ the induced polarization (IP) method to characterize the contaminants. Six time domain IP survey lines were conducted at a former chemical plant contaminated with LNAPLs. Even though the contaminated areas corresponding to BTEX concentration above 180 mg/kg are less than 5 mS/m, the source and plume zones cannot be distinguished by conductivity alone. However, a noticeable difference in phase (φ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varphi$$\\end{document}) between the two zones is observed, and the threshold phase value corresponding to a critical concentration of 450 mg/kg is 20 mrad. Moreover, the normalized chargeability (Mn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M_{n}$$\\end{document}) threshold for the source zone is 80 mS/m, and the corresponding Mn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M_{n}$$\\end{document} differences between the source and plume zones are more significant than those in φ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varphi$$\\end{document}. These results illustrate that changes in polarization characteristics associated with BTEX concentrations can aid in further distinguishing between the source and plume zones. Ultimately, it is concluded that IP imaging is a well-suited method for LNAPL investigations that permits an improved characterization of different contaminated zones, which can facilitate the optimization of drillings for further site assessment and remediation.

A wind-to-wake approach for selecting future marine fuels and powertrains

Global shipping contributes (2.8%) to greenhouse gas emissions and needs to find future fuels which will allow the International Maritime organisation's 2050 net zero targets to be met. There is much uncertainty as to which fuels should be used between hydrogen, ammonia or methanol as future costs are uncertain. We propose and evaluate a Wind-to-Wake ratio that provides an objective measure based on the amount of renewable energy required to propel a ship. Time domain voyage energy demand profiles are used to simulate the fuel used and emissions for a cruise ship, a research survey vessel, a container ship and a large multi-fuel Liquefied Natural Gas carrier. Alternative ship power systems are investigated using various carbon-based fuels, ammonia and hydrogen either using conventional engines or fuel cells. For all voyage and fuel scenarios the combination of hydrogen and fuel cells uses 30% less renewable energy than ammonia and 26% less than methanol. Hydrogen only emits steam whereas the other fuel scenarios still emit significant amounts of greenhouse gasses.

A Terminal Residual Vibration Suppression Method of a Robot Based on Joint Trajectory Optimization

Vibration problems have become one of the most important factors affecting robot performance. To this end, a terminal residual vibration suppression method based on joint trajectory optimization is proposed to improve the accuracy and stability of robot motion. Firstly, based on the characteristics of the friction nonlinearity due to joint coupling and physical feasibility of dynamic parameters, a semidefinite programming method is used to identify dynamic parameters with actual physical meaning, thereby obtaining an accurate dynamic model. Then, based on the result of the residual vibration time domain analysis, a joint trajectory optimization model with the goal of minimizing joint tracking error is established. The Chebyshev collocation method is used to discretize the optimization model. The dynamic model is used as the optimization constraint, and barycentric interpolation is used to obtain the optimized joint motion trajectory. Finally, industrial robot experiments prove that the vibration suppression method proposed in this article can reduce the maximum acceleration amplitude of residual vibration by 62% and the vibration duration by 71%. Compared with the input shaping method, the method proposed in this paper can reduce the terminal residual vibration more effectively and ensure the consistency of running time and trajectory.

Characteristic value decomposition: A unifying paradigm for data-driven modal analysis

Data-driven modal analysis is an indispensable means to understand the dynamic behavior of engineered structures and natural systems. It effectively captures active dynamic behavior and embeds them in a set of identified linear modal subspaces, unveiling complex dynamic behavior via the superposition of simpler hierarchical spatiotemporal dynamics. Despite the existence of many methods, there is no unified perspective connecting these modal analysis techniques. This paper proposes a new modal decomposition method, the characteristic value decomposition (CVD), that provides a unifying paradigm for data-driven modal analysis. CVD identifies identical spatial modes and temporal coordinates from two measurement data matrices. The modal parameters are identified through an eigendecomposition to a quotient of auto-covariance and cross-covariance matrices of the two data matrices. This paper shows that several data-driven modal analysis methods, namely, the state-variable decomposition, the dynamic mode decomposition, the Ibrahim time domain method, and the eigensystem realization algorithm, are special cases of CVD when the two data matrices are appropriately selected. Moreover, the CVD identifies the modal parameters with higher accuracy and is robust to added noise compared to established methods, as demonstrated using numerical experiments. It is also shown that the CVD flexibly utilizes data from multiple experiments and undersampled data sets to unveil system dynamics.

