Band alignment in quantum wells from automatically tuned DFT+U.

Band alignment between two materials is of fundamental importance for a multitude of applications. However, density functional theory (DFT) either underestimates the bandgap - as is the case with the local density approximation (LDA) or generalized gradient approximation (GGA) - or is highly computationally demanding, as is the case with hybrid-functional methods. The latter can become prohibitive in electronic-structure calculations of supercells which describe quantum wells. We propose to apply the DFT+U method, with U for each atomic shell being treated as set of tuning parameters, to automatically fit the bulk bandgap and the lattice constant, and then use the thus obtained U parameters in large supercell calculations to determine the band alignment. We apply this procedure to InP/In0.5Ga0.5As, In0.5Ga0.5As/In0.5Al0.5As and InP/In0.5Al0.5As quantum wells, and obtain good agreement with experimental results. Although this procedure requires some experimental input, it provides both meaningful valence and conduction band offsets while, crucially, lattice relaxation is taken into account. The computational cost of this procedure is comparable to that of LDA. We believe that this is a practical procedure that can be useful for providing accurate estimates of band alignments between more complicated alloys.

Reassessing Graphene Absorption and Emission Spectroscopy.

We present a new paradigm for understanding optical absorption and hot electron dynamics experiments in graphene. Our analysis pivots on assigning proper importance to phonon-assisted indirect processes and bleaching of direct processes. We show indirect processes figure in the excess absorption in the UV region. Experiments which were thought to indicate ultrafast relaxation of electrons and holes, reaching a thermal distribution from an extremely nonthermal one in under 5-10 fs, instead are explained by the nascent electron and hole distributions produced by indirect transitions. These need no relaxation or ad-hoc energy removal to agree with the observed emission spectra and fast pulsed absorption spectra. The fast emission following pulsed absorption is dominated by phonon-assisted processes, which vastly outnumber direct ones and are always available, connecting any electron with any hole any time. Calculations are given, including explicitly calculating the magnitude of indirect processes, supporting these views.

Preparation, applications, and digital simulation of carbon interdigitated array electrodes.

Carbon interdigitated array (IDA) electrodes with features sizes down to 1.2 µm were fabricated by controlled pyrolysis of patterned photoresist. Cyclic voltammetry of reversible redox species produced the expected steady-state currents. The collection efficiency depends on the IDA electrode spacing, which ranged from around 2.7 to 16.5 µm, with the smaller dimensions achieving higher collection efficiencies of up to 98%. The signal amplification because of redox cycling makes it possible to detect species at relatively low concentrations (10(-5) molar) and the small spacing allows detection of transient electrogenerated species with much shorter lifetimes (submillisecond). Digital simulation software that accounts for both the width and height of electrode elements as well as the electrode spacing was developed to model the IDA electrode response. The simulations are in quantitative agreement with experimental data for both a simple fast one electron redox reaction and an electron transfer with a following chemical reaction at the IDAs with larger gaps whereas currents measured for the smallest IDA electrodes, that were larger than the simulated currents, are attributed to convection from induced charge electrokinetic flow.

Internal relaxation in dye sensitized solar cells based on Zn2SnO4 nanostructures.

In this work we study the effect of internal relaxation in a (Bu(4)N)(2)Ru(dcbpyH)(2)(NCS)(2) (N719) dye molecule in a dye sensitized solar cell. Experimentally measured light intensity dependencies of short circuit current and open circuit voltage for two different types of photoanodes, ZTO (Zn(2)SnO(4)) nanorods and nanoparticles, are explained in the framework of the proposed microscopic theory. This theory is based on a density matrix equation with a Markovian relaxation term. The computational results are in favor of the fast relaxation inside the unoccupied and occupied bands rather than slow interband electron-hole recombination. The difference in experimental dependencies for ZTO nanorods and nanoparticles is explained by the difference in the electron transfer matrix elements, and therefore, the electron transfer injection constants for the different morphologies of the photoanodes.

Nonadiabatic dynamics of cobalt tricarbonyl nitrosyl for ligand dissociation induced by electronic excitation.

We utilize real-time time-dependent density functional theory and Ehrenfest dynamics scheme to investigate excited-state nonadiabatic dynamics of ligand dissociation of cobalt tricarbonyl nitrosyl, Co(CO)3NO, which is a precursor used for cobalt growth in advanced technologies, where the precursor's reaction is enhanced by electronic excitation. Based on the first-principles calculations, we demonstrate two dissociation pathways of the NO ligand on the precursor. Detailed electronic structures are further analyzed to provide an insight into dynamics following the electronic excitations. This study sheds light on computational demonstration and underlying mechanism of the electronic-excitation-induced dissociation, especially in molecules with complex chemical bonds such as the Co(CO)3NO.

Using evolutionary information to find specificity-determining and co-evolving residues.

Intricate networks of protein interactions rely on the ability of a protein to recognize its targets: other proteins, ligands, and sites on DNA and RNA. To recognize other molecules, it was suggested that a protein uses a small set of specificity-determining residues (SDRs). How can one find these residues in proteins and distinguish them from other functionally important amino acids? A number of bioinformatics methods to predict SDRs have been developed in recent years. These methods use genomic information and multiple sequence alignments to identify positions exhibiting a specific pattern of conservation and variability. The challenge is to delineate the evolutionary pattern of SDRs from that of the active site residues and the residues responsible for formation of the protein's structure. The phylogenetic history of a protein family makes such analysis particularly hard. Here we present two methods for finding the SDRs and the co-evolving residues (CERs) in proteins. We use a Monte Carlo approach for statistical inference, allowing us to reveal specific evolutionary patterns of SDRs and CERs. We apply these methods to study specific recognition in the bacterial two-component system and in the class Ia aminoacyl-tRNA synthetases. Our results agree well with structural information and the experimental analyses of these systems. Our results point at the complex and distinct patterns characteristic of the evolution of specificity in these systems.

Protein knot server: detection of knots in protein structures.

KNOTS