Operational Timescales Research Articles

Dynamic On-State Resistance and Threshold-Voltage Instability in SiC MOSFETs

Dynamic on-state resistance has been experimentally observed in all commercially-available SiC MOSFETs studied on the time scale of normal device operation, and can be explained by the presence of dynamic threshold-voltage instability. The magnitude of this dynamic on-state resistance varies from vendor to vendor, but in every case this magnitude generally corresponds to the magnitude of that device’s threshold-voltage instability, as described by standard textbook equations-especially in the case of large threshold-voltage instabilities.

Unveiling the environmental significance of acetylperoxyl radical: Reactivity quantification and kinetic modeling.

Acetylperoxyl radical (CH3C(O)OO•) is among highly reactive organic radicals which are known to play crucial roles in atmospheric chemistry, aqueous chemistry and, most recently, peracetic acid (PAA)-based advanced oxidation processes. However, fundamental knowledge for its reactivity is scarce and severely hampers the understanding of relevant environmental processes. Herein, three independent experimental approaches were exploited for revelation and quantification of the reaction rates of acetylperoxyl radical. First, we developed and verified laser flash photolysis of biacetyl, ultraviolet (UV) photolysis of biacetyl, and pulse radiolysis of acetaldehyde, each as a clean source of CH3C(O)OO•. Then, using competition kinetics and selection of suitable probe and competitor compounds, the rate constants between CH3C(O)OO• and compounds of diverse structures were determined. The three experimental approaches complemented in reaction time scale and ease of operation, and provided cross-validation of the rate constants. Moreover, the formation of CH3C(O)OO• was verified by spin-trapped electron paramagnetic resonance, and potential influence of other reactive species in the systems was assessed. Overall, CH3C(O)OO• displays distinctively high reactivity and selectivity, reacting especially favorably with naphthyl and diene compounds (k ∼ 107-108 M-1 s-1) but sluggishly with N- and S-containing groups. Significantly, we demonstrated that incorporating acetylperoxyl radical-oxidation reactions significantly improved the accuracy in modeling the degradation of environmental micropollutants by UV/PAA treatment. This study is among the most comprehensive investigation for peroxyl radical reactivity to date, and establishes a robust methodology for investigating organic radical chemistry. The determined rate constants strengthen kinetic databases and improve modeling accuracy for natural and engineered systems.

Electroluminescence Rectification and High Harmonic Generation in Molecular Junctions.

The field of molecular electronics has emerged from efforts to understand electron propagation through single molecules and to use them in electronic circuits. Serving as a testbed for advanced theoretical methods, it reveals a significant discrepancy between the operational time scales of experiments (static to GHz frequencies) and theoretical models (femtoseconds). Utilizing a recently developed time-linear nonequilibrium Green function formalism, we model molecular junctions on experimentally accessible time scales. Our study focuses on the quantum pump effect in a benzenedithiol molecule connected to two copper electrodes and coupled with cavity photons. By calculating both electric and photonic current responses to an ac bias voltage, we observe pronounced electroluminescence and high harmonic generation in this setup. The mechanism of the latter effect is more analogous to that from solids than from isolated molecules, with even harmonics being suppressed or enhanced depending on the symmetry of the driving field.

