Efficient Routing Research Articles

Ni(II)‐Complex Anchored Over Functionalized Mesoporous SBA‐15: A Nanocatalyst for the Synthesis of Aminophenoxazinone Derivatives

AbstractImmobilization of the reactive metal sites over high surface area porous nanomaterial is a very demanding route in designing novel nanocatalysts for the synthesis of valuable fine chemicals. Here we report an efficient, eco‐friendly and sustainable route for the synthesis of aminophenoxazinone derivatives via oxidative coupling of o‐aminophenols catalysed by a novel mesoporous highly ordered Ni(II)‐complex functionalized mesoporous heterogeneous organosilica catalyst. A novel structurally characterized Ni(II)‐complex derived from 2‐(I‐(2‐(piperizin‐1‐yl) ethylimino) methyl)‐5‐methylphenol ligand has been immobilised over a 2D‐hexagonally ordered functionalized mesoporous SBA‐15 synthesized via surface functionalization of SBA‐15 material with 3‐aminopropyltriethoxysilane (APTES) to obtain the Ni(II)‐nanocatalyst SANI. Its catalytic activity has been explored for three different substrates like o‐aminophenol (OAP), 3‐amino‐4‐hydroxybenzoic acid (CAP) and 2‐amino‐4‐methylphenol (MAP) that produces corresponding phenoxazinone derivatives having the yields of 92, 81 and 85 %, respectively. suggesting wide scope of this supported mesoporous nanocatalyst.

Construction of schottky-assisted Z-scheme heterojunction Cd0.3Zn0.7S@Ti3C2/Ag/CeO2 boosted carriers charge separation for efficient photocatalytic hydrogen production

The purposeful modulation of interfacial charge transfer pathways in heterogeneous structures is an innovative and feasible strategy to improve photocatalysis efficiency. However, it is often characterized by difficulties in charge separation and transport and the high charge recombination limits its applications. Herein, a Cd0.3Zn0.7S-based heterostructure of Cd0.3Zn0.7S@Ti3C2/Ag/CeO2 was fabricated in which the efficient electron transfer route was designed by synergistic action of Z-scheme and Schottky junction. Serial characterizations and Density-Functional Theory calculations identify the Schottky junction promoted the electrons in Cd0.3Zn0.7S to transfer to Ti3C2, whereas the Z-scheme heterojunction accelerated the electrons transfer from CeO2 to Cd0.3Zn0.7S@Ti3C2 with Ag acting as the electronic intermediary. Significantly, the optimized Cd0.3Zn0.7S@Ti3C2/Ag/CeO2 exhibited stronger photocatalytic H2 evolution of 16.3 mmol·g−1·h−1 with an apparent quantum efficiency of 29.8 % at 420 nm, which was 4.2 times higher than the pristine Cd0.3Zn0.7S material. This work offers valuable insights into realizing the desired charge transfer route through artificial heterointerface and a new possibility for applying Cd1-xZnxS materials in photocatalytic hydrogen production.

Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids.

Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance and resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance routing decisions in AMI deployments based on wireless mesh technologies. Q-RPL leverages the principles of Reinforcement Learning (RL) to dynamically select optimal next-hop forwarding candidates, adapting to changing network conditions. The protocol operates on top of the standard IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), integrating it with intelligent decision-making capabilities. Through extensive simulations carried out in real map scenarios, Q-RPL demonstrates a significant improvement in key performance metrics such as packet delivery ratio, end-to-end delay, and compliant factor compared to the standard RPL implementation and other benchmark algorithms found in the literature. The adaptability and robustness of Q-RPL mark a significant advancement in the evolution of routing protocols for Smart Grid AMI, promising enhanced efficiency and reliability for future intelligent energy systems. The findings of this study also underscore the potential of Reinforcement Learning to improve networking protocols.