Spinning waveforms from the Kosower-Maybee-O’Connell formalism at leading order

We provide the analytic waveform in time domain for the scattering of two Kerr black holes at leading order in the post-Minkowskian (weak field, but generic velocity) expansion and up to fourth order in both spins. The result is obtained by the generalization of the Kosower-Maybee-O’Connell formalism to radiative observables, combined with the analytic continuation of the five-point scattering amplitude to complex kinematics. We use analyticity arguments to express the waveform directly in terms of the three-point coupling of the graviton to the spinning particles and the gravitational Compton amplitudes, completely bypassing the need to compute and integrate the five-point amplitude. In particular, this allows us to easily include higher-order spin contributions for any spinning compact body. Finally, in the spinless case, we find a new compact and gauge-invariant representation of the Kovacs-Thorne waveform. Published by the American Physical Society 2024

Optimization method for low-velocity impact identification in nanocomposite using genetic algorithm

Abstract Fiber-reinforced plastic (FRP) is prone to invisible damage caused by low-velocity impact (LVI) during service. The structural health monitoring system is of great significance for damage monitoring and maintenance of composite materials. In this study, four fiber Bragg grating sensors were employed to collect the time domain strain signals of composite materials subjected to LVIs. Furthermore, a numerical simulation model was established to rapidly obtain impact signal dataset. The signal arrival time, peak time, and peak amplitude were selected as signal features, and the backpropagation neural network was successfully applied to determine the location and energy of LVIs. To address the issue of peak feature extraction in the strain signal processing, a genetic algorithm-based sliding window peak detection optimization method was proposed, which significantly improved the final prediction accuracy. The experimental results indicated that within a position range of 300 mm × 300 mm, the average positioning error can reach 5.1 mm; and in an energy range of 0.5–1 J, the average energy prediction error can reach 0.030 J. The proposed method achieved accurate identification of the LVI location and energy for FRP.

Plasmon-enhanced sub-Debye-length nanogap photoelectrochemical cells for field-assisted electrolyte-free water splitting

This work studies pure water splitting (i.e., no additional electrolyte) using plasmonic sub-Debye-length nanogap photoelectrochemical cells (NPECs). With 60 nm Au gratings covered by 4 nm amorphous TiO2 under 638 nm normal incident illumination, we demonstrate up to 66 × higher photocurrent at 1.5 V than that of Au-gratings-only NPECs. In addition, we are able to efficiently drive pure water splitting at voltages as low as 1.3 V, which is very close to the theoretical thermodynamic potential threshold of 1.23 V. Our electromagnetic finite difference time domain (FDTD) simulation results (Lumerical Inc.) show a 240 × increase in the electric field intensity near the TiO2 layer compared to the incident electric field. We attribute our observations to 1) Hot spots generated by surface plasmonic resonance (SPR) on Au gratings, which greatly increase the number of electron-hole pairs; 2) The 60 nm gap distance between electrodes, which is smaller than the Debye length of pure water (∼220 nm) resulting in a much higher electric field by eliminating the shield effect and by coupling two half-reactions of water splitting together; and 3) The 4 nm amorphous TiO2, which improves hot carriers separation. Our NPEC is a promising device for efficient hydrogen production enabling the utilization of visible light.

