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The Structural theory of chemistry introduces chemical/molecular structure as a combination of relative arrangement and bonding patterns of atoms in molecule. Nowadays, the structure of atoms in molecules is derived from the topological analysis of the quantum theory of atoms in molecules (QTAIM). In this context a molecular structure is varied by large geometrical variations and concomitant reorganization of electronic structure that are usually taking place in chemical reactions or under extreme hydrostatic pressure. In this report a new mode of structural variation is introduced within the context of the newly proposed multi-component QTAIM (MC-QTAIM) that originates from mass variation of nuclei. Accordingly, XCN and CNX series of species are introduced where X stands for a quantum particle with a unit of positive charge and a variable mass that is varied in discrete steps between the masses of proton and positron. Ab initio non-Born-Oppenheimer (non-BO) calculations are done on both series of species and the resulting non-BO wavefunctions are used for the MC-QTAIM analysis revealing a triatomic structure for the proton mass and a diatomic structure for the positron mass. In bo

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ChemCrow, an LLM chemistry agent designed to accomplish tasks across organic synthesis, drug discovery and materials design. By integrating 18 expert-designed tools and using GPT-4 as the LLM, ChemCrow augments the LLM performance in chemistry, and new capabilities emerge. Our agent autonomously planned and executed the syntheses of an insect repellent and three organocatalysts and guided the discovery of a novel chromophore. Our evaluation, including both LLM and expert assessments, demonstrates ChemCrow’s effectiveness in automating a diverse set of chemical tasks. Our work not only aids expert chemists and lowers barriers for non-experts but also fosters scientific advancement by bridging the gap between experimental and computational chemistry. Large language models can be queried to perform chain-of-thought reasoning on text descriptions of data or computational tools, which can enable flexible and autonomous workflows. Bran

Lithium-ion batteries have aided the portable electronics revolution for nearly three decades. They are now enabling vehicle electrification and beginning to enter the utility industry. The emergence and dominance of lithium-ion batteries are due to their higher energy density compared to other rechargeable battery systems, enabled by the design and development of high-energy density electrode materials. Basic science research, involving solid-state chemistry and physics, has been at the center of this endeavor, particularly during the 1970s and 1980s. With the award of the 2019 Nobel Prize in Chemistry to the development of lithium-ion batteries, it is enlightening to look back at the evolution of the cathode chemistry that made the modern lithium-ion technology feasible. This review article provides a reflection on how fundamental studies have facilitated the discovery, optimization, and rational design of three major categories of oxide cathodes for lithium-ion batteries, and a personal perspective on the future of this important area. The 2019 Nobel Prize in Chemistry has been awarded to a trio of pioneers of the modern lithium-ion battery. Here, Professor Arumugam Manthiram lo

In their recent article, Derrien et al. (Derrien et al., 2023) study the anisotropy of microdosimetric quantities for spherical sites of several sizes placed around spherical gold nanoparticles of several diameters irradiated by monoenergetic photons. This comment points out that (1) the reported single event distributions of specific energy may be biased due to overcounting. (2) by considering only energy imparted by electrons produced in photon interactions in the nanoparticle, the magnitude of the anisotropy is overestimated by up to orders of magnitude with respect to an irradiation under conditions of secondary particle equilibrium.

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The development of selective high precision chemical functionalization strategies for device fabrication, in conjunction with associated techniques for patterning graphene wafers with atomic accuracy would provide the necessary basis for a post-CMOS manufacturing technology. This requires a thorough understanding of the principles governing the reactivity and patterning of graphene at the sub-nanometer length scale. This article reviews our quest to delineate the principles of graphene chemistry - that is, the chemistry at the Dirac point and beyond, and the effect of covalent chemistry on the electronic structure, electrical transport and magnetic properties of this low-dimensional material in order to enable the scalable production of graphene-based devices for low- and high-end technology applications.

1,4-benzodiazepine-2-ones and their derivatives are prominent structures in medicinal chemistry. These biomolecules have wide biological activities and posses therapeutic applications. In this works, we introduce new derivatives of 1,4-benzodiazepine-2-ones which are synthesized using michael addition reaction of 7-chloro- 1,3-dihydro-5-phenyl-2H-1,4-benzodiazepine-2-ones with fumaric esters that matches with green chemistry protocols. The structures of all products are confirmed by FT-IR, 1H-NMR, 13C-NMR and MASS spectroscopy. Since the stereochemistry of 1,4-benzo diazepine-2-ones is important, we study the most stable conformer of one of the products as a model for conformational analysis by hyper chem soft ware and semi empirical AM1 program. Also, using the 1H-NMR spectrum, we investigate the produced diastereomers of one of products as a model.

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