Chemoenzymatic One‐Pot Cascade for the Construction of Asymmetric C−C and C−P Bonds via Formal C−H Activation

AbstractThe integration of organocatalysis and enzyme catalysis in one‐pot cascade processes allows for the efficient construction of complex molecular architectures with high levels of stereocontrol. However, challenges related to reaction compatibility between both processes are often a limitation for the development of efficient synthetic routes. In this study, we describe the combination of an enzymatic aerobic oxidation followed by the squaramide‐mediated asymmetric formation of C−P and C−C bonds to access important building blocks such as chiral α‐hydroxyphosphonates and β‐nitro alcohols in good yields and enantiomeric ratios. This sequential process is conducted in a one‐pot fashion within a biphasic system and represents a pioneering example of a chemoenzymatic cascade involving aerobic biooxidation and an organocatalytic step operating under hydrogen‐bond activation mode and under mild reaction conditions.

Catalytic Investigation of ε-caprolactone Polymerization through Schiff BaseTitanium (IV) Complexes

Background: The ring-opening polymerization (ROP) reaction has provided an efficient and convenient route to prepare polyesters of high molecular weight, low polydispersity index, and high optical purity. The poly(ε-caprolactone) (PCL) and poly(lactide) (PLA) were prepared through ROP reaction of ε-caprolactone and D, L-lactide, respectively. These compounds have a huge industrial demand and become an interest among the scientific community to develop more economically and eco-friendly catalysts for ROP reactions. Methods: Three Schiff base ligands, 2-((benzo[d]thiazole-2-ylimino)methyl)phenol, L1; 2-(1-benzo[d]thiazole-2-ylimino)ethyl)phenol, L2; and 2- ((benzo[d]thiazole-2-ylimino)methyl)-5-methoxyphenol, L3; were prepared by the reaction of 2-aminobenzothiazole with 2-hydroxybenzaldehyde, 2-hydroxyacetophenone and 2-hydroxy-4-methoxybenzaldehyde in 1:1 molar ratio. In anticipation of interesting stereochemistry, reactivity, and catalytic potential against ε-caprolactone polymerization, three Titanium(IV) complexes (1 – 3) of these Schiff base ligands were synthesized. All the prepared compounds were characterized by elemental analysis, molar conductance, FT-IR, UV-Vis, 1H-NMR, 13C{1H}-NMR and FAB-Mass spectroscopic technique. Geometry was optimized with the help of DFT. Results: Complex 3 gives a much higher yield (87.7%) in comparison to 1 and 2. The order of catalytic efficiency for complexes is 3>1>2. With the increase in temperature, the % yield was found to decrease, and results are in support of moderate to good potency of synthesized catalysts. Conclusion: Complexes were screened for catalytic potency against ε-Caprolactone polymerization reaction. A most plausible mechanism for the polymerization was also proposed.

Sono-synthesis and characterization of next-generation antimicrobial ZnO/TiO2 and Fe3O4/TiO2 bi-nanocomposites, for antibacterial and antifungal applications

Ultrasonic-assisted synthesis of ZnO/TiO₂ and Fe₃O₄/TiO₂ bi-oxide nanocomposites at low frequencies (60 kHz) with their characterizations and antibacterial/antifungal applications are investigated in this study. Using nanotechnology as the next-generation solution, this research explored the potential of metal oxide nanoparticles as effective antibacterial agents. Nanomaterials were synthesized via a novel and facile method (sono-synthesis) and characterized using various techniques (XRD, SEM, FTIR, zeta potential analysis, Raman spectroscopy, and XPS), revealing nanoscale sizes of 25 nm for ZnO/TiO₂ and 31 nm for Fe₃O₄/TiO₂. Structural analysis demonstrated the distinct crystalline phases of the synthesized nanomaterials: TiO₂ with anatase structure (25 %), hexagonal wurtzite structure for ZnO, and Fe₃O₄ with inverse spinel structure, formed in nano-dimensions (19–31 nm) with a near-spherical shape. Antibacterial and antifungal assays highlighted the efficacy of both bi-nanocomposites against gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacteria, along with their potent activity against Candida albicans and non-albicans Candida. Moreover, principal component analysis (PCA) was used to identify potential relationships between the physicochemical properties (zeta potential, size, conductivity, and concentration) of all nanomaterials tested and their zone of inhibition (ZOI) against all bacterial species tested. Overall, this study emphasizes the novelty of employing a simple and efficient sono-synthetic route to synthesize ZnO/TiO₂ and Fe₃O₄/TiO₂ bi-nanocomposites and investigate their significant antibacterial and antifungal activities. Additionally, it identifies the potential relationships between the physicochemical properties of the nanomaterials tested and their antimicrobial activity. This approach provides a robust framework for future applications of bi-nanocomposites in combating microbial infections.

