Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality

Catalyst optimization for enantioselective transformations has traditionally relied on empirical evaluation of catalyst properties. Although this approach has been successful in the past it is intrinsically limited and inefficient. To address this problem, our laboratory has developed a fully informatics guided workflow to leverage the power of artificial intelligence (AI) and machine learning (ML) to accelerate the discovery and optimization of any class of catalyst for any transformation. This approach is mechanistically agnostic, but also serves as a discovery platform to identify high performing catalysts that can be subsequently investigated with physical organic methods to identify the origins of selectivity.

Fluorine-Retentive Strategies for the Functionalization of gem-Difluoroalkenes

gem-Difluoroalkenes are readily available fluorinated building blocks, and the fluorine-induced electronic perturbations of the alkenes enables a wide array of selective functionalization reactions. However, many reactions of gem-difluoroalkenes result in a net C–F functionalization to generate monofluorovinyl products or addition of F to generate trifluoromethyl-containing products. In contrast, fluorine-retentive strategies for the functionalization of gem-difluoroalkenes remain less generally developed, and is now becoming a rapidly developing area. This review will present the development of fluorine-retentive strategies including electrophilic, nucleophilic, radical, and transition metal catalytic strategies with an emphasis on key physical organic and mechanistic aspects that enable reactivities.

An outstanding organic chemist and organizer of science in the Donetsk region (to the 100th anniversary of Academician LM. Lytvynenko)

January 12 marks the 100th anniversary of the birth of a prominent Ukrainian scientist in the field of physical and organic chemistry, a talented organizer of science, winner of the State Prize of Ukraine in Science and Technology (1993, posthumously), winner of the L.V. Pisarzhevsky Prize of the NAS of Ukraine (1969), the organizers and first rector (1965-1968) of the Donetsk National University, one of the founders and first chairman (1971–1978) of the Donetsk Scientific Center, founder and director (1975-1983) of the Litvinenko Institute of Physical Organic and Coal Chemistry of the NAS of Ukraine, Doctor of Chemical Sciences (1961), Professor (1962), Academician of the NAS of Ukraine (1965) Leonid M. Lytvynenko.

Machine learning prediction of hydrogen atom transfer reactivity in photoredox-mediated C–H functionalization

DFT-computed structure–activity relationship data and physical organic descriptors create accurate machine learning model for HAT barrier prediction in photoredox-mediated HAT catalysis.

1.5 Photochemistry and Radical Generation: Approaches in Mechanism Elucidation

The development of photocatalytic reactions has reemerged as an active area of research in organic synthesis. A large variety of synthetically valuable transformations have now been developed that take advantage of the ease by which photocatalysts generate a variety of open-shelled reactive intermediates. The study of the mechanisms of these reactions, however, is a challenge, especially in increasingly sophisticated reactions that often involve multiple steps and complex reaction mixtures. Multiple complementary techniques often need to be utilized in tandem in order to develop a detailed understanding of these reactions. The first part of this review outlines many of the most common techniques that are used to interrogate the initiation and product-formation steps of a photocatalytic transformation. The second part describes case studies that provide contextual examples of how photophysical, electrochemical, physical organic, and computational investigations can be used together to provide insights into the mechanisms of complex photocatalytic reactions.

Opinion: Chemical Meoscopics for the Mesoparticles Reactivity Explanation

The estimation of chemical particles reactivity and the determination of chemical reactions direction are the actual theme in new scientific trend – Chemical Mesoscopics. Paper includes the proposal about the using the theory of free energy linear dependence from physical organic chemistry and their applications for prognosis of reactions flowing. The semi-empiric constants is given according to mesoscopic physics definitions as well as the transformed Kolmogorov–Avrami equation is discussed. It is the development of Chemical Mesoscopics for organic reactivity estimation including nanostructures reactivity.

Racism as a challenge for church and society in democratic South Africa: Human dignity perspective

The image of God has been vandalised by racism in South Africa, which it is argued is a sin. It is an ecclesiological responsibility to address the vandalised image of God in South Africa. The author will argue from the human relationship as a build-up to the Theanthropocosmic principle. This principle denotes the relationship between God (theos) the human being (anthropos) and the physical-organic environment (cosmos). For addressing this responsibility, the grounds of internal racism are exposed using a philosophical interpretation. According to the author, there is a correlation between sin and racism. The latter is viewed as multidimensional from a Theanthropocosmic perspective.The theoretical framework will be within hamartiology and soteriology. The philosophical interpretation will be utilised to broaden the understanding of the theological problem of the vandalised image of God.