Power Routing Research Articles

Optimizing Disaster Response: OptiDrone- Advanced Integration of Dijkstra's Algorithm and Cutting-Edge Software Solutions for UAV Path Planning and Obstacle Avoidance Efficiency

The objective of the research is development of a specific concept called "OptiDrone," which is based on the integration of Dijkstra's Algorithm and the latest development of aerial vehicles' path planning and obstacle avoidance efficacy. The study involves a combination of theoretical and algorithmic refinement as well simulation-based experiments to test the effectiveness of OptiDrone in dynamic disaster scenarios. OptiDrone's combination of powerful route planning techniques along with advanced software programs is set to achieve a substantially higher response rate and operational resilience in the face of difficulties. The results add much value to the body of knowledge about UAV-assisted disaster management systems, indicating possible gains in efficiency and timeliness while addressing crisis situations. Different disciplines of disaster management, robotics, and software engineering can benefit from this research, which is a significant milestone towards the use of more efficient and innovative unmanned aerial systems in disaster response.

Interrupted SNAr-Alkylation Dearomatization.

Dearomatizations provide powerful synthetic routes to rapidly assemble substituted carbocycles and heterocycles found in a plethora of bioactive molecules. Harnessing the advantages of dearomatization typically requires vigorous reagents because of the difficulty in disrupting the stable aromatic core. A relatively mild dearomatization strategy is described that employs lithiated nitriles or isocyanides in a simple SNAr-type addition to form σ-complexes that are trapped by alkylation. The dearomatizations are diastereoselective and efficient and rapidly install two new carbon-carbon bonds, one of which is a quaternary center, as well as nitrile, isocyanide, and cyclohexadiene functionalities.

Pd-Catalyzed Cascade Cyclization/Thiocarbonylation with Thioformates: Synthesis of Thioester-Functionalized Oxindoles.

A Pd-catalyzed thiocarbonylative cyclization of N-(o-iodoaryl)acrylamides with easily accessible thioformates has been developed. The reaction has a wide substrate scope with good yields and represents a powerful route to the synthesis of thioester-functionalized oxindoles. Both S-aryl and alkyl thioformates as the thioester sources were well tolerated. The active Pd-CO intermediate may play an important role in the transformation process.

Monitoring the Evolution of Relative Product Populations at Early Times during a Photochemical Reaction.

Identifying multiple rival reaction products and transient species formed during ultrafast photochemical reactions and determining their time-evolving relative populations are key steps toward understanding and predicting photochemical outcomes. Yet, most contemporary ultrafast studies struggle with clearly identifying and quantifying competing molecular structures/species among the emerging reaction products. Here, we show that mega-electronvolt ultrafast electron diffraction in combination with ab initio molecular dynamics calculations offer a powerful route to determining time-resolved populations of the various isomeric products formed after UV (266 nm) excitation of the five-membered heterocyclic molecule 2(5H)-thiophenone. This strategy provides experimental validation of the predicted high (∼50%) yield of an episulfide isomer containing a strained three-membered ring within ∼1 ps of photoexcitation and highlights the rapidity of interconversion between the rival highly vibrationally excited photoproducts in their ground electronic state.

Simplified control of TAB converter for scalable multibattery charging system

SummaryThe integration of distributed energy resources (DERs) into DC microgrids has become commonplace in many applications, including electric vehicle (EV) systems that use batteries, fuel cells, and supercapacitors as energy storage systems. To make a sustainable charging system for electric vehicles, DERs can be used in conjunction with the grid. In many cases, charging systems based on isolated DC‐DC converters, such as the dual active bridge (DAB) converter, with various controls, are typically used. However, integrating multiple DERs at the common input DC link can result in a loss of isolation in the DAB converter and also leads to problems with circulating current. To maintain isolation, multiple DAB converters can be used, but this increases the system's size. Alternatively, the multiport isolated DC‐DC converter can address such issues but introduces complexities such as cross‐coupling between power flow. This paper proposes a hardware decoupling control methodology for a triple active bridge (TAB) based isolated DC‐DC converter, with power routing features for simultaneously charging two EV's battery stack. Through hardware decoupling control, appropriate passive components are designed and selected to connect with the individual H‐bridges of the TAB for power decoupling. The paper discusses the cross‐coupling issue in the TAB and describes a methodology derived from mathematical expressions for achieving power decoupling. For validation of the control, a 5 kW system is modeled in MATLAB Simulink, and the results demonstrate how the proposed approach overcomes cross‐coupling issues. Further, a 500 W hardware prototype has been developed to validate the proposed approach.

