Minimum Energy Research Articles

考虑作业工况特性的纯电动园艺作业机械动力传动系统参数匹配方法研究

To meet the economy requirement of the horticultural machinery, a two-speed transmission system was proposed based on the characteristics of the driving cycle of the horticultural machinery. Firstly, the test cycle of the horticultural machinery was established based on the data collector that fixed on the machinery. Secondly, the two-speed driveline system was designed. To reduce the energy consumption in the horticultural machinery working cycle, the gear ratio of the two-speed gear box was optimized with the goal of minimum energy consumption by the Genetic Algorithm. The optimized gear ratio were 11.6 and 9.62. The comparison of energy consumption between single gear ratio and two-speed gear ratio was made. The comparison result showed that the energy consumption can reduce 0.25% under one transportation test condition, the energy consumption can reduce 0.41% under one ploughing test condition, and the energy consumption can reduce 0.41% under one rotary test condition.

Comparative study of atomic models of plastic deformation mechanism in ductile inorganic semiconductors: A theoretical discussion

Recently developed ductile inorganic semiconductors have opened a new avenue toward potential applications such as flexible electronics. Significant studies have been conducted based on different atomic models to understand the deformation mechanism using first-principle calculations; however, the comparative study on these atomic models remains unexplored. In this paper, taking Ag2S as an example, we simulated the slipping process using bulk, slab, and tilt-cell models. Systematic supercell tests were performed to investigate the convergence of the slip/cleavage energy based on the three atomic models. It was found that a reasonably large supercell is required to converge the slip/cleavage energy, and the ratio between minimum cleavage and maximum slip energy converges to a comparable value among different atomic models, where the tilt-cell and slab models show slightly higher energy ratio values compared with the bulk model. However, the comparison of different exchange-correlation functionals and van der Waals corrections indicates that the calculations of slip and cleavage energies are sensitive to the choice of calculation methods, highlighting the importance of using the same method for comparing slip and cleavage energies of different materials. This work provides insights into understanding different atomic models of ductility mechanisms in ductile inorganic semiconductors.

Green Syngas Production from Natural Lignin, Sunlight, and Water over Pt-Decorated InGaN Nanowires.

Transformation of lignin to syngas can turn waste into treasure yet remains a tremendous challenge because of its naturally evolved stubborn structure. In this work, light-driven reforming of natural lignin in water for green syngas production is explored using Pt-decorated InGaN nanowires. The spectroscopic characterizations, isotope, and model compound experiments, as well as density function theory calculation, disclose that among a variety of groups including aromatic ring, -OH, -OCH3, -C3H7 with complex chemical bonds of O-H, C-H, C-C, C-O, etc., InGaN nanowires are cooperative with Pt for preferably breaking the C-O bond of the rich O-CH3 group in lignin to liberating ⋅CH3 by photogenerated holes with a minimum dissociation energy of 2.33 eV. Syngas are subsequently yielded from the continuous evolution of ⋅CH3 and ⋅OH from photocatalytic reforming of lignin in water. Together with the superior optoelectronic attributes of Pt-decorated InGaN nanowires, the evolution rate of syngas approaches 43.4 mol ⋅ g-1 ⋅ h-1 with tunable H2/CO ratios and a remarkable turnover number (TON) of 150, 543 mol syngas per mol Pt. Notably, the architecture demonstrates a high light efficiency of 12.1 % for syngas generation under focused light without any extra thermal input. Outdoor test ascertains the viability of producing syngas with the only inputs of natural lignin, water, and sunlight, thus presenting a low-carbon route for synthesizing transportation fuels and value-added chemicals.

