1,719 research outputs found

    Can Density Matrix Embedding Theory with the Complete Activate Space Self-Consistent Field Solver Describe Single and Double Bond Breaking in Molecular Systems?

    Full text link
    Density matrix embedding theory (DMET) [Phys. Rev. Lett.2012, 109, 186404] has been demonstrated as an efficient wave-function-based embedding method to treat extended systems. Despite its success in many quantum lattice models, the extension of DMET to real chemical systems has been tested only on selected cases. Herein, we introduce the use of the complete active space self-consistent field (CASSCF) method as a correlated impurity solver for DMET, leading to a method called CAS-DMET. We test its performance in describing the dissociation of a H-H single bond in a H10 ring model system and an N=N double bond in azomethane (CH3-N=N-CH3) and pentyldiazene (CH3(CH2)4-N=NH). We find that the performance of CAS-DMET is comparable to CASSCF with different active space choices when single-embedding DMET corresponding to only one embedding problem for the system is used. When multiple embedding problems are used for the system, the CAS-DMET is in a good agreement with CASSCF for the geometries around the equilibrium, but not in equal agreement at bond dissociation.Comment: 28 pages, 9 figures, TOC graphi

    Prediction of new inorganic molecules with quantum chemical methods

    Get PDF
    Quantum chemistry can today be employed to invent new molecules and explore unknown molecular bonding. An overview of novel species containing metals bound to polynitrogen clusters is presented. The prediction of metal polyhydrides is discussed. Finally, some species containing gold that behaves as a halogen are described, together with recent advances in actinide chemistry and exploration of the nature of the actinide-actinide chemical bondin

    Sobre lectores, lecturas y salud : Experiencias en la Biblioteca Ambulante del Hospital de Niños

    Get PDF
    Fil: Gagliardi, Lucas. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina

    Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

    Get PDF
    Background: The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals.Methods: We enrolled 96 participants (age range 50–75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features.Results: Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI.Conclusions: Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption

    MC-PDFT Can Calculate Singlet-Triplet Splittings of Organic Diradicals.

    Get PDF
    The singlet-triplet splittings of a set of diradical organic molecules are calculated using multiconfiguration pair-density functional theory (MC-PDFT) and the results are compared with those obtained by Kohn-Sham density functional theory (KS-DFT) and complete active space second-order perturbation theory (CASPT2) calculations. We found that MC-PDFT, even with small and systematically defined active spaces, is competitive in accuracy with CASPT2, and it yields results with greater accuracy and precision than Kohn-Sham DFT with the same parent functional. MC-PDFT also avoids the challenges associated with spin contamination in KS-DFT. It is also shown that MC-PDFT is much less computationally expensive than CASPT2 when applied to larger active spaces, and this illustrates the promise of this method for larger diradical organic systems

    Multireference Methods are Realistic and Useful Tools for Modeling Catalysis

    Get PDF
    Highly correlated systems, in particular those that include transition metals, are ubiquitous in catalysis. The significant static correlation found in such systems is often poorly accounted for using Kohn Sham density functional theory methods, as they are single determinantal in nature. Applications to catalysis of more rigorous and appropriate multiconfigurational methods have been reported in select instances, but their use remains rare. We discuss obstacles that hinder the routine application of multireference (MR) wave function theoretical calculations to catalytic systems and the current state of the art with respect to removing those obstacles

    Analytic Gradients for Complete Active Space Pair-Density Functional Theory

    Full text link
    Analytic gradient routines are a desirable feature for quantum mechanical methods, allowing for efficient determination of equilibrium and transition state structures and several other molecular properties. In this work, we present analytical gradients for multiconfiguration pair-density functional theory (MC-PDFT) when used with a state-specific complete active space self-consistent field reference wave function. Our approach constructs a Lagrangian that is variational in all wave function parameters. We find that MC-PDFT locates equilibrium geometries for several small- to medium-sized organic molecules that are similar to those located by complete active space second-order perturbation theory but that are obtained with decreased computational cost
    corecore