A finite-time quantum Otto engine with tunnel coupled one-dimensional Bose gases

We undertake a theoretical study of a finite-time quantum Otto engine cycle driven by inter-particle interactions in a weakly interacting one-dimensional (1D) Bose gas in the quasicondensate regime. Utilizing a c-field approach, we simulate the entire Otto cycle, i.e. the two work strokes and the two equilibration strokes. More specifically, the interaction-induced work strokes are modelled by treating the working fluid as an isolated quantum many-body system undergoing unitary evolution. The equilibration strokes, on the other hand, are modelled by treating the working fluid as an open quantum system tunnel-coupled to another quasicondensate which acts as either the hot or cold reservoir, albeit of finite size. We find that, unlike a uniform 1D Bose gas, a harmonically trapped quasicondensate cannot operate purely as a heat engine; instead, the engine operation is enabled by additional chemical work performed on the working fluid, facilitated by the inflow of particles from the hot reservoir. The microscopic treatment of dynamics during equilibration strokes enables us to evaluate the characteristic operational time scales of this Otto thermochemical engine, crucial for characterizing its power output, without any ad hoc assumptions about typical thermalization timescales. We analyse the performance and quantify the figures of merit of the proposed Otto thermochemical engine, finding that it offers a favourable trade-off between efficiency and power output, particularly when the interaction-induced work strokes are implemented via a sudden quench. We further demonstrate that in the sudden quench regime, the engine operates with an efficiency close to the near-adiabatic (near maximum efficiency) limit, while concurrently achieving maximum power output.

Combining Liquid Chromatography and Cryogenic IR Spectroscopy in Real Time for the Analysis of Oligosaccharides.

While the combination of liquid chromatography (LC) and mass spectrometry (MS) serves as a robust approach for oligosaccharide analysis, it has difficulty distinguishing the smallest differences between isomers. The integration of infrared (IR) spectroscopy within a mass spectrometer as an additional analytical dimension can effectively address this limitation by providing a molecular fingerprint that is unique to each isomer. However, the direct interfacing of LC-MS with IR spectroscopy presents a technical challenge arising from the mismatch in the operational time scale of each method. In previous studies, this temporal incompatibility was mitigated by employing strategies designed to slow down or broaden the LC elution peaks of interest, but this workaround is applicable only for a few species at a time, necessitating multiple LC runs for comprehensive analysis. In the current work, we directly couple LC with cryogenic IR spectroscopy by acquiring a spectrum in as little as 10 s. This allows us to generate an orthogonal data dimension for molecular identification in the same amount of time that it normally takes for LC analysis. We successfully demonstrate this approach on a commercially available human milk oligosaccharide product, acquiring spectral information on the eluting peaks in real time and using it to identify both the specified constituents and nonspecified product impurities.

RoCoF Constrained Unit Commitment Considering Spatial Difference in Frequency Dynamics

The post-disturbance rate of change of frequency (RoCoF) is a critical index for low-inertia power system frequency stability. This paper proposes a RoCoF constrained unit commitment model so as to enhance the frequency stability in operation time-scale, where the spatial difference in frequency dynamics is considered and the RoCoF constraint is enforced for each node. The maximum of node RoCoF is approximated by two terms, i.e., the initial post-disturbance node RoCoF and the maximum of the center of inertia (COI) RoCoF. Analytical expressions of the node initial RoCoF under typical disturbances are derived. Then, a tractable relationship between the node initial RoCoF and the working status of generators is obtained by the piecewise linearization approach. Simulation results carried out on the IEEE 39-bus system demonstrate the proposed model can limit the node RoCoF in an economic and accurate manner. The adaptability to renewable power generation and online application are also discussed.

High-Throughput Screening of Molecules for Flow Batteries

Development of next generation stationary energy storage technologies is of crucial importance for increasing the share of the intermitted renewable electricity generation in the world. Traditional trial and error based approach for discovery of novel materials is very slow, so we have been thinking of how to accelerate the process. Some crucial parameters such as redox potentials can be readily evaluated with computational tools, such as those developed in our CompBat project [1], [2], but other parameters such as stability are more difficult to be evaluated. In this work we will demonstrate our web-based application for evaluating redox potentials of molecules from the SMILES structure, illustrating very impressive or problematic performance depending on the training data used for the model.For the question of stability, we believe that sufficient quantity of experimental data is required for training of specific machine learning models for stability prediction. For this purpose, we will illustrate our experimental approach for high-throughput electrochemistry, to evaluate the stability of molecules in the time-scale of voltammetry. Moreover, we will discuss the order of magnitude of the kinetics of the decomposition reactions that can be evaluated by voltammetry, and illustrate that voltammetry is a good tool for roughly separating more stable species from the less stable, but other techniques are required for evaluating stability in the time scale of battery operation.References https://compbat.eu/A. Hamza, F.B. Németh, Á. Madarász, A. Nechaev, P. Pihko, P. Peljo, I. Pápai, N-alkylated pyridoxal derivatives as negative electrolyte materials for aqueous organic flow batteries: Computational screening, 10.26434/chemrxiv-2023-bzc6w

A comparative study of robot-assisted and traditional surgeries in the treatment of thoracolumbar fractures based on 1-year follow-up observation.

