Project description:We develop a formalism for calculating forces on the nuclei within the linear-scaling stochastic density functional theory (sDFT) in a nonorthogonal atom-centered basis set representation (Fabian et al. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2019, 9, e1412, 10.1002/wcms.1412) and apply it to the Tryptophan Zipper 2 (Trp-zip2) peptide solvated in water. We use an embedded-fragment approach to reduce the statistical errors (fluctuation and systematic bias), where the entire peptide is the main fragment and the remaining 425 water molecules are grouped into small fragments. We analyze the magnitude of the statistical errors in the forces and find that the systematic bias is of the order of 0.065 eV/Å (∼1.2 × 10-3Eh/a0) when 120 stochastic orbitals are used, independently of system size. This magnitude of bias is sufficiently small to ensure that the bond lengths estimated by stochastic DFT (within a Langevin molecular dynamics simulation) will deviate by less than 1% from those predicted by a deterministic calculation.
Project description:Generative molecular design strategies have emerged as promising alternatives to trial-and-error approaches for exploring and optimizing within large chemical spaces. To date, generative models with reinforcement learning approaches have frequently used low-cost methods to evaluate the quality of the generated molecules, enabling many loops through the generative model. However, for functional molecular materials tasks, such low-cost methods are either not available or would require the generation of large amounts of training data to train surrogate machine learning models. In this work, we develop a framework that connects the REINVENT reinforcement learning framework with excited state quantum chemistry calculations to discover molecules with specified molecular excited state energy levels, specifically molecules with excited state landscapes that would serve as promising singlet fission or triplet-triplet annihilation materials. We employ a two-step curriculum strategy to first find a set of diverse promising molecules, then demonstrate the framework's ability to exploit a more focused chemical space with anthracene derivatives. Under this protocol, we show that the framework can find desired molecules and improve Pareto fronts for targeted properties versus synthesizability. Moreover, we are able to find several different design principles used by chemists for the design of singlet fission and triplet-triplet annihilation molecules.
Project description:The hydrogen evolution reaction performance of semiconducting 2H-phase molybdenum disulfide (2H-MoS2) presents a significant hurdle in realizing its full potential applications. Here, we utilize theoretical calculations to predict possible functionalized graphene quantum dots (GQDs), which can enhance HER activity of bulk MoS2. Subsequently, we design a functionalized GQD-induced in-situ bottom-up strategy to fabricate near atom-layer 2H-MoS2 nanosheets mediated with GQDs (ALQD) by modulating the concentration of electron withdrawing/donating functional groups. Experimental results reveal that the introduction of a series of functionalized GQDs during the synthesis of ALQD plays a crucial role. Notably, the higher the concentration and strength of electron-withdrawing functional groups on GQDs, the thinner and more active the resulting ALQD are. Remarkably, the synthesized near atom-layer ALQD-SO3 demonstrate significantly improved HER performance. Our GQD-induced strategy provides a simple and efficient approach for expanding the catalytic application of MoS2. Furthermore, it holds substantial potential for developing nanosheets in other transition-metal dichalcogenide materials.
Project description:This review covers sixty original publications dealing with the application of multicomponent reactions (MCRs) in the synthesis of novel nucleoside analogs. The reported approaches were employed for modifications of the parent nucleoside core or for de novo construction of a nucleoside scaffold from non-nucleoside substrates. The cited references are grouped according to the usually recognized types of the MCRs. Biochemical properties of the novel nucleoside analogs are also presented (if provided by the authors).
Project description:Predicting electronic energies, densities, and related chemical properties can facilitate the discovery of novel catalysts, medicines, and battery materials. However, existing machine learning techniques are challenged by the scarcity of training data when exploring unknown chemical spaces. We overcome this barrier by systematically incorporating knowledge of molecular electronic structure into deep learning. By developing a physics-inspired equivariant neural network, we introduce a method to learn molecular representations based on the electronic interactions among atomic orbitals. Our method, OrbNet-Equi, leverages efficient tight-binding simulations and learned mappings to recover high-fidelity physical quantities. OrbNet-Equi accurately models a wide spectrum of target properties while being several orders of magnitude faster than density functional theory. Despite only using training samples collected from readily available small-molecule libraries, OrbNet-Equi outperforms traditional semiempirical and machine learning-based methods on comprehensive downstream benchmarks that encompass diverse main-group chemical processes. Our method also describes interactions in challenging charge-transfer complexes and open-shell systems. We anticipate that the strategy presented here will help to expand opportunities for studies in chemistry and materials science, where the acquisition of experimental or reference training data is costly.