Functionalized MBene, Ti[formula omitted]BX[formula omitted] (X=Si, Ge, P, As) as potential excellent anode materials for lithium and sodium-ion batteries: A first-principles study

In the search for next-generation energy storage devices, superior-performance alternative electrode materials based on two-dimensional materials for rechargeable metal-ion batteries are essential. Here, we explored group III and IV functionalization of 2D Ti2B, Ti2BX2 (X=Si, Ge, P, As) as anode materials for Li and Na ion batteries using first-principles calculations. The structures had excellent metallic properties and demonstrated energetically favorable adsorptions for metal ions. Analyzing charge transfer and electronic band structures, silicon and phosphorous-functionalized Ti2B (Ti2BSi2 and Ti2BP2) showed the most potential. The energy band diagrams showed that both Ti2BSi2 and Ti2BP2 had metallic characteristics after Li and Na-ion adsorption, which offered considerable advantage for rechargeable-ion batteries. The structures exhibited low energy barriers for Li and Na-ion migration. The minimum energy barriers calculated for Na were 0.08 eV for Ti2BSi2 and 0.24 eV for Ti2BP2. Theoretical specific capacity and open circuit voltage were calculated using maximum layer adsorption. For both Li and Na, high values of specific capacity and low values of open circuit voltage (¡ 1 V) were found. Ti2BSi2 had the best performance, with a theoretical specific capacity of 1647.10 and 1317.68 mA h/g for Li and Na, respectively. Its open circuit voltages for Li and Na were 0.65 and 0.38 V. The insights of this study will be beneficial in fabricating high-performing Ti2BX2-based anodes for rechargeable Li and Na ion batteries.

Analytical Solution to Estimate the Effect of Underlying Tunnel Excavations on the Existing Tunnel

ABSTRACTThe tunneling underlying inevitably leads to the displacement of adjacent soil, greatly influencing the deformation of the tunnel above. Most theoretical studies primarily concentrate on analyzing the mechanical equilibrium of individual tunnel sections, ignoring the energy generated by the system during tunnel deformation. Based on this, in view of the energy relationship, the overlying tunnel's deformation is simulated by using the Rayleigh–Ritz method. Further, its potential energy equation can be established based on the Vlasov foundation. The corresponding energy variational solution is solved according to the minimum potential energy principle, leading to an analytical solution for the shield tunneling‐induced overlying tunnel's response. The efficacy of the suggested method is verified by contrasting it with centrifuge experiments and field case studies derived from prior studies. Relative to the Winkler foundation model, which deviated from the suggested approach, the results derived from the suggested method show a closer correlation with the collected measurement data. Further parameter studies show that the vertical clearance and skew angle between two tunnels, the volume loss rate, and elastic modulus are significant factors affecting the tunnel behaviors due to tunneling underneath. The suggested theoretical model can be applied to forecast potential risks that an existing tunnel may encounter during the excavation of a new tunnel underlying in similar engineering projects.

A deep insight of re-entrant martensitic transformation mechanism in Co2Cr(Ga,Si) shape memory alloys

Co2Cr(Ga,Si) shape memory alloys have a wide application temperature range due to the unique re-entrant martensite phase transformation (RMT) behavior. Nevertheless, the microscopic mechanism of RMT remains elusive and unsystematic. The heart of this investigation lies the comprehensive exploration of phase stability, phase transformation path, and martensite slip direction during RMT from martensite (D022-PM) to austenite (L21-FM). In this work, we systematically investigate the re-entrant martensitic transformation of Co2Cr(Ga,Si) SMAs using first-principles methods for the first time. Firstly, the density of states (DOS) calculation indicates that the stability of L21-FM is higher than D022-PM. The charge density calculation further indicates that the bonding strength between Co atoms and Cr (Si) atoms in the L21-FM phase is the highest. In addition, Fermi surface calculation further reveals that phase instability is due to the Fermi surface nesting caused by electron-phonon coupling. Moreover, the minimum energy path was calculated by the G-SSNEB method for the first time, which indicates the RMT can occur. Finally, the calculation of the elastic constants indicates that RMT is caused by the crystal plane slip of the D022-PM phase along the <110> direction. Our calculations provide the electronic-level and thermodynamic mechanism for RMT of Co2Cr(Ga,Si) alloy and shed some light on the revelation of the phase transformation mechanism.