There are conflicting results for robot-assisted (RA) pedicle screw fixation compared with freehand (FH) pedicle screw fixation. This study was designed to retrospectively compare the accuracy and efficacy of RA percutaneous pedicle screw fixation and traditional freehand FH pedicle screw fixation in the treatment of thoracolumbar fractures. A total of 26 cases were assigned to the RA group, and 24 cases were assigned to the FH group. The operation time, bleeding volume, and visual analog scale (VAS) score 1 day after the operation, and the anterior/posterior (A/P) vertebral height ratio of the injured vertebrae at 3 days and at internal fixation removal 1 year after the operation were compared between the two groups. Pedicle screw position accuracy was assessed according to Gertzbein criteria. The operation times of the RA group and FH group were 138.69 ± 32.67 minutes and 103.67 ± 14.53 minutes, respectively, and the difference was statistically significant. The intraoperative blood loss was 49.23 ± 22.56 ml in the RA group and 78.33 ± 23.90 ml in the FH group, and the difference was statistically significant. There was a significant difference in the A/P vertebral height ratio of the injured vertebrae 3 days after the operation compared with before the operation in both groups (P <0.05). There was a significant difference in the A/P vertebral height ratio of the injured vertebrae 3 days after the operation compared with that at fixation removal in both groups (P <0.05). The application of RA orthopedic treatment for thoracolumbar fractures can achieve good fracture reduction.

Short- and long-duration cooperative energy storage system: Optimizing sizing and comparing rule-based strategies

Reasonable configuration of energy storage equipment could solve the mismatch problem between load demand and renewable power output. The energy storage devices could be classified into short-duration and long-duration storage according to the operation timescale. Short- and long-duration cooperative energy storage is a promising trend because of its complementary advantages. This work focuses on the systems of photovoltaics and wind farms combined with energy storage components, such as batteries, thermal energy storage (TES), and hydrogen energy storage (HS). The optimal design parameters are obtained by multi-objective optimization with the objective of levelized cost of energy and loss of power supply probability. The techno-economic performance of different short- and long-term cooperative energy storage systems are compared. The influence of rule-based strategies on the system performance is investigated. Results indicate that the system with batteries and TES has great competitiveness from an economic perspective, and the system with batteries and HS has a lower potential energy waste probability when the power-supply reliability is extremely high. The recommended discharging priority of the system with batteries and TES is TES first and then batteries, which could completely achieve power supply reliability.

Perspectives on Distribution Network Flexible and Curtailable Resource Activation and Needs Assessment

A curtailable and flexible resource activation framework for solving distribution network (DN) voltage and thermal congestions is used to quantify three important aspects with respect to modelling low voltage networks. This framework utilizes the network states in the absence of such flexible or curtailable resources as the input for calculating flexibility activation signal (FAS). The FAS has some similarities with optimal power flow duals associated with power balance constraint. FAS due to drooping design, incentivize corrective flexibility activation prior to any network limit violations. The nonlinear resource dispatch optimal power flow (RDOPF) utilizes FAS for the activation of flexible and curtailable resources. Solving the OPF problem for a large system is computationally intensive, and second-order cone (SOC) relaxation is often applied in the literature. First, we highlight the multi-objective nature of SOC relaxed RDOPF. A Pareto front tuning mechanism is proposed for choosing loss penalty factor while reducing the optimality gap of the SOC relaxed RDOPF. Secondly, we present a methodology for evaluating temporal and locational flexibility needs assessment of a DN, which DSO's can utilize for flexibility planning in operational timescales and procurement in the flexibility market. Lastly, we quantify the impact of reactive power flexibility for a DN with varying load power factors. Numerical simulations indicate that the presence of reactive flexibility reduces the active power flexibility needs by 50% for the test feeder with 0.8 aggregated load power factor.