Deep neural network with fuzzy algorithm to improve power and traffic-aware reliable reactive routing

<span>In wireless networks, link breaks, and restricted resources create fundamental challenges for maintaining network applications. Several wireless network routing techniques concentrate on power efficiency to expand the network lifetime, but the traffic and reliability parameters are not the primary concern. Though, these techniques are not capable of dealing with the wireless network. Hence, this paper proposes deep neural network (DNN) with a fuzzy algorithm to improve power and traffic-aware reliable reactive routing (PTAR) in wireless networks. The wireless network is formed by clustering by the node power and selects the cluster head (CH) based on a fuzzy algorithm. The wireless node power level, node buffer space, and node reliability to consider the input parameters of the fuzzy system. Then thefuzzy algorithm gives the output for CH round length. This selected CH improves the node reliability, power efficiency with minimized network congestion. Then we use a DNN algorithm to choose an optimal relay by applying an adaptive load balance factor in the network. DNN is a machine learning algorithm, and it provides high accuracy. From the simulation results, the PTAR approach improves the network performance, such as packet received ratio, delay, residual energy, and routing overhead.</span>

Thermal Control of Quasi-2-Level Super-Switch by Power Routing

The requirement of power converters for Medium Voltage (MV) and High Voltage (HV) applications accelerates faster than the development of semiconductor switches capable of handling such voltage levels. For that reason, it is common to use the series connection of semiconductors with auxiliary snubbers. In contrast, an increased number of semiconductors is more likely to cause reliability problems due to increased redundancy, unequal thermal conditions, or different remaining lifetime. On the other hand, the quasi-2-level super-switch (Q2L SS) yields increased flexibility, enabling precise readjustments of the voltage and switching losses of individual devices of the converter due to the utilization of small capacitors. The power routing capability of the Q2L SS to redistribute the switching losses from the overheated semiconductors is presented in this paper. The influence of power routing on performance of Q2L SS is investigated with the Double Fourier analysis and experimental results.

DEVELOPMENT OF PARAMETERIZED MODEL OF LOGIC ELEMENTS AT CLOCK TREE SYNTHESIS

Clock synthesis, routing optimization, placement and logic optimization are the three primary phases of physical design implementation. Since clock network synthesis uses at least 30% of the entire power budget, it is one of the crucial steps. Power consumption for high-performance blocks can reach 50% of the entire power. Not only would a high-quality clock tree will fix timing violations, but it will also minimize power usage and routing resource use. A new neural network based parameterized model is proposed in this paper, which can be used to obtain not only the list of logic elements, but it also can predict the circuits timing behaviour. Different ICs using SAED 14 and 32 nm technologies are designed using the proposed method.

30 years of PPLN-what is old, what is new, and where next for PPLN and QPM material research?

Since the first demonstration of electric field poling in 1993 - by workers at Sony - periodically poled materials (e.g. PPLN) have become ubiquitous in photonics. Their ability to allow quasi-phase matching opens up nonlinear optics across the full transparency bands of a material. In the case of PPLN this spans from the visible out to around 5 microns – offering a powerful route to create light in spectral regions where convenient lasers do not exist. This talk will cover underlying physics, materials, design, manufacturing and applications, as well as looking at next generation applications.

Electrochemically modulated surface plasmon waves for characterization and interrogation of DNA-based sensors.