Efficient acceleration of the convergence of the minimum free energy path via a path-planning generated initial guess.

We demonstrate that combining a shifted clustering algorithm with a fast-marching-based algorithm can generate accurate approximations of the minimum energy path (MEP) given a free energy landscape (FEL). Using this approximation as the initial guess for the MEP, followed by further refinement with the string method (referred to as the fast marching tree (FMT)-string combined approach), significantly reduces the number of iterations required for MEP convergence. This approach saves substantial time compared to using linear interpolation (LI) for the initial guess. Our method offers a viable solution for obtaining an effective initial guess of the MEP when an approximate or converged FEL is available. This work highlights the potential of applying FMT-based approaches to extract the MEP in chemical reactions.

Variational approach to learning photonic unitary operators

Structured light, light tailored in its internal degrees of freedom, has become topical in numerous quantum and classical information processing protocols. In this work, we harness the high dimensional nature of structured light modulated in the transverse spatial degree of freedom to realize an adaptable scheme for learning unitary operations. Our approach borrows from concepts in variational quantum computing, where a search or optimization problem is mapped onto the task of finding a minimum ground state energy for a given energy/goal function. We achieve this by a pseudo-random walk procedure over the parameter space of the unitary operation, implemented with optical matrix-vector multiplication enacted on arrays of Gaussian modes by exploiting the partial Fourier transforming capabilities of a cylindrical lens in the transverse degree of freedom for the measurement. We outline the concept theoretically, and experimentally demonstrate that we are able to learn optical unitary matrices for dimensions d = 2, 4, 8, and 16 with average fidelities of &gt;90%. Our work advances high dimensional information processing and can be adapted to both process and quantum state tomography of unknown states and channels.

An overview of the constructions of conveyors for moving bulk materials, comparison and study of their parameters

The production of concrete mixes, along with their use in the production of building materials and structures, is one of the key processes in the construction industry during the construction, restoration and repair of buildings and structures. Because of this, the need to create modern concrete mixing plants that will meet the requirements of minimum energy consumption and maximum productivity of concrete mixture production is an urgent task. Not only the main operations, which include the dosing of the components of the mixture and their mixing, but also the maintenance operations, namely operations that ensure the timely movement of the components of the concrete mixture from warehouses to the main technological equipment, affect the set rhythm of the concrete mixture production. Conveyors of various types and designs are used to move bulk materials, such as crushed stone and sand. For the rational selection of such equipment in accordance with the characteristics of the cargo to be transported, knowledge of the types of conveyors, their structures and parameters, understanding of operation issues and methods of parameter calculation are required. In addition, it is worth paying attention to the following parameters: maximum cargo transportation productivity, low energy consumption per unit of moved products, low metal content of the structure. The work reviewed the most common designs of conveyors used to move bulk materials in concrete mixing plants, analyzed the disadvantages and advantages of conveyors, as well as technical parameters. As a result, the predominant directions for the use of belt and plate conveyors at construction enterprises were determined. The advantages of belt conveyors, which contribute to their widespread distribution, are high productivity, simplicity of design, reliability, quiet operation, low specific power consumption. When choosing a conveyor, it is recommended to choose the equipment with the highest productivity and the lowest power of the drive motors, however, the performance should be clearly related to other technological equipment.

Theoretical Investigation on the Reversible Photoswitch Mechanism of Benzylidene-Oxazolone System.

The design and application of molecular photoswitches have attracted much attention. Herein, we performed a detailed computational study on the photoswitch benzylidene-oxazolone system based on static electronic structure calculations and on-the-fly excited-state dynamic simulations. For the Z and E isomer, we located six and four minimum energy conical intersections (MECIs) between the first excited state (S1) and the ground state (S0), respectively. Among them, the relaxation pathway driven by ring-puckering motion is the most competitive channel with the photoisomeization process, leading to the low photoisomerization quantum yield. In the dynamic simulations, about 88 % and 66 % trajectories decay from S1 to S0 for Z and E isomer, respectively, within the total simulation time of ~2 ps. The photoisomeization quantum yields obtained in our study (0.20 for Z→E and 0.12 for E→Z) agree well with the experimental measured values (0.25 and 0.11), even though the number of trajectories is limited to 50. Our study sheds light on the complexity of the benzylidene-oxazolone system 's deactivation process and the competitive mechanisms among different reaction channels, which provides theoretical guidance for further design and development of benzylidene-oxazolone based molecular photoswitches.