A Novel Energy-Efficient Routing Protocol for Industrial WSN Using Hybrid Coot-Ls Algorithm with LSTM-Based Dom Prediction

In industrial Wireless Sensor Networks (WSNs), energy efficiency and reliable data transmission are critical challenges that need to be addressed to ensure sustainable and robust network operations. This paper proposes a novel energy-efficient routing protocol that integrates a Hybrid COOT-LS (Coot- Levy Search) algorithm with Long Short-Term Memory (LSTM)-based Dominant Object Motion (DOM) prediction. The routing protocol leverages the strengths of Hybrid Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to enhance routing efficiency and reduce energy consumption. The Hybrid PSO and ACO algorithms are employed to optimize routing paths by balancing exploration and exploitation, considering multiple factors such as energy levels, node distance, and reliability. The COOT-LS algorithm further refines these paths by incorporating a Levy flight mechanism to enhance the search process. Additionally, the LSTM-based DOM prediction provides accurate forecasts of network conditions, enabling dynamic adjustments to routing strategies in real time. Simulation results demonstrate that the proposed protocol significantly improves network lifetime, reduces energy consumption, and enhances data transmission reliability compared to traditional routing protocols. This approach provides a robust and scalable solution for industrial WSN applications, ensuring efficient and reliable network performance in dynamic and complex industrial environments.

Energy efficient cluster-based routing protocol for WSN using multi-strategy fusion snake optimizer and minimum spanning tree

In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the internet of things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the multi-strategy fusion snake optimizer (MSSO) and employs the minimum spanning tree algorithm for inter-cluster routing planning, thereby extending the system’s lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space. Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy c-means (FCM) algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%.

Efficient allylic oxidation of cyclohexene catalyzed by Ti-MCM-41 using H2O2 as oxidant

2-cyclohexen-1-ol and 2-cyclohexen-1-one are very important chemical raw materials, and it is a challenge to develop an environmental and efficient synthesis route with titanium-containing catalyst to obtain high yield of allylic oxidation product. Herein, we present an intensive study on the allylic oxidation of cyclohexene over titanosilicates/H2O2 system. Ti-MCM-41 is found as an efficient catalyst. The reaction parameters, including cyclohexene/H2O2 molar ratios, solvent, catalyst amount, titanium content, reaction temperature and reaction time, were studied in detail. And a high cyclohexene conversion (∼20.2 %) and total selectivity of 2-cyclohexen-1-one and 2-cyclohexen-1-ol (∼90.0 %) was achieved under optimized reaction conditions. Further the allylic oxidation of cyclohexene proceeds a radical mechanism as demonstrated by the addition of radical scavenger BHT. This will make it possible for the highly selective green generation of enols and ketenes.

Multi-Objective Optimization of Resilient, Sustainable, and Safe Urban Bus Routes for Tourism Promotion Using a Hybrid Reinforcement Learning Algorithm

Urban transportation systems in tourism-centric cities face challenges from rapid urbanization and population growth. Efficient, resilient, and sustainable bus route optimization is essential to ensure reliable service, minimize environmental impact, and maintain safety standards. This study presents a novel Hybrid Reinforcement Learning-Variable Neighborhood Strategy Adaptive Search (H-RL-VaNSAS) algorithm for multi-objective urban bus route optimization. Our mathematical model maximizes resilience, sustainability, tourist satisfaction, and accessibility while minimizing total travel distance. H-RL-VaNSAS is evaluated against leading optimization methods, including the Crested Porcupine Optimizer (CPO), Krill Herd Algorithm (KHA), and Salp Swarm Algorithm (SSA). Using metrics such as Hypervolume and the Average Ratio of Pareto Optimal Solutions, H-RL-VaNSAS demonstrates superior performance. Specifically, H-RL-VaNSAS achieved the highest resilience index (550), sustainability index (370), safety score (480), tourist preferences score (300), and accessibility score (2300), while minimizing total travel distance to 950 km. Compared to other methods, H-RL-VaNSAS improved resilience by 12.24–17.02%, sustainability by 5.71–12.12%, safety by 4.35–9.09%, tourist preferences by 7.14–13.21%, accessibility by 4.55–9.52%, and reduced travel distance by 9.52–17.39%. This research offers a framework for designing efficient, resilient, and sustainable public transit systems that align with urban planning and transportation goals. The integration of reinforcement learning with VaNSAS significantly enhances optimization capabilities, providing a valuable tool for mathematical and urban transportation research communities.