Optimal allocation of energy storage in distribution network considering microgrid cluster and system economic operation

A two-stage optimization model for the location of distribution grid energy storage (ES) configuration and its capacity determination is proposed for different operating conditions of the distribution grid, consider the impact of microgrid cluster operation strategies and sub-microgrid cooperation on the distribution network (DN). In the first stage, location, number of ES devices, the charging/discharging strategy were solved for using GAMS software, the minimum operating cost of the distribution system is used as the target for the daily operating timescale. In the second stage, the minimum annual operating cost is taken as the target for a one-year time scale, consisting of investment, ES equipment’s operation and maintenance in the DN, and is solved using a particle swarm optimisation algorithm with nested ES lifetime calculations in MATLAB software. The calculations show that the optimal allocation method of ES equipment in DN can effectively reduce the operating costs of DN as well as the investment and maintenance costs of ES under different operating conditions, taking into account the economic operation of microgrid clusters and distribution systems. As a result, the economy of the DN can be substantially improved.

Experimental verification of arcsine laws in mesoscopic nonequilibrium systems.

A large number of processes in the mesoscopic world occur out of equilibrium, where the time evolution of a system becomes immensely important since it is driven principally by dissipative effects. Nonequilibrium steady states (NESS) represent a crucial category in such systems, where relaxation timescales are comparable to the operational timescales. In this study, we employ a model NESS stochastic system, which is comprised of a colloidal microparticle optically trapped in a viscous fluid, externally driven by a temporally correlated noise, and show that time-integrated observables such as the entropic current, the work done on the system or the work dissipated by it, follow the three Lévy arcsine laws [A.C. Barato et al., Phys. Rev. Lett. 121, 090601 (2018)0031-900710.1103/PhysRevLett.121.090601], in the large time limit. We discover that cumulative distributions converge faster to arcsine distributions when it is near equilibrium and the rate of entropy production is small, because in that case the entropic current has weaker temporal autocorrelation. We study this phenomenon by changing the strength of the added noise as well as by perturbing our system with a flow field produced by a microbubble at close proximity to the trapped particle. We confirm our experimental findings with theoretical simulations of the systems. Our work provides an interesting insight into the NESS statistics of the meso-regime, where stochastic fluctuations play a pivotal role.

Diagonal Stability of Systems With Rank-1 Interconnections and Application to Automatic Generation Control in Power Systems

We study a class of matrices with a rank-1 interconnection structure, and derive a simple necessary and sufficient condition for diagonal stability. The underlying Lyapunov function is used to provide sufficient conditions for diagonal stability of approximately rank-1 interconnections. The main result is then leveraged as a key step in a larger stability analysis problem arising in power systems control. Specifically, we provide the first theoretical stability analysis of automatic generation control (AGC) in an interconnected nonlinear power system. Our analysis is based on singular perturbation theory, and provides theoretical justification for the conventional wisdom that AGC stabilizes under the typical time-scales of operation. We illustrate how our main analysis results can be leveraged to provide further insight into the tuning and dynamic performance of AGC.

Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model

The identification of appropriate locations for wind energy development is a complex problem that involves several factors, ranging from technical to socio-economic and environmental aspects. Wind energy site selection is generally associated with high degrees of uncertainty due to the long planning, design, construction, and operational timescales. Thus, there is a crucial need to develop efficient methods that are capable of capturing uncertainties in subjective assessments provided by different stakeholders with diverse views. This paper proposes a novel multi-criteria decision model integrating the fuzzy analytic network process (FANP) and the fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to evaluate and prioritize the potential sites for wind power development. Four major criteria, namely economic, social, technical, and geographical, with nine sub-criteria are identified based on consultation with wind farm investors, regulatory bodies, landowners and residents, developers and operators, component suppliers, ecologists, and GIS analysts. The stakeholders’ preferences regarding the relative importance of criteria are measured using a logarithmic least squares method, and then the alternative sites are prioritized based on their relative closeness to the positive ideal solution. The proposed model is applied to determine the most appropriate site for constructing an onshore wind power plant consisting of 10 wind turbines of 2.5 MW. Finally, the results are discussed and compared with those obtained using the traditional AHP, ANP and ANP-TOPSIS decision-making approaches.