This work reports on a comparative analysis of electrical and optical measurements for structural characterization and for assessing signal transduction performance of a redox-labeled DNA-based sensing platform. We conducted complementary investigations employing conventional electrochemical techniques with electric current measurements in cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) and confronted those results with optical measurements using surface plasmon waves while the redox assembly was undergoing similar electrochemical modulation as in the electrical CV and EIS measurements. The specific sensor configuration deployed here was composed of a methylene blue (MB)-modified single-stranded DNA (ssDNA) signaling probe and an unlabeled capture ssDNA probe that complements the signaling probe. Two types of signaling probes were employed: one with MB attached to the 3' end, which positions the redox marker closer to the electrode surface upon hybridization with the capture probe, and the other with MB attached to the 5' end, which places the redox marker farther from the electrode surface. For each molecular assembly and for each electrochemical modulation protocol, both the electrical and optical experimental data were quantitatively analyzed to determine the surface density of electro-active species and the rate of electron transfer between the redox marker and the electrode surface. Our experimental results highlight the consistency of the confronted methodologies and indicate that optical impedance spectroscopy utilizing electrochemically modulated surface plasmon waves, which is a transduction protocol immune from non-faradaic interferents that invariably are present in the electrical methodology, can provide a powerful route for developing a redox-labeled DNA-hybridization biosensing strategy.

Controlling the Charge Density Wave Transition in Single-Layer TiTe2xSe2(1-x) Alloys by Band Gap Engineering.

Closing the band gap of a semiconductor into a semimetallic state gives a powerful potential route to tune the electronic energy gains that drive collective phases like charge density waves (CDWs) and excitonic insulator states. We explore this approach for the controversial CDW material monolayer (ML) TiSe2 by engineering its narrow band gap to the semimetallic limit of ML-TiTe2. Using molecular beam epitaxy, we demonstrate the growth of ML-TiTe2xSe2(1-x) alloys across the entire compositional range and unveil how the (2 × 2) CDW instability evolves through the normal state semiconductor-semimetal transition via in situ angle-resolved photoemission spectroscopy. Through model electronic structure calculations, we identify how this tunes the relative strength of excitonic and Peierls-like coupling, demonstrating band gap engineering as a powerful method for controlling the microscopic mechanisms underpinning the formation of collective states in two-dimensional materials.

Opto-Electrochemical Synaptic Memory in Supramolecularly Engineered Janus 2D MoS2.

Artificial synapses combining multiple yet independent signal processing strategies in a single device are key enabler to achieve high-density of integration, energy efficiency, and fast data manipulation in brain-like computing. By taming functional complexity, the use of hybrids comprising multiple materials as active components in synaptic devices represents a powerful route to encode both short-term potentiation (STP) and long-term potentiation (LTP) in synaptic circuitries. To meet such a grand challenge, herein a novel Janus 2D material is developed by dressing asymmetrically the two surfaces of 2D molybdenum disulfide (MoS2 ) with an electrochemically-switchable ferrocene (Fc)/ ferrocenium (Fc+ ) redox couple and an optically-responsive photochromic azobenzene (Azo). Upon varying the magnitude of the electrochemical stimulus, it is possible to steer the transition between STP and LTP, thereby either triggering electrochemical doping of Fc/Fc+ pair on MoS2 or controlling an adsorption/desorption process of such redox species on MoS2 .In addition, a lower magnitude LTP is recorded by activating the photoisomerization of azobenzene chemisorbed molecules and therefore modulating the dipole-induced doping of the 2D semiconductor. Significantly, the interplay of electrochemical and optical stimuli makes it possible to construct artificial synapses where LTP can be boosted to 4-bit (16 memory states) while simultaneously functioning as STP.

Power-to-liquid versus biomass-derived kerosene: a comparative study

Power-to-Liquid (PtL) kerosene is considered by many experts as the only viable option to achieve a large scale decarbonization of the aviation sector in the near-medium term. In the PtL process carbon dioxide of renewable origin or from ambient air and green hydrogen are combined to produce a liquid fuel that can replace fossil kerosene. For this purpose the Fischer-Tropsch pathway and the methanol pathway are available. On the other hand, more production pathways are available when using a biomass feedstock. The aim of this work is to compare the power and biogenic routes for the production of sustainable kerosene in terms of performance and requirements. Indeed, there is a lack of studies in the literature that directly compare the two options, i.e. biofuels and e-fuels, on a common basis. Accordingly, simulation models are built in this work for both routes to calculate the yield of kerosene and co-products, the hydrogen demand, the flows of carbon dioxide, the electricity and thermal energy demands. The simulation outputs are compared against the results of the relevant studies in the literature. The expectation from this comparative study is to highlight the criticalities of each route and, possibly, any opportunity to overcome them by exploring any synergy between the different routes.

