Ab initio calculations of the hydrogen bond

Recent x-ray Compton scattering experiments in ice have provided useful information about the quantum nature of the interaction between H$_2$O monomers. The hydrogen bond is characterized by a certain amount of charge transfer which could be determined in a Compton experiment. We use ab-initio simulations to investigate the hydrogen bond in H$_2$O structures by calculating the Compton profile and related quantities in three different systems, namely the water dimer, a cluster containing 12 water molecules and the ice crystal. We show how to extract estimates of the charge transfer from the Compton profiles.Comment: 16 pages, 7 figures, to appear in Phys. Rev.

SCN1A variants from bench to bedside-improved clinical prediction from functional characterization

Variants in the SCN1A gene are associated with a wide range of disorders including genetic epilepsy with febrile seizures plus (GEFS+), familial hemiplegic migraine (FHM), and the severe childhood epilepsy Dravet syndrome (DS). Predicting disease outcomes based on variant type remains challenging. Despite thousands of SCN1A variants being reported, only a minority has been functionally assessed. We review the functional SCN1A work performed to date, critically appraise electrophysiological measurements, compare this to in silico predictions, and relate our findings to the clinical phenotype. Our results show, regardless of the underlying phenotype, that conventional in silico software correctly predicted benign from pathogenic variants in nearly 90%, however was unable to differentiate within the disease spectrum (DS vs. GEFS+ vs. FHM). In contrast, patch‐clamp data from mammalian expression systems revealed functional differences among missense variants allowing discrimination between disease severities. Those presenting with milder phenotypes retained a degree of channel function measured as residual whole‐cell current, whereas those without any whole‐cell current were often associated with DS (p = .024). These findings demonstrate that electrophysiological data from mammalian expression systems can serve as useful disease biomarker when evaluating SCN1A variants, particularly in view of new and emerging treatment options in DS

Work functions, ionization potentials, and in-between: Scaling relations based on the image charge model

We revisit a model in which the ionization energy of a metal particle is associated with the work done by the image charge force in moving the electron from infinity to a small cut-off distance just outside the surface. We show that this model can be compactly, and productively, employed to study the size dependence of electron removal energies over the range encompassing bulk surfaces, finite clusters, and individual atoms. It accounts in a straightforward manner for the empirically known correlation between the atomic ionization potential (IP) and the metal work function (WF), IP/WF$\sim$2. We formulate simple expressions for the model parameters, requiring only a single property (the atomic polarizability or the nearest neighbor distance) as input. Without any additional adjustable parameters, the model yields both the IP and the WF within $\sim$10% for all metallic elements, as well as matches the size evolution of the ionization potentials of finite metal clusters for a large fraction of the experimental data. The parametrization takes advantage of a remarkably constant numerical correlation between the nearest-neighbor distance in a crystal, the cube root of the atomic polarizability, and the image force cutoff length. The paper also includes an analytical derivation of the relation of the outer radius of a cluster of close-packed spheres to its geometric structure.Comment: Original submission: 8 pages with 7 figures incorporated in the text. Revised submission (added one more paragraph about alloy work functions): 18 double spaced pages + 8 separate figures. Accepted for publication in PR

Ab initio studies of structures and properties of small potassium clusters

We have studied the structure and properties of potassium clusters containing even number of atoms ranging from 2 to 20 at the ab initio level. The geometry optimization calculations are performed using all-electron density functional theory with gradient corrected exchange-correlation functional. Using these optimized geometries we investigate the evolution of binding energy, ionization potential, and static polarizability with the increasing size of the clusters. The polarizabilities are calculated by employing Moller-Plesset perturbation theory and time dependent density functional theory. The polarizabilities of dimer and tetramer are also calculated by employing large basis set coupled cluster theory with single and double excitations and perturbative triple excitations. The time dependent density functional theory calculations of polarizabilities are carried out with two different exchange-correlation potentials: (i) an asymptotically correct model potential and (ii) within the local density approximation. A systematic comparison with the other available theoretical and experimental data for various properties of small potassium clusters mentioned above has been performed. These comparisons reveal that both the binding energy and the ionization potential obtained with gradient corrected potential match quite well with the already published data. Similarly, the polarizabilities obtained with Moller-Plesset perturbation theory and with model potential are quite close to each other and also close to experimental data.Comment: 33 pages including 10 figure

Genotype–phenotype associations in 1018 individuals with SCN1A-related epilepsies

Objective: SCN1A variants are associated with epilepsy syndromes ranging from mild genetic epilepsy with febrile seizures plus (GEFS+) to severe Dravet syndrome (DS). Many variants are de novo, making early phenotype prediction difficult, and genotype–phenotype associations remain poorly understood. Methods: We assessed data from a retrospective cohort of 1018 individuals with SCN1A-related epilepsies. We explored relationships between variant characteristics (position, in silico prediction scores: Combined Annotation Dependent Depletion (CADD), Rare Exome Variant Ensemble Learner (REVEL), SCN1A genetic score), seizure characteristics, and epilepsy phenotype. Results: DS had earlier seizure onset than other GEFS+ phenotypes (5.3 vs. 12.0 months, p <.001). In silico variant scores were higher in DS versus GEFS+ (p <.001). Patients with missense variants in functionally important regions (conserved N-terminus, S4–S6) exhibited earlier seizure onset (6.0 vs. 7.0 months, p =.003) and were more likely to have DS (280/340); those with missense variants in nonconserved regions had later onset (10.0 vs. 7.0 months, p =.036) and were more likely to have GEFS+ (15/29, χ2 = 19.16, p <.001). A minority of protein-truncating variants were associated with GEFS+ (10/393) and more likely to be located in the proximal first and last exon coding regions than elsewhere in the gene (9.7% vs. 1.0%, p <.001). Carriers of the same missense variant exhibited less variability in age at seizure onset compared with carriers of different missense variants for both DS (1.9 vs. 2.9 months, p =.001) and GEFS+ (8.0 vs. 11.0 months, p =.043). Status epilepticus as presenting seizure type is a highly specific (95.2%) but nonsensitive (32.7%) feature of DS. Significance: Understanding genotype–phenotype associations in SCN1A-related epilepsies is critical for early diagnosis and management. We demonstrate an earlier disease onset in patients with missense variants in important functional regions, the occurrence of GEFS+ truncating variants, and the value of in silico prediction scores. Status epilepticus as initial seizure type is a highly specific, but not sensitive, early feature of DS