On the Strong Binding Affinity of Gold-Graphene Heterostructures with Heavy Metal Ions in Water: A Theoretical and Experimental Investigation.

Minimum energy configurations in 2D material-based heterostructures can enable interactions with external chemical species that are not observable for their monolithic counterparts. Density functional theory (DFT) calculations reveal that the binding energy of divalent toxic metal ions of Cd, Pb, and Hg on graphene-gold heterointerfaces is negative, in contrast to the positive value associated with free-standing graphene. The theoretical predictions are confirmed experimentally by Surface Plasmon Resonance (SPR) spectroscopy, where a strong binding affinity is measured for all the heavy metal ions in water. The results indicate the formation of a film of heavy metal ions on the graphene-gold (Gr/Au) heterointerfaces, where the adsorption of the ions follows a Langmuir isotherm model. The highest thermodynamic affinity constant K = 3.1 × 107 L mol-1 is observed for Hg2+@Gr/Au heterostructures, compared to 1.1 × 107 L mol-1 and 8.5 × 106 L mol-1 for Pb2+@Gr/Au and Cd2+@Gr/Au, respectively. In the case of Hg2+ ions, it was observed a sensitivity of about 0.01°/ppb and a detection limit of 0.7 ppb (∼3 nmol L-1). The combined X-ray photoelectron spectroscopy (XPS) and SPR analysis suggests a permanent interaction of all of the HMIs with the Gr/Au heterointerfaces. The correlation between the theoretical and experimental results indicates that the electron transfer from the graphene-gold heterostructures to the heavy metal ions is the key for correct interpretation of the enhanced sensitivity of the SPR sensors in water.

Insights into transition metal encapsulated inside carbon aerogel for accelerated electro-peroxone oxidation: Activity evaluation and reactive oxygen species generation

Transition metals have critical influences on the generation of reactive oxygen species in activating O3 and H2O2, as the binary oxidant sources in electro-peroxone (EP). To evaluate the catalytic activity of different metals and reveal the reactive oxygen species generation in heterogeneous EP, series of metals encapsulated inside carbon aerogel spheres (M@CS, M=Fe, Co, Ni, Zn) were fabricated for strengthening EP. Atrazine was used as model pollutant due to its low reactivity with O3, and the abatement trends followed Co@CS > Fe@CS > Ni@CS > Zn@CS. Co@CS exhibited the superior catalytic activity with maximum metal active site utilization (1.28 × 103 min-1 mol-1 per mole Co atom sites at pH 7) and minimum electric energy consumption (0.106 kWh/m3-log). The catalytic activity of M@CS was related to the adsorption energies for O3 and H2O2 (Fe@CS > Co@CS > Ni@CS > Zn@CS) and the graphitization degree (Co@CS > Fe@CS > Ni@CS > Zn@CS). Verified by theoretical calculation and in-situ Fourier transformed infrared, the metal effectively promoted the adsorption and decomposition of O3 and H2O2 into the surface oxygen intermediates, finally generating ·OH/·O2-/1O2. The carbon layer was conducive to the reduction of internal metal, ensuring catalyst durability. Electronic paramagnetic resonance and kinetic model revealed the occurrence, ratio and transient concentration of ·OH/·O2-/1O2 in M@CS/EP. M@CS/EP showed good performance for pollutant removal in coexistence of anions, humic acid and real water. This study provides guidance for selecting the metal–carbon catalyst in heterogeneous EP.