A Routing Algorithm Based on Software-Defined Computing First Network

With the continuous development of mobile Internet technology, new services and applications appear, such as AR/VR, Internet of Vehicles, and Ultra HD Video. They not only require higher network bandwidth resources but also need more computing resources to ensure normal operation and user experience. As a new network technology, computing first network promotes the deep integration of distributed computing resources and networks to make efficient use of these resources. This paper proposes a computing power routing algorithm based on software-defined computing first network (SD-CFN) architecture. It comprehensively considers computing resources and available bandwidth resources of network links. Experimental results show that compared with the nearby scheduling strategy, the proposed computing power routing algorithm can better allocate computing resources to services. Moreover, it can improve the utilization rate of computing resources and provide optimal bandwidth resources in the process of service transmission.

Fullerene Fragment Restructuring: How Spatial Proximity Shapes Defect-Rich Carbon Electrocatalysts.

Fullerene transformation emerges as a powerful route to construct defect-rich carbon electrocatalysts, but the carbon bond breakage and reformation that determine the defect states remain poorly understood. Here, we explicitly reveal that the spatial proximity of disintegrated fullerene imposes a crucial impact on the bond reformation and electrocatalytic properties. A counterintuitive hard-template strategy is adopted to enable the space-tuned fullerene restructuring by calcining impregnated C60 not only before but also after the removal of rigid silica spheres (∼300 nm). When confined in the SiO2 nanovoids, the adjacent C60 fragments form sp3 bonding with adverse electron transfer and active site exposure. In contrast, the unrestricted fragments without SiO2 confinement reconnect at the edges to form sp2-hybridized nanosheets while retaining high-density intrinsic defects. The optimized catalyst exhibits robust alkaline oxygen reduction performance with a half-wave potential of 0.82 V via the 4e- pathway. Copper poisoning affirms the intrinsic defects as the authentic active sites. Density functional theory calculations further substantiate that pentagons in the basal plane lead to localized structural distortion and thus exhibit significantly reduced energy barriers for the first O2 dissociation step. Such space-regulated fullerene restructuring is also verified by heating C60 crystals confined in gallium liquid and a quartz tube.

Multi-Scale Engineered 2D Carbon Polyhedron Array with Enhanced Electrocatalytic Performance.

Electrocatalyst engineering from the atomic to macroscopic level of electrocatalysts is one of the most powerful routes to boost the performance of electrochemical devices. However, multi-scale structure engineering mainly focuses on the range of atomic-to-particle scale such as hierarchical porosity engineering, while catalyst engineering at the macroscopic level, such as the arrangement configuration of nanoparticles, is often overlooked. Here, a 2D carbon polyhedron array with a multi-scale engineered structure via facile chemical etching, ice-templating induced self-assembly, and high-temperature pyrolysis processes is reported. Controlled phytic acid etching of the carbon precursor introduces homogeneous atomic phosphorous and nitrogen doping, as well as a well-defined mesoporous structure. Subsequent ice-templated self-assembly triggers the formation of a 2D particle array superstructure. The atomic-level doping gives rise to high intrinsic activity, while the well-engineered porous structure and particle arrangement addresses the mass transport limitations at the microscopic particle level and macroscopic electrode level. As a result, the as-prepared electrocatalyst delivers outstanding performance toward oxygen reduction reaction in both acidic and alkaline media, which is better than recently reported state-of-the-art metal-free electrocatalysts. Molecular dynamics simulation together with extensive characterizations indicate that the performance enhancement originates from multi-scale structural synergy.