Stoichiometric Study on Ion Composition of a Precursor in Chemical Bottom-Up Synthesis for Peroxo-Titanate.

Layered alkali titanates of the lepidocrocite type are gaining enormous interest in various fields owing to their unique properties. These materials are mainly synthesized through a hydrothermal alkali treatment. However, this method uses a highly concentrated alkali solution, which has high environmental impacts and is therefore unsuitable for mass synthesis. Herein, we propose an efficient method for the large-scale synthesis of layered sodium titanate structures (Na2-x H x Ti2O5) using a recently reported bottom-up chemical process. The effects of the Na:Ti molar ratio in the peroxo-titanium complex ion precursor on the products are investigated through stoichiometric calculations for a molar ratio range of 10:1-1:1. The optimal ratio for the complete ionization of TiH2 (which is the starting material) to form the peroxo-titanium complex ion is found to be 1.1:1. The amount of alkali raw material required is 99.6% lower than that required in the traditional hydrothermal method. The crystal structures and morphologies of the samples are almost identical regardless of the Na:Ti molar ratio. The precursor-derived peroxo bonds narrow the energy band gaps of the layered titanates even when the amount of titanium ions dissolved in the precursor increases. The proposed method is not only an efficient synthetic route for mass production but also has potential applications in the development of photofunctional materials.

Exploring nicotinamide adenine dinucleotide precursors across biosynthesis pathways: Unraveling their role intheovary.

Natural Nicotinamide Adenine Dinucleotide (NAD+) precursors have attracted much attention due to their positive effects in promoting ovarian health. However, their target tissue, synthesis efficiency, advantages, and disadvantages are still unclear. This review summarizes the distribution of NAD+ at the tissue, cellular and subcellular levels, discusses its biosynthetic pathways and the latest findings in ovary, include: (1) NAD+ plays distinct roles both intracellularly and extracellularly, adapting its distribution in response to requirements. (2) Different precursors differs in target tissues, synthetic efficiency, biological utilization, and adverse effects. Importantly: tryptophan is primarily utilized in the liver and kidneys, posing metabolic risks in excess; nicotinamide (NAM) is indispensable for maintaining NAD+ levels; nicotinic acid (NA) constructs a crucial bridge between intestinal microbiota and the host with diverse functions; nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) increase NAD+ systemically and can be influenced by delivery route, tissue specificity, and transport efficiency. (3) The biosynthetic pathways of NAD+ are intricately intertwined. They provide multiple sources and techniques for NAD+ synthesis, thereby reducing the dependence on a single molecule to maintain cellular NAD+ levels. However, an excess of a specific precursor potentially influencing other pathways. In addition, Protein expression analysis suggest that ovarian tissues may preferentially utilize NAM and NMN. These findings summarize the specific roles and potential of NAD+ precursors in enhancing ovarian health. Future research should delve into the molecular mechanisms and intervention strategies of different precursors, aiming to achieve personalized prevention or treatment of ovarian diseases, and reveal their clinical application value.