Searching for Broadband Pulsed Beacons from 1883 Stars Using Neural Networks

The search for extraterrestrial intelligence at radio frequencies has largely been focused on continuous-wave narrowband signals. We demonstrate that broadband pulsed beacons are energetically efficient compared to narrowband beacons over longer operational timescales. Here, we report the first extensive survey searching for such broadband pulsed beacons toward 1883 stars as a part of the Breakthrough Listen’s search for advanced intelligent life. We conducted 233 hr of deep observations across 4–8 GHz using the Robert C. Byrd Green Bank Telescope and searched for three different classes of signals with artificial (or negative) dispersion. We report a detailed search—leveraging a convolutional neural network classifier on high-performance GPUs—deployed for the very first time in a large-scale search for signals from extraterrestrial intelligence. Due to the absence of any signal-of-interest from our survey, we place a constraint on the existence of broadband pulsed beacons in our solar neighborhood: ≲1 in 1000 stars have transmitter power densities ≳105 W Hz−1 repeating ≤500 s at these frequencies.

Fusion rules in a Majorana single-charge transistor

A demonstration of the theoretically predicted non-abelian properties of Majorana bound states (MBSs) would constitute a definite proof of a topological superconducting phase. Alongside the nontrivial braiding statistics, the fusion rules are fundamental properties of all non-abelian anyons. In this work, we propose and theoretically analyze a way to demonstrate MBS fusion rules in a Majorana single-charge transistor. Our proposal reduces both the number of operations and the device complexity compared to previous designs. Furthermore, we show that the fusion protocol can be adapted to pump a quantized amount of charge in each cycle, providing a straightforward method to detect fusion rules through a DC current measurement. We analyze the protocol numerically and analytically and show that the required operational timescales and expected measurement signals are within experimental capabilities in various superconductor-semiconductor hybrid platforms.

Short-Term Postoperative Pain and Function of Unilateral Biportal Endoscopic Discectomy versus Percutaneous Endoscopic Lumbar Discectomy for Single-Segment Lumbar Disc Herniation: A Systematic Review and Meta-analysis.

Objective Spinal surgery is gradually moving toward minimally invasive surgery, but there is still some lack of knowledge about the Unilateral Biportal Endoscopic (UBE) technique that has been hotly debated in recent years. We performed this systematic review and meta-analysis to clarify whether UBE is superior to percutaneous endoscopic lumbar discectomy (PELD) for relieving short-term postoperative pain and promoting functional recovery. Methods Computer searches of PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang databases were performed to search for studies on UBE versus PELD for single-segment lumbar disc herniation (ssLDH) from the time of database construction to Mar. 2022, and two investigators independently performed literature screening and data extraction, and evaluation of the quality of the included studies was observed as operation time, complications, and visual analogue scale (VAS) at each preoperative and postoperative stage as well as Oswestry Disability Index (ODI), and meta-analysis was performed by applying the Review Manager 5.4 software. Results Meta-analysis showed that PELD had shorter operation time (MD = 35.36, 95% CI (4.67, 66.04), P = 0.02) and had lower VAS of back pain at 3 days postoperatively (MD = 0.62, 95% CI (0.04, 1.19), P = 0.04) compared to the UBE. However, there was no statistical significance between the two groups in terms of complications (MD = 2.53, 95% CI (0.40, 16.11), P = 0.33), VAS of back pain at 30 days postoperatively (MD = 0.05, 95% CI (-0.19, 0.28), P = 0.70), VAS of leg pain at 3 days postoperatively (MD = 0.21, 95% CI (-0.20, 0.61), P = 0.33), VAS of leg pain at 30 days postoperatively (MD = 0.09, 95% CI (-0.29, 0.46), P = 0.65), and ODI at 30 days postoperatively (MD = −0.81, 95% CI (-3.03, 1.41), P = 0.47). Conclusions Current evidence suggests that both UBE and PELD are effective in relieving short-term postoperative pain and promoting functional recovery, and there is no difference in complications between them; UBE requires longer operation time, and PELD may be superior in relieving immediate postoperative pain. This trial is registered with PROSPERO ID: CRD42021287810.