Genotype–phenotype associations in 1018 individuals with SCN1A‐related epilepsies

Objective: SCN1A variants are associated with epilepsy syndromes ranging from mild genetic epilepsy with febrile seizures plus (GEFS+) to severe Dravet syndrome (DS). Many variants are de novo, making early phenotype prediction difficult, and genotype–phenotype associations remain poorly understood. Methods: We assessed data from a retrospective cohort of 1018 individuals with SCN1A-related epilepsies. We explored relationships between variant characteristics (position, in silico prediction scores: Combined Annotation Dependent Depletion (CADD), Rare Exome Variant Ensemble Learner (REVEL), SCN1A genetic score), seizure characteristics, and epilepsy phenotype. Results: DS had earlier seizure onset than other GEFS+ phenotypes (5.3 vs. 12.0 months, p &lt; .001). In silico variant scores were higher in DS versus GEFS+ (p &lt; .001). Patients with missense variants in functionally important regions (conserved N-terminus, S4–S6) exhibited earlier seizure onset (6.0 vs. 7.0 months, p = .003) and were more likely to have DS (280/340); those with missense variants in nonconserved regions had later onset (10.0 vs. 7.0 months, p = .036) and were more likely to have GEFS+ (15/29, χ2 = 19.16, p &lt; .001). A minority of protein-truncating variants were associated with GEFS+ (10/393) and more likely to be located in the proximal first and last exon coding regions than elsewhere in the gene (9.7% vs. 1.0%, p &lt; .001). Carriers of the same missense variant exhibited less variability in age at seizure onset compared with carriers of different missense variants for both DS (1.9 vs. 2.9 months, p = .001) and GEFS+ (8.0 vs. 11.0 months, p = .043). Status epilepticus as presenting seizure type is a highly specific (95.2%) but nonsensitive (32.7%) feature of DS. Significance: Understanding genotype–phenotype associations in SCN1A-related epilepsies is critical for early diagnosis and management. We demonstrate an earlier disease onset in patients with missense variants in important functional regions, the occurrence of GEFS+ truncating variants, and the value of in silico prediction scores. Status epilepticus as initial seizure type is a highly specific, but not sensitive, early feature of DS

Electrochemical characteristics of xLi(2)MnO(3)-(1-x)Li(Mn0.375Ni0.375Co0.25)O-2 (0.0 <= x <= 1.0) composite cathodes: Effect of particle and Li2MnO3 domain size

We have investigated the electrochemical characteristics of a series of high capacity xLi(2)MnO(3)-(1-x)Li(Mn0.375Ni0.375Co0.25)O-2 (0.0 <= x <= 1.0) integrated cathodes. Among several interrelated factors (viz. nominal molar content of Li2MnO3 and Li(Mn0.375Ni0.375Co0.25)O2 constituents, activation of Li2MnO3 component, crystallinity of the particles etc) an optimum particle size is argued to be most critical to yield better electrochemical performance of the synthesized cathodes. Through X-ray diffraction in conjunction with micro-Raman spectroscopy and high resolution transmission microscopy analyses we have demonstrated that with the increase of nominal Li2MnO3 contents, the size of the ordered nano-domains (inside the active matrix) and the average size of the composite cathode particles increase systematically. The size of the ordered nano-domains, cathode particles, and electrochemically triggered layer to spinel phase transformation influence the electrochemical characteristics of these cathodes. The average particle size of 0.5Li(2)MnO(3)-0.5Li(Mn0.375Ni0.375Co0.25)O-2 particles have been systematically varied by tuning the calcination time temperature combination. The optimized cathode yields a discharge capacity similar to 300 mAhg(-1) with capacity retention about 96% after 50 charge-discharge cycles at 10 mAg(-1) rate. The cathode with optimal particle size also exhibits a decent rate capability with room temperature discharge capacity similar to 200 mAhg(-1) at 300 mAg(-1) rate. (C) 2014 Elsevier Ltd. All rights reserved

Performance of wet chemical synthesized xLi(2)MnO(3)-(1-x)Li(Mn0.375Ni0.375Co0.25)O-2 (0.0 <= x <= 1.0) integrated cathode for lithium rechargeable battery

In the present work, we have reported the electrochemical performance of xLi(2)MnO(3)-(1-x)Li(Mn0.375Ni0.375Co0.25)O-2 (0.0 = 0.5) integrated cathodes to economic environmentally benign manganese rich, high voltage, high capacity lithium ion batteries. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.081207jes] All rights reserved