Plasma-assisted synthesis of ultra-fine NiCo2O4/NiCo-layered double hydroxides nanoparticles-decorated electrospun carbon nanofibers with enhanced electrochemical performance

Nickel cobaltate/NiCo-layered double hydroxides (NiCo2O4/NiCo-LDH) as energy storage materials offer considerable potential for various applications. However, many of current methods for synthesizing NiCo2O4/NiCo-LDH suffer from long synthesis times, complex preparation process, and high temperatures and high pressures. In this study, we present a green, simple, and efficient approach known as assisted liquid-phase plasma electrolysis, which realizes the rapid fabrication of ultra-fine NiCo2O4/NiCo-LDH nanoparticle-decorated electrospun carbon nanofibers (NiCo2O4/NiCo-LDH/CNFs) composites. Ultra-fine NiCo2O4/NiCo-LDH nanoparticles (<70 nm) are uniformly deposited on the CNF surface. The CNFs are intertwined to form a highly conductive three-dimensional mesh structure, which synergizes the NiCo2O4/NiCo-LDH nanoparticles with a high specific capacitance in favor of ion/electron transport efficiency. In addition, the cooperative effect between the two phases of NiCo2O4 and NiCo-LDH further improves the electrochemical properties. The NiCo2O4/NiCo-LDH/CNFs composites exhibit a high specific capacitance of 1534.7 F/g at 1 A/g and a capacitance retention of 93.9 % after 5000 cycles. An assembled asymmetric supercapacitor using activated carbon and NiCo2O4/NiCo-LDH/CNFs composites achieves an energy density of 33.8 Wh/kg at a power density of 400 W/kg and a capacitance retention of 93.0 % after 5000 cycles. Notably, two series-connected NiCo2O4/NiCo-LDH/CNFs ASC supercapacitors can light up an LED bulb, which maintains a certain brightness even after 50 min. Hence, this work provides a new and efficient route for synthesizing carbon-based NiCo2O4/NiCo-LDH composites for use as advanced energy storage materials.

Enantioselective Synthesis of Spiro[cyclopentane-1,3'-oxindole] Scaffolds with Five Consecutive Stereocenters.

A highly diastereo- and enantioselective cascade annulation reaction of Morita-Baylis-Hillman (MBH) maleimides of isatins with ortho-hydroxychalcones was achieved by a chiral N,N'-dioxide/Mg(II) complex Lewis acid catalyst. This strategy provides a concise and efficient route to densely functionalized spiro[cyclopentane-1,3'-oxindole] compounds with five consecutive stereocenters. The reaction itself features mild conditions, good functional group compatibility, and broad substrate scope (62 examples, up to 99% yield, up to >20:1 dr, 97% ee). In addition, an obvious ligand acceleration effect and chiral amplification effect were observed. DFT calculations were performed to elucidate the stereoselectivity observed. The gram-scale synthesis and the inhibitory effect of two products on the viability of A549 cells demonstrate the potential utility of the current method.

Batch and Continuous Flow Total Synthesis of Cannabidiol.

Herein, we present a comprehensive total synthesis of cannabidiol integrating both batch and continuous flow conditions. Our approach is planned to streamline the synthesis of olivetolic acid derivatives and utilize an enantiomerically pure monoterpene moiety obtained from naturally occurring (R)-(+)-limonene by photocatalysis. Key reactions, including the synthesis of olivetolic ester and a Friedel-Crafts alkylation, are successfully adapted to continuous flow, resulting in improved yields and selectivities. This study not only offers a scalable and efficient route for cannabidiol synthesis but also contributes to the synthetic approaches to access cannabinoids (diversity synthesis), with potential applications in medicinal and industrial contexts.

Direct C−H Alkylation of Naphthoquinone with Acetone and 1,3‐Dicarbonyl Compounds via Radical Cross Dehydrogenation Coupling

AbstractA direct C−H alkylation of naphthoquinones with acetone and 1,3‐dicarbonyl compounds was developed to construct C−C bonds of alkyl‐substituted naphthoquinone derivatives. It proceeded through an oxidative radical cross dehydrogenation coupling process under simple and mild conditions. This method provides a facile and efficient route for synthesis of functionalized naphthoquinones from readily available feedstocks.