Controlling the dynamics of ultracold polar molecules in optical tweezers

Ultracold molecules trapped in optical tweezers show great promise for the implementation of quantum technologies and precision measurements. We study a prototypical scenario where two interacting polar molecules placed in separate traps are controlled using an external electric field. This, for instance, enables a quantum computing scheme in which the rotational structure is used to encode the qubit states. We estimate the typical operation timescales needed for state engineering to be in the range of few microseconds. We further underline the important role of the spatial structure of the two-body states, with the potential for significant gate speedup employing trap-induced resonances.

Trends in Intelligent Communication Systems: Review of Standards, Major Research Projects, and Identification of Research Gaps

The increasing complexity of communication systems, following the advent of heterogeneous technologies, services and use cases with diverse technical requirements, provide a strong case for the use of artificial intelligence (AI) and data-driven machine learning (ML) techniques in studying, designing and operating emerging communication networks. At the same time, the access and ability to process large volumes of network data can unleash the full potential of a network orchestrated by AI/ML to optimise the usage of available resources while keeping both CapEx and OpEx low. Driven by these new opportunities, the ongoing standardisation activities indicate strong interest to reap the benefits of incorporating AI and ML techniques in communication networks. For instance, 3GPP has introduced the network data analytics function (NWDAF) at the 5G core network for the control and management of network slices, and for providing predictive analytics, or statistics, about past events to other network functions, leveraging AI/ML and big data analytics. Likewise, at the radio access network (RAN), the O-RAN Alliance has already defined an architecture to infuse intelligence into the RAN, where closed-loop control models are classified based on their operational timescale, i.e., real-time, near real-time, and non-real-time RAN intelligent control (RIC). Different from the existing related surveys, in this review article, we group the major research studies in the design of model-aided ML-based transceivers following the breakdown suggested by the O-RAN Alliance. At the core and the edge networks, we review the ongoing standardisation activities in intelligent networking and the existing works cognisant of the architecture recommended by 3GPP and ETSI. We also review the existing trends in ML algorithms running on low-power micro-controller units, known as TinyML. We conclude with a summary of recent and currently funded projects on intelligent communications and networking. This review reveals that the telecommunication industry and standardisation bodies have been mostly focused on non-real-time RIC, data analytics at the core and the edge, AI-based network slicing, and vendor inter-operability issues, whereas most recent academic research has focused on real-time RIC. In addition, intelligent radio resource management and aspects of intelligent control of the propagation channel using reflecting intelligent surfaces have captured the attention of ongoing research projects.

Skyrmion Qubits: A New Class of Quantum Logic Elements Based on Nanoscale Magnetization.

We introduce a new class of primitive building blocks for realizing quantum logic elements based on nanoscale magnetization textures called skyrmions. In a skyrmion qubit, information is stored in the quantum degree of helicity, and the logical states can be adjusted by electric and magnetic fields, offering a rich operation regime with high anharmonicity. By exploring a large parameter space, we propose two skyrmion qubit variants depending on their quantized state. We discuss appropriate microwave pulses required to generate single-qubit gates for quantum computing, and skyrmion multiqubit schemes for a scalable architecture with tailored couplings. Scalability, controllability by microwave fields, operation time scales, and readout by nonvolatile techniques converge to make the skyrmion qubit highly attractive as a logical element of a quantum processor.