B-Spline signature responses in structural change detection: method development

Damage detection is perhaps the most critical objective of structural health monitoring. Proper documentation of the progression of structural damage from onset to failure enables performance-based maintenance that mitigates risk and contains socioeconomic impact. Recently, damage detection methods that focus on change detection through analyses of the structural global response in the frequency or time domain have garnered attention due to their efficiency and accuracy. This work proposes a novel time-domain, nonparametric, data-driven change detection method. The time-domain B-Spline transfer function is defined as a signature time history response of the structure, referred to in this work as the B-Spline signature response (BSR). BSR may be computed directly through a physics-based simulation, or it be extracted in a discrete form from measurements of displacement, velocity, or acceleration time histories of structural response to any external excitation. The BSR is independent of loading, is a characteristic of the system, and captures the condition of the structure at the time of acquisition without the need for identifying structural properties. In this work, the fundamentals of the BSR concept are introduced first along with the process of extracting a BSR from structural responses to arbitrary excitations. Verification and validation studies are conducted based on computer simulations and laboratory testing and are discussed in detail. Subsequently, an approach is proposed to detect change through correlation of BSR signals acquired at different times during the monitoring period. Any changes in the intrinsic characteristics affecting the response cause BSR changes and correlation loss. The change detection methodology is demonstrated through computer simulations and experimental investigations. Initial parametric studies are conducted to investigate the suitability of the proposed approach to detect small structural changes. This article demonstrates the validity of the proposed method and establishes the framework for further development and case-specific applications.

Laser irradiation-induced surface-enhanced Raman scattering of Sn@SnO composite films

In this work, Sn@SnO composite films were obtained by Nd:YAG fiber pulsed laser ablation at room temperature. The effects of laser ablation on the microstructure, optical properties, and Raman scattering properties of the films were investigated. Tunable Localized Surface Plasmon resonance(LSPR)of Sn nanoparticles was realized in the wavelength range of 380–450 nm by varying the scanning rate to modulate the degree of oxidation of Sn nanoparticles. Surface enhanced Raman scattering (SERS) was also observed in the composite structure, which was demonstrated excellent stability and SERS sensitivity with the detectable concentration of methylene blue (MB) as low as 10−9 M and an enhancement factor of 1.75 × 105 as well as a good uniformity. Finally, the electric field distribution of the samples before and after the laser treatment is simulated by the finite difference in time domain (FDTD) method, and the results are consistent with those of experimental ones.

Vibration-Induced Sweeping Operation in Fiber Lasers

A new vibration-based mechanism of optical frequency/wavelength sweeping in fiber lasers induced by optical path length modulation of a laser cavity section is proposed. The mechanism is implemented for an erbium-doped fiber ring laser with a saturable absorber. Without the vibrations, the laser generates a single longitudinal mode (SLM) radiation. We show experimentally for the first time that mechanical vibrations of the laser cavity section can lead to mode dynamics in both frequency and time domains. The possibility of obtaining various mode dynamics, such as vibration-induced sweeping in a wavelength range of up to 2.2 nm or SLM generation with periodic mode hopping between two fixed longitudinal modes depending on the pump wavelength, is experimentally shown. In this vibration-based approach, the interval between changes in the laser cavity modes has good stability, because it directly relates to the vibration period.

Health State Prediction Method Based on Multi-Featured Parameter Information Fusion

The prediction of the health status of critical components is an important influence in making accurate maintenance decisions for rotating equipment. Since vibration signals contain a large amount of fault information, they can more accurately describe the health status of critical components. Therefore, it is widely used in the field of rotating equipment health state prediction. However, there are two major problems in predicting the health status of key components based on vibration signals: (1) The working environment of rotating equipment is harsh, and if only one feature in the time or frequency domain is selected for fault analysis, it will be susceptible to harsh operating environments and cannot completely reflect the fault information. (2) The vibration signals are unlabeled time series data, which are difficult to accurately convert into the health status of key components. In order to solve the above problems, this paper proposes a combined prediction model combining a bidirectional long- and short-term memory network (BiLSTM), a self-organizing neural network (SOM) and particle swarm optimization (PSO). Firstly, the SOM is utilized to fuse the fault characteristics of multiple vibration signals of key components to obtain an indicator (HI) that can reflect the health status of rotating equipment and to also compensate for the vulnerability of single signal characteristics in the time or frequency domain to environmental influences. Secondly, the K-means clustering method is employed to cluster the health indicators and determine the health state, which solves the problem of determining the health of a component from unsupervised vibration signal data which is quite difficult. Finally, the particle swarm optimized BiLSTM model is used to predict the health state of key components and the bearing dataset from the IEEE PHM 2012 Data Challenge verifies the method’s effectiveness and validity.