Deep learning-based energy prediction and tangent search remora optimization-based secure multi-path data communication mechanism in WSN

ABSTRACT Wireless Sensor Network (WSN) has been exploited in numerous regions which can be hardly accessed by humans. However, it is essential to convey the information accumulated by the sensing devices or nodes to the Base Station (BS) for further processing. Multipath routing protocols are found to address these challenges and provide reliable communication. This paper aims to find an optimal path to the gateway with minimum energy consumption and reduced error rate while meeting the end-to-end delay requirements. In this research, an effective multipath routing based on energy prediction and hybrid optimization is developed. Here, a Deep Q-Network (DQN) is applied to predict the energy, and the process is augmented by the usage of a proposed Tangent Search Remora Optimization (TSRO) algorithm. Further, the multipath routing is executed using the TSRO algorithm, considering a fitness function formulated using various factors, like residual energy, distance, throughput, reliability, trust factors, predicted energy, Link Life Time (LLT), delay, and traffic intensity. The devised TSRO-routing is scrutinized for its competence based on trust, throughput, energy, distance, and delay and has achieved superior values of energy of 0.402 J, throughput at 25.056Mbps, trust at 84.975, and minimal distance of 29.964 m, and delay of 0.750 ms.

Unraveling the mechanism of carbonic anhydrase IX inhibition by alkaloids from Ruta chalepensis: A synergistic analysis of in vitro and in silico data

Due to the pivotal role of carbonic anhydrase IX (CA IX) in pathological conditions, there's a pressing need for novel inhibitors to improve patient outcomes and clinical management. Herein, we investigated the inhibitory efficacy of six alkaloids from Ruta chalepensis against CA IX through in vitro inhibition assay and computational modeling. Skimmianine and maculosidine displayed significant inhibitory activity in vitro, with low IC50 values of 105.2 ± 3.2 and 295.7 ± 14.1 nM, respectively. Enzyme kinetics analyses revealed that skimmianine exhibited a mixed inhibition mode, contrasting with the noncompetitive inhibition mechanism observed for the reference drug (acetazolamide), as indicated by intersecting lines in the Lineweaver-Burk plots. The findings of docking calculations revealed that skimmianine and maculosidine exhibited extensive polar interactions with the enzyme. These alkaloids demonstrate substantial binding interactions and occupy identical binding site as acetazolamide, thereby enhancing their efficacy as inhibitors of CA IX. Utilizing a 100 ns molecular dynamics (MD) simulation, the dynamic interactions between isolated alkaloids and CA IX were intensively assessed. Analysis of diverse MD parameters revealed that skimmianine and maculosidine displayed consistent trajectories and notable energy stabilization during their interaction with CA IX. The findings of MM/PBSA analysis depicted the minimum binding free energy for skimmianine and maculosidine. In addition, the Potential Energy Landscape (PEL) analysis revealed distinct and stable conformational states for the CA IX-ligand complexes, with Skimmianine showing the most stable and lowest energy configuration. These computational findings align with experimental results, emphasizing the potential efficacy of skimmianine and maculosidine as inhibitors of CA IX.

Nucleation and growth behavior of primary Al11Ce3 intermetallic compounds during solidification in a hypereutectic Al–Ce alloy

In this study, the nucleation and growth mechanisms of Al11Ce3 intermetallic compounds (IMCs) in a hypereutectic Al–Ce alloy during solidification were investigated through synchrotron radiation X-ray real-time imaging. The results showed that Al11Ce3 IMCs nucleate and grow from the melt as the primary phase at the initial stage of solidification. Growth preferred orientations were observed in two opposite directions, resulting in an I-shaped growth pattern. Based on the minimum energy criterion, the morphology of Al11Ce3 IMCs displayed either hollow cubic tubes or grooves. The nucleation and growth rates of Al11Ce3 IMCs gradually decreased over time, owing to the variations in the Ce concentration in the melt and the undercooling. The nucleation and growth characteristics of Al11Ce3 IMCs can provide the theoretical basis for optimization on the performance of Al–Ce alloys.