Development of a molecularly imprinted photoelectrochemical sensor for enhanced detection of ciprofloxacin in milk

In this work, a molecularly imprinted polymer (MIP)-based photoelectrochemical (PEC) sensor for the detection of ciprofloxacin (CIP) was constructed. Carbon-modified ZnO (ZnO/C) nanocomposite with adjustable zinc content was prepared by a carbonaceous method, facilitating visible light absorption and electron transition. The structure, morphology, and surface chemistry of ZnO/C were well characterized. The MIP membrane was formed by electropolymerizing, with ZnO/C nanocomposite, o-phenylenediamine (C6H4(NH3)2,o-PD), and CIP as highly efficient photoactive materials, functional monomer, and template, respectively. The PEC properties of different photoactive electrodes were measured and analyzed. The MIP-based PEC sensor showed excellent sensitivity and selectivity towards CIP, displaying a broad linear range from 0.01 nM to 1000 nM, a low detection limit of 8.41 pM, and satisfied recovery rates within 96.8%103.2%. The sensor exhibited reliable reproducibility and stability, with a relative standard deviation (RSD) of 2.48% for the CIP in milk. The constructed MIP-based PEC sensor not only provides a powerful and reliable route for the detection of CIP, but also can be extended to detect other antibiotics in food and natural environment.

Hierarchical porous tannic-acid-modified MOFs/alginate particles with synergized adsorption-photocatalysis for water remediation

Organic dye contaminants pose increasing threats to water ecological systems and global sustainability. Rational development of functional particles with adsorption-catalysis synergy is envisioned as a powerful route for enhanced water remediation. Here, hierarchical porous MOF-integrated alginate particles with synergized adsorption and photocatalytic degradation is developed for effective water remediation. The particles exhibit unique mesh-like Ca-alginate (CaAlg) networks with incorporated macro-/micro-porous zeolitic imidazolate framework-8 (ZIF-8) nanoparticles, both modified with negatively-charged tannic acid (TA). The TA-modified mesh-like CaAlg (CaAlg@TA) networks serve as highly porous absorbents, while the TA-modified ZIF-8 (ZIF-8@TA) nanoparticles serve as both hierarchical porous nano-absorbents and photoactive nano-catalysts. This combination simultaneously harnesses the advantages of CaAlg@TA networks and ZIF-8@TA nanoparticles to achieve adsorption-photocatalysis synergy for efficient water remediation. As demonstrated by removal of toxic and carcinogenic dye methylene blue (MB), these particles show much higher performances with fast adsorption and high capacity (1277 mg g−1), as compared to control group particles without adsorption-photocatalysis synergy. Meanwhile, the adsorption-photocatalysis synergy largely suppresses undesired secondary water contamination from the MB-adsorbed particles, and benefits particle regeneration to achieve good reusability for repeated MB removal (>95.5 % for 10 cycles). This work provides a simple and flexible route for rational fabrication of MOF-integrated particles with adsorption-photocatalysis synergy, and thus may open up new horizons for developing advanced functional particles for effective water remediation.

Power Routing Method Based on Optimization Problem to Improve CHB-DAB Lifetime

Power Routing Method Based on Optimization Problem to Improve CHB-DAB Lifetime

Nitrogen Pretreatment of Growth Substrates for Vacancy-Saturated MoS2.

Two-dimensional transition-metal dichalcogenides (2D TMDCs) are considered promising materials for optoelectronics due to their unique optical and electric properties. However, their potential has been limited by the occurrence of atomic vacancies during synthesis. While post-treatment processes have demonstrated the passivation of such vacancies, they increase process complexity and affect the TMDC's quality. We here introduce the concept of pretreatment as a facile and powerful route to solve the problem of vacancies in MoS2. Low-temperature nitridation of the sapphire substrate prior to growth provides a nondestructive method to MoS2 modification without introducing new processing steps or increasing the thermal budget. Spectroscopic characterization and atomic-resolution microscopy reveal the incorporation of nitrogen from the sapphire surface layer into chalcogen vacancies. The resulting MoS2 with nitrogen-saturated defects shows a decrease in midgap states and more intrinsic doping as confirmed by ab initio calculations and optoelectronic measurements. The demonstrated pretreatment method opens up new routes toward future, high-performance 2D electronics, as evidenced by a 3-fold reduction in contact resistance and a 10-fold improved performance of 2D photodetectors.