A Finite-Time Control Design for the Discrete-Time Chaotic Logistic Equations

Finite-time control theory has been widely used as a mathematical tool to design robust controllers. By manipulating the finite-time convergence proof of this theory, we developed a new control design appropriately tuned for the finite-time control of the chaotic logistics system. In this experimental setup, the logistic equation is programmed into a PIC microcontroller, and a part of the controller was conceived using analog electronics. Because the system to be controlled is in the discrete-time domain, and the finite-time stability proof is stated in the continuous-time representation, our finite-time control approach is a good example for designing control algorithms in both time domain schemes. Hence, our experimental results support our main contribution. Pulse width modulation (PWM) is the format used to translate digital signals into the continuous-time field. Therefore, the main contribution of this article is the theoretical foundations for creating a recent controller that satisfies the convergence criterion in finite time and its construction using an 8-bit microcontroller. All this contributes to the chaotic logistical map.

Diagnostics on Power Electronics Converters by Means of Autoregressive Modelling

Power conversion systems for wireless power transfer (WPT) applications have demanding requirements for continuity of service, besides being operated with stressing environmental conditions. Diagnostic and prognostic programs are thus quite useful and this work shows a novel approach based on the analysis of spectra of an autoregressive (AR) model to recognize a wide range of faulty devices, including incipient faults, when deviations from nominal parameters begin to manifest. AR modeling provides cleaner and easier to interpret spectra, where only the salient features remain, and they are more sensitive to variations in the corresponding time domain waveforms. A log spectral distance is calculated that successfully separates healthy and faulty states of the feeding single-phase inverter, even in challenging scenarios of poor signal-to-noise ratio.

Prospects for Time-Domain and Multi-Messenger Science with AXIS

The Advanced X-ray Imaging Satellite (AXIS) promises revolutionary science in the X-ray and multi-messenger time domain. AXIS will leverage excellent spatial resolution (<1.5 arcsec), sensitivity (80× that of Swift), and a large collecting area (5–10× that of Chandra) across a 24-arcmin diameter field of view at soft X-ray energies (0.3–10.0 keV) to discover and characterize a wide range of X-ray transients from supernova-shock breakouts to tidal disruption events to highly variable supermassive black holes. The observatory’s ability to localize and monitor faint X-ray sources opens up new opportunities to hunt for counterparts to distant binary neutron star mergers, fast radio bursts, and exotic phenomena like fast X-ray transients. AXIS will offer a response time of <2 h to community alerts, enabling studies of gravitational wave sources, high-energy neutrino emitters, X-ray binaries, magnetars, and other targets of opportunity. This white paper highlights some of the discovery science that will be driven by AXIS in this burgeoning field of time domain and multi-messenger astrophysics. This White Paper is part of a series commissioned for the AXIS Probe Concept Mission; additional AXIS White Papers can be found at the AXIS website.

Generation of Soliton Frequency Combs in NEMS.

In this study, we present an innovative approach leveraging combination internal resonances within a NEMS platform to generate mechanical soliton frequency combs (FCs) spanning a broad spectrum. In the time domain, the FCs take the form of a periodic train of narrow pulses, a highly coveted phenomenon within the realm of nonlinear wave-matter interactions. Our method relies on an intricate interaction among multiple vibration modes of a bracket-nanocantilever enabled by the strong nonlinearity of the electrostatic field. Through numerical simulation and experimental validation, we demonstrate that by amplifying the motions of the NEMS with the external electrostatic forcing tuned to excite the superharmonic resonance of order-n of the fundamental mode and exploiting combination internal resonances, we can generate multiple stable localized mechanical wave packets with different lobe sizes embodying soliton states I and II. This represents a significant breakthrough with profound implications for quantum computing and metrology.

Thermal emitter performance of ultra-broadband solar metamaterial absorber based on metal-insulator-metal device structure

In this paper, we have designed a solar absorber with ultra-broadband absorption. The structure has seven layers with a metal-dielectric periodic film stack and a metallic copper substefficiency. The metal-dielectric periodic membrane stack and the dielectric are continuous to form a metal/dielectric composite microstructure. It has a very high absorption efficiency at 280 nm–2893 nm. The absorption efficiency in this wavelength range is 96.26% and absorption efficiency at AM 1.5 is up to 95.66% by finite difference time domain method (FDTD) simulation. The thermal radiation absorption efficiency of the structure is 93.69% at 1000K and 94.5% at 1200 K, which can also be used in the manufacture of the heat sink due to its high thermal radiation absorption efficiency. Our proposed solar absorber has good incidence angle insensitivity (0°–60°) and good polarization independence (0°–90°). These advantages enable our absorbers to be widely used for solar absorption and emission and offer a variety of design options for ideal absorbers.