Hydrogen adsorption on fcc metal surfaces towards the rational design of electrode materials

The successful large-scale implementation of hydrogen as an energy vector requires high performance electrodes and catalysts made of abundant materials. Rational materials design strategies are the most efficient means of reaching this goal. Here we present a study on the adsorption of H-atoms onto fcc transition metal surfaces and propose descriptors for the rational design of electrodes and catalysts by means of correlations between fundamental properties of the materials and among other properties, their experimentally measured performance as hydrogen evolution electrodes (HEE). A large set of quantum mechanical modelling data at the DFT level was produced, covering the adsorption of H-atoms onto the most stable surfaces (100), (110) and (111) of: Ag, Au, Co, Cu, Ir, Ni, Pd, Pt and Rh. For each material and surface, a coverage dependent set of minimum energy structures was produced and chemical potentials for adsorption of H-atoms were obtained. Averaging procedures are here proposed to approach modelling to the experiments. Several correlations between the computed data and experimentally measured quantities are done to validate our methodology: surface plane dependent adsorption energies, chemical potentials and experimentally determined surface energies and work functions. We search for descriptors of catalytic activity by testing correlations between the DFT data obtained from our averaging procedures and experimental data on HEE performance. Our methodology allows us to obtain linear correlations between the adsorption energy of H-atoms and the exchange current density (i0) in a HEE, avoiding the volcano-like plots. We show that the chemical potential has limitations as a descriptor of i0 because it reaches an early plateau in terms of i0. Simple quantities obtained from database data such as the first stage electronegativity (χ) as devised by Mulliken has a strong linear correlation i0. With a quantity we denominate modified second-stage electronegativity (χ2m) we can reproduce the typical volcano plot in a correlation with i0. A theoretical and conceptual framework is presented. It shows that both χ and χ2m, that depend on the first ionization potential, second ionization potential and electron affinity of the elements can be used as descriptors in rational design of electrodes or of catalysts for hydrogen systems.

Exploiting the Potential of Iridium(III) bis-Nitrone Complexes as Phosphorogenic Bifunctional Reagents for Phototheranostics.

Cross-linking strategies have found wide applications in chemical biology, enabling the labeling of biomolecules and monitoring of protein-protein interactions. Nitrone exhibits remarkable versatility and applicability in bioorthogonal labeling due to its high reactivity with strained alkynes via the strain-promoted alkyne-nitrone cycloaddition (SPANC) reaction. In this work, four cyclometalated iridium(III) polypyridine complexes functionalized with two nitrone units were designed as novel phosphorogenic bioorthogonal reagents for bioimaging and phototherapeutics. The complexes showed efficient emission quenching, which is attributed to an efficient nonradiative decay pathway via the low-lying T1/S0 minimum energy crossing point (MECP), as revealed by computational studies. However, the complexes displayed significant emission enhancement and lifetime extension upon reaction with (1R,8S,9s)-bicyclo[6.1.0]non-4-yne (BCN) derivatives. In particular, they showed a remarkably higher reaction rate toward a bis-cyclooctyne derivative (bis-BCN) compared with its monomeric counterpart (mono-BCN). Live-cell imaging and (photo)cytotoxicity studies revealed higher photocytotoxicity in bis-BCN-pretreated cells, which is ascribed to the enhanced singlet oxygen (1O2) photosensitization resulting from the elimination of the nitrone-associated quenching pathway. Importantly, the cross-linking properties and enhanced reactivity of the complexes make them highly promising candidates for the development of hydrogels and stapled/cyclized peptides, offering intriguing photophysical, photochemical, and biological properties. Notably, a nanosized hydrogel (2-gel) demonstrated potential as a drug delivery system, while a stapled peptide (2-bis-pDIKK) exhibited p53-Mdm2 inhibitory activity related to apoptosis and a cyclized peptide (2-bis-RGD) showed cancer selectivity.