Hybrid Boosted Chameleon and modified Honey Badger optimization algorithm-based energy efficient cluster routing protocol for cognitive radio sensor network

Single clustering protocols cannot meet the event-driven and time-triggered traffic requirements of Cognitive Radio Sensor Networks (CRSNs). The long wait between the completion of events and the process of clustering and searching for accessible routes results in increased time for information transmission. This paper proposed a Hybrid Boosted Chameleon and Modified Honey Badge optimization Algorithm-based Energy Efficient cluster routing protocol (HBCMHBOA) for handling the issues of traffic driven information transfer with energy efficiency in the CRSNs. This HBCMHBOA is proposed as one among few event-driven and time-triggered clustering protocol for the requirements of CRSNs. The integration of Boosted Chameleon and Modified Honey Badge optimization Algorithm is adopted for determining optimal number of clusters and constructs the structure of primitive clusters in an automated way to serve the time-triggered traffic in a periodic manner. It adopted priority-based schedule and its associated frame structure for guaranteeing reliable event-driven information delivery. It leveraged the merits of time-triggering for the construction of clustering architecture and confirmed than none of the cluster construction and selection of routes are facilitated after the emergent events. This characteristic helps in permitting only the nodes and their associated Cluster Heads (CHs) of CRSNs to discover emergent events. It facilitates the coverage of a fewer nodes, especially when sink is positioned in a corner to minimize the delay and node energy consumption. The simulation results of the proposed HBCMHBOA confirmed a reduction in total energy consumption and number of covered nodes on an average of 34.12 %, and 26.89 % than the prevailing studies.

A deep reinforcement learning-based intelligent QoS optimization algorithm for efficient routing in vehicular networks

With the rapid development of Telematics, Vehicle Self-Organizing Networks (VANETs) play an increasingly critical role in Intelligent Transportation Systems (ITS). Especially in the environment without roadside assistance units (RSUs), how to effectively manage inter-vehicle communication and improve the stability and communication efficiency of the network has become a hot topic of current research. In this paper, a Deep Reinforcement Learning-based Intelligent QoS-optimized efficient routing algorithm for vehicular networks (DRLIQ) is proposed for VANETs with/without RSU environments, and routing methods are proposed respectively. Among them, in RSU-free environment, the DRLIQ algorithm utilizes the powerful processing capability of deep reinforcement learning to intelligently select the optimal data transmission path by dynamically learning and adapting to the changes in the vehicular network, thus effectively reducing communication interruptions and delays, and improving the accuracy of data transmission. The performance of the DRLIQ algorithm under different vehicle densities is evaluated in simulation experiments and compared with current popular algorithms. The experimental results show that the DRLIQ algorithm outperforms the comparison algorithms in reducing the number of communication interruptions, BER and network delay, especially in vehicle-dense environments. In addition, the DRLIQ algorithm shows higher adaptability and stability in coping with network topology changes and vehicle dynamics.

Recently Adopted Synthetic Protocols for Piperazines: A Review

Piperazines, a class of heterocyclic compounds, have garnered significant attention in the field of organic synthesis due to their diverse pharmacological activities and widespread applications in medicinal chemistry. This review provides a comprehensive overview of the recent advancements in the synthesis of piperazines, highlighting innovative methodologies, novel reagents, and green synthesis approaches adopted by researchers. The synthesis of piperazines has witnessed remarkable progress, with a focus on developing efficient and sustainable synthetic routes. Various strategies, such as transition-metal-catalyzed reactions, microwave-assisted synthesis, photo-redox reactions, and bio-inspired methods, have emerged as powerful tools for constructing piperazine scaffolds. The review also encompasses discussions on the stereochemistry and regioselectivity issues associated with piperazine synthesis, shedding light on the intricacies of achieving specific substitution patterns. The impact of newly synthesized piperazines in drug discovery and development is also explored, emphasizing the therapeutic potential of these compounds in various disease areas. In conclusion, this review provides a comprehensive and up-to-date account of the recent advancements in piperazine synthesis, offering insights into the current state of the field and guiding future research directions. The integration of innovative methodologies and the exploration of sustainable practices underscore the ongoing efforts to streamline the synthesis of piperazines, contributing to the expansion of their applications in medicinal chemistry and related disciplines.

Palladium-Catalyzed Asymmetric Desymmetrization for the Simultaneous Construction of Chiral Phosphorus and Quaternary Carbon Stereocenters.

A palladium-catalyzed asymmetric tandem Heck and carbonylation of bisallyl-phosphine oxides has been developed. This desymmetrization process provided an efficient route to the simultaneous synthesis of a chiral P-stereogenic center and a chiral quaternary carbon stereocenter in good yields with good diastereo- and enantioselectivities.