Synthetic Methods for Azaheterocyclic Phosphonates and Their Biological Activity: An Update 2004–2024

Chemical Reviews, Journal Year: 2024, Volume and Issue: 124(12), P. 7907 - 7975

Published: May 29, 2024

The increasing importance of azaheterocyclic phosphonates in the agrochemical, synthetic, and medicinal field has provoked an intense search development synthetic routes for obtaining novel members this family compounds. This updated review covers methodologies established since 2004, focusing on synthesis phosphonates, which phosphonate moiety is directly substituted onto to structure. Emphasizing recent advances, classifies newly developed approaches according ring size providing information biological activities whenever available. Furthermore, summarizes various methods formation C–P bonds, examining sustainable such as Michaelis–Arbuzov reaction, Michaelis–Becker Pudovik Hirao coupling, Kabachnik–Fields reaction. After analyzing applications investigated years, a predominant focus evaluation these compounds anticancer agents evident. emerging underline versatility potential compounds, highlighting need continued research expand interesting family.

Language: Английский

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Constructing Pr-doped CoOOH catalytic sites for efficient electrooxidation of 5-hydroxymethylfurfural

Journal of Energy Chemistry, Journal Year: 2024, Volume and Issue: 100, P. 234 - 244

Published: Aug. 30, 2024

Language: Английский

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Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning

Angewandte Chemie International Edition, Journal Year: 2021, Volume and Issue: 60(42), P. 22804 - 22811

Published: Aug. 9, 2021

Abstract Asymmetric hydrogenation of olefins is one the most powerful asymmetric transformations in molecular synthesis. Although several privileged catalyst scaffolds are available, development for still a time‐ and resource‐consuming process due to lack predictive design strategy. Targeting data‐driven catalysis, we herein report standardized database that contains detailed information over 12000 literature hydrogenations olefins. This provides valuable platform machine learning applications catalysis. Based on this database, developed hierarchical approach achieve leaning model using only dozens enantioselectivity data with target olefin, which offers useful solution few‐shot problem will facilitate reaction optimization new olefin substrate catalysis screening.

Language: Английский

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Preferential Adsorption of Ethylene Oxide on Fe and Chlorine on Ni Enabled Scalable Electrosynthesis of Ethylene Chlorohydrin

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 62(13)

Published: Feb. 3, 2023

Industrial manufacturing of ethylene chlorohydrin (ECH) critically requires excess corrosive hydrochloric acid or hypochlorous with dealing massive by-products and wastes. Here we report a green efficient electrosynthesis ECH from oxide (EO) NaCl over NiFe2 O4 nanosheet anode. Theoretical results suggest that EO Cl preferentially adsorb on Fe Ni sites, respectively, collaboratively promoting the synthesis. A radical-mediated ring-opening process is proposed confirmed, key carbon radical species are identified by high-resolution mass spectrometry. This strategy can enable scalable 185.1 mmol in 1 h 92.5 % yield at 55 mA cm-2 current density. Furthermore, series other chloro- bromoethanols good to high yields paired synthesis 4-amino-3,6-dichloropyridine-2-carboxylicacid via respectively loading unloading achieved, showing promising potential this strategy.

Language: Английский

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Trinity of electrochemistry, photochemistry, and transition metal catalysis

Chem Catalysis, Journal Year: 2024, Volume and Issue: 4(3), P. 100898 - 100898

Published: Jan. 24, 2024

Language: Английский

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Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 62(11)

Published: Jan. 16, 2023

Catalytic systems using a small amount of organic photosensitizer for the activation an inorganic (on-demand ligand-free) nickel(II) salt represent cost-effective method cross-coupling reactions, while C(sp2 )-O bond formation remains less developed. Herein, we report strategy synthesis phenols with and photosensitizer, which was identified via investigation into catalytic activity 60 photosensitizers consisting various electron donor acceptor moieties. To examine effect multiple intractable parameters on photosensitizers, machine-learning (ML) models were developed, wherein embedded descriptors representing their physical structural properties, obtained from DFT calculations RDKit, respectively. The study clarified that integrating both DFT- RDKit-derived in ML balances higher "precision" "recall" across wide range search space relative to only one two descriptor sets.

Language: Английский

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Machine learning-guided yield optimization for palladaelectro-catalyzed annulation reaction

Chem, Journal Year: 2024, Volume and Issue: 10(7), P. 2283 - 2294

Published: July 1, 2024

Electrosynthesis has become an increasingly popular platform in modern organic chemistry, possessing distinctive features and reaction parameters like applied current/potential, electrodes, electrolyte systems, cell design. While these unique give chemists more opportunities to control reactivity selectivity, they also increase the dimensionalities of a complicate interactions between variables, making optimization challenging. Herein, we present machine learning (ML) workflow that leverages physical descriptor-based yield prediction orthogonal experimental design strike delicate balance need for sampling diversity pursuit improvements, thereby efficiently identifying ideal conditions enantioselective palladaelectro-catalyzed annulation from extensive synthetic space. This work shows potential synergizing electrochemistry data-driven approach tackle multidimensional chemical problems.

Language: Английский

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Modulation strategies of electrocatalysts for 5-hydroxymethylfurfural oxidation-assisted water splitting

Microstructures, Journal Year: 2024, Volume and Issue: 4(3)

Published: July 24, 2024

To address energy shortages and environmental issues, prioritizing renewable development usage is crucial. Employing sources for water electrolysis offers a sustainable method hydrogen generation. Reducing the potential vital efficient clean conversion storage. Substituting anodic oxygen evolution reaction in conventional production from with more thermodynamically favorable 5-hydroxymethylfurfural (HMF) oxidation can greatly decrease overpotential yield valuable product 2,5-furan dicarboxylic acid. The key to this process developing effective electrocatalysts minimize of HMF electrooxidation-hydrogen system. Therefore, review provides comprehensive introduction modulation strategies that affect electronic geometric structure oxidation-assisted splitting. encompass heteroatom doping, defect projection, interface engineering, structural design, multi-metal synergies. catalysts are assessed various angles, encompassing characterization, mechanisms, electrochemical performance. Finally, current challenges catalyst design promising field proposed.

Language: Английский

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Working at the interfaces of data science and synthetic electrochemistry

Tetrahedron Chem, Journal Year: 2022, Volume and Issue: 1, P. 100012 - 100012

Published: March 1, 2022

Electrochemistry is quickly entering the mainstream of synthetic organic chemistry. The diversity new transformations enabled by electrochemistry to a large extent consequence unique features and reaction parameters in electrochemical systems including redox mediators, applied potential, electrode material, cell construction. While offering chemists means control reactivity selectivity, these additional also increase dimensionalities system complicate its optimization. This challenge, however, has spawned increasing adoption data science tools aid discovery as well development high-throughput screening platforms that facilitate generation high quality datasets. In this Perspective, we provide an overview recent advances data-science driven with emphasis on opportunities challenges facing growing subdiscipline.

Language: Английский

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Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation

Green Chemistry, Journal Year: 2021, Volume and Issue: 23(16), P. 5825 - 5831

Published: Jan. 1, 2021

A highly efficient synthesis of α-ketiminophosphonates has been established for the electrochemical oxidation α-amino phosphonates with utilization machine-learning-assisted simultaneous multiparameter screening.

Language: Английский

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