A novel fractional rat hawk optimization–enabled routing with deep learning–based energy prediction in wireless sensor networks

SummaryWireless sensor networks (WSNs) contain different sensors, which collect various data in the monitoring area. In general, one of the significant resources in WSNs is energy, which prolongs the network's lifetime. The energy‐efficient routing algorithms reduce energy consumption and enhance the survival cycle of WSNs. Thus, this work developed the optimization‐based WSN routing and deep learning (DL)–enabled energy prediction scheme for efficient routing in WSNs. Initially, the WSN simulation is carried out, and then, the node with minimum energy consumption is chosen as the cluster head (CH). Here, the proposed rat hawk optimization (RHO) algorithm is established for finding the best CH, and the RHO is the integration of rat swarm optimization (RSO) and fire hawk optimization (FHO). Furthermore, the routing is accomplished by the developed fractional rat hawk optimization (FRHO) using the fitness function includes delay, distance, link lifetime, and predicted energy of a network for predicting the finest route. Here, the fractional calculus (FC) is incorporated with the RHO to form the FRHO. The energy prediction is achieved by deep recurrent neural network (DRNN). The energy, delay, and throughput evaluation metrics are considered for revealing the efficiency of the proposed system, and the proposed system achieves the best results of 0.246 J, 0.190 s, and 67.13 Mbps, respectively.

A hierarchical frequency stability control strategy for distributed energy resources based on ADMM

With the large-scale distributed energy resources (DERs) interfaced by power electronic converters connected to the power grid, the traditional synchronous generation is gradually replaced, and the inertia and primary frequency regulation capability of the power system is weakened, which seriously threatens the frequency security of the power grid. In view of the above problems, a hierarchical control strategy by coordinating the distributed wind turbine (WT) and photovoltaic (PV) is presented to improve the transient frequency (TF) and steady-state frequency (SSF). For the system control level, the optimal frequency regulation coefficients of multiple WTs and PVs clustering systems are determined by the optimal control principle with minimum frequency regulation energy, while considering the constraints of TF and SSF. For the WT/PV control level, the frequency regulation coefficients of WTs and PVs are solved by the model predictive controller (MPC) and alternating direction method of multipliers (ADMM), with the minimum control cost of WT and PV. It achieves the optimal allocation of frequency regulation power and improves the computing efficiency. Finally, the validity of the proposed method is tested in the modified IEEE 10-machine 39-bus system.

Recent Advances in Nanocatalyzed One-Pot Sustainable Synthesis of Bioactive N, N-Heterocycles with Anticancer Activities: An Outlook of Medicinal Chemistry.

N-heterocycles represent a predominant and unique class of organic chemistry. They have received a lot of attention due to their important chemical, biomedical, and industrial uses. Food and Drug Administration (FDA) approved about 75% of drugs containing N-based heterocycles, which are currently available in the market. N-Heterocyclic compounds exist as the backbone of numerous natural products and act as crucial intermediates for the construction of pharmaceuticals, veterinary items, and agrochemicals frequently. Among N-based heterocyclic compounds, bioactive N,N-heterocycles constitute a broad spectrum of applications in modern drug discovery and development processes. Cefozopran (antibiotic), omeprazole (antiulcer), enviradine (antiviral), liarozole (anticancer), etc., are important drugs containing N,N-heterocycles. The synthesis of N,Nheterocyclic compounds under sustainable conditions is one of the most active fields because of their significant physiological and biological properties as well as synthetic utility. Current research is demanding the development of greener, cheaper, and milder protocols for the synthesis of N,N-heterocyclic compounds to save mother nature by avoiding toxic metal catalysts, extensive application of energy, and the excessive use of hazardous materials. Nanocatalysts play a profound role in sustainable synthesis because of their larger surface area, tiny size, and minimum energy; they are eco-friendly and safe, and they provide higher yields with selectivity in comparison to conventional catalysts. It is increasingly demanding research to design and synthesize novel bioactive compounds that may help to combat cancer since the major causes of death worldwide are due to cancer. Hence, the important uses of nanocatalysts for the one-pot synthesis of biologically potent N,N-heterocycles with anticancer activities have been presented in this review.