Project description:Tuning metal-support interaction has been considered as an effective approach to modulate the electronic structure and catalytic activity of supported metal catalysts. At the atomic level, the understanding of the structure-activity relationship still remains obscure in heterogeneous catalysis, such as the conversion of water (alkaline) or hydronium ions (acid) to hydrogen (hydrogen evolution reaction, HER). Here, we reveal that the fine control over the oxidation states of single-atom Pt catalysts through electronic metal-support interaction significantly modulates the catalytic activities in either acidic or alkaline HER. Combined with detailed spectroscopic and electrochemical characterizations, the structure-activity relationship is established by correlating the acidic/alkaline HER activity with the average oxidation state of single-atom Pt and the Pt-H/Pt-OH interaction. This study sheds light on the atomic-level mechanistic understanding of acidic and alkaline HER, and further provides guidelines for the rational design of high-performance single-atom catalysts.
Project description:Poly-α-methylstyrene (PAMS) is considered as the preferred mandrel material, whose degradation is crucial for the fabrication of high-quality inertial confinement fusion (ICF) targets. Herein, we reveal that hydrogen atom transfer (HAT) during PAMS degradation, which is usually attributed to the thermal effect, unexpectedly exhibits a strong high-temperature tunneling effect. Specifically, although the energy barrier of the HAT reaction is only 10-2 magnitude different from depolymerization, the tunneling probability of the former can be 14-32 orders of magnitude greater than that of the latter. Furthermore, chain scission following HAT will lead to a variety of products other than monomers. Our work highlights that quantum tunneling may be an important source of uncertainty in PAMS degradation, which will provide a direction for the further development of key technology of target fabricating in ICF research and even the solution of plastic pollution.
Project description:Here, we report CdS quantum dot (QD) gels, a three-dimensional network of interconnected CdS QDs, as a new type of direct hydrogen atom transfer (d-HAT) photocatalyst for C-H activation. We discovered that the photoexcited CdS QD gel could generate various neutral radicals, including α-amido, heterocyclic, acyl, and benzylic radicals, from their corresponding stable molecular substrates, including amides, thio/ethers, aldehydes, and benzylic compounds. Its C-H activation ability imparts a broad substrate and reaction scope. The mechanistic study reveals that this reactivity is intrinsic to CdS materials, and the neutral radical generation did not proceed via the conventional sequential electron transfer and proton transfer pathway. Instead, the C-H bonds are activated by the photoexcited CdS QD gel via a d-HAT mechanism. This d-HAT mechanism is supported by the linear correlation between the logarithm of the C-H bond activation rate constant and the C-H bond dissociation energy (BDE) with a Brønsted slope α=0.5. Our findings expand the currently limited direct hydrogen atom transfer photocatalysis toolbox and provide new possibilities for photocatalytic C-H activation.
Project description:The choice of Gaussian basis functions for computing the ground-state properties of molecules and clusters, employing wave function-based electron-correlated approaches, is a well-studied subject. However, the same cannot be said when it comes to the excited-state properties of such systems, in general, and optical properties, in particular. The aim of the present study is to understand how the choice of basis functions affects the calculations of linear optical absorption in clusters, qualitatively and quantitatively. For this purpose, we have calculated linear optical absorption spectra of several small charged and neutral clusters, namely, Li2, Li3, Li4, B2 +, B3 +, Be2 +, and Be3 +, using a variety of Gaussian basis sets. The calculations were performed within the frozen-core approximation, and a rigorous account of electron correlation effects in the valence sector was taken by employing various levels of configuration interaction (CI) approach both for the ground and excited states. Our results on the peak locations in the absorption spectra of Li3 and Li4 are in very good agreement with the experiments. Our general recommendation is that for excited-state calculations, it is very important to utilize those basis sets which contain augmented functions. Relatively smaller aug-cc-pVDZ basis sets also yield high-quality results for photoabsorption spectra and are recommended for such calculations if the computational resources are limited.
Project description:The explicit polarization (X-Pol) theory is a fragment-based quantum chemical method that explicitly models the internal electronic polarization and intermolecular interactions of a chemical system. X-Pol theory provides a framework to construct a quantum mechanical force field, which we have extended to liquid hydrogen fluoride (HF) in this work. The parameterization, called XPHF, is built upon the same formalism introduced for the XP3P model of liquid water, which is based on the polarized molecular orbital (PMO) semiempirical quantum chemistry method and the dipole-preserving polarization consistent point charge model. We introduce a fluorine parameter set for PMO, and find good agreement for various gas-phase results of small HF clusters compared to experiments and ab initio calculations at the M06-2X/MG3S level of theory. In addition, the XPHF model shows reasonable agreement with experiments for a variety of structural and thermodynamic properties in the liquid state, including radial distribution functions, interaction energies, diffusion coefficients, and densities at various state points.