Light-trapping by wave interference in intermediate-thickness silicon solar cells

The power conversion efficiency of crystalline silicon (c − Si) solar cells have witnessed a 2.1% increase over the last 25 years due to improved carrier transport. Recently, the conversion efficiency of c − Si cell has reached 27.1% but falls well below the Shockley-Queisser limit as well as the statistical ray-optics based 29.43% limit. Further improvement of conversion efficiency requires reconsideration of traditional ray-trapping strategies for sunlight absorption. Wave-interference based light-trapping in photonic crystals (PhC) provides the opportunity to break the ray-optics based 4n 2 limit and offers the possibility of conversion efficiencies beyond 29.43% in c − Si cells. Using finite difference time domain simulations of Maxwell’s equations, we demonstrate photo-current densities above the 4n 2 limit in 50 − 300µm-thick inverted pyramid silicon PhCs, with lattice constant 3.1µm. Our 150µm-thick PhC design yields a maximum achievable photo-current density (MAPD) of 45.22mA/cm 2. We consider anti-reflection coatings and surface passivation consisting of SiO 2 − SiN x − Al 2 O 3 stacks. Our design optimization shows that a 80 − 120 − 150nm stack leads to slightly better solar light trapping in photonic crystal cells with thicknesses <50µm, whereas the 80 − 40 − 20nm stack performs better for cells with thicknesses >100µm. We show that replacing SiN x with SiC may improve the MAPD for PhC cells thinner than 100µm. For a fixed lattice constant of 3.1µm, we find no significant improvement in the solar absorption for 50 and 100µm-thick cells relative to a 15µm cell. A substantial improvement in the MAPD is observed for the 150µm cell, but there is practically no improvement in the solar light absorption beyond 150µm thickness.

Highly Stable CsPbBr3@MoS2 Nanostructures: Synthesis and Optoelectronic Properties Toward Implementation into Solar Cells.

Halide perovskites (HPs) have gained significant interest in the scientific and technological sectors due to their unique optical, catalytic, and electrical characteristics. However, the HPs are prone to decomposition when exposed to air, oxygen, or heat. The instability of HP materials limits their commercialization, prompting significant efforts to address and overcome these limitations. Transition metal dichalcogenides, such as MoS2, are chemically stable and are suitable for electronic, optical, and catalytic applications. Moreover, it can be used as a protective media or shell for other nanoparticles. In this study, a novel CsPbBr3@MoS2 core-shell nanostructure (CS-NS) is successfully synthesized by enveloping CsPbBr3 within a MoS2 shell for the first time. Significant stability of CS-NSs dispersed in polar solvents for extended periods is also demonstrated. Remarkably, the hybrid CS-NS exhibits an absorption of MoS2 and quenching of the HP's photoluminescence, implying potential charge or energy transfer from HPs to MoS2. Using finite difference time domain simulations, it is found that the CS-NSs can be utilized to produce efficient solar cells. The addition of a MoS2 shell enhances the performance of CS-NS-based solar cells by 220% compared to their CsPbBr3 counterparts. The innovative CS-NS represents important progress in harnessing HPs for photovoltaic and optoelectronic applications.

PREDICTION OF CRACK PLANE ORIENTATION IN RAILWAY WHEELS FOR DIFFERENT BRAKING CONDITIONS

In In this paper the stress analysis of a railway wheel is introduced. The wheel was analysed by Finite element method (FEM) under different service conditions during the braking process, which means that the friction coefficient and the relative speed between the wheel and rail were altered, creating 22 different loading conditions. Stress and strain histories were evaluated in the time domain during rolling, and the fatigue parameter was used to find the critical plane in each condition. The orientation of this critical plane was used to predict the crack propagation direction and the possible fatigue mode of the wheel. Relying on the results a critical plane map was created to visualize the possible fracture modes of the wheel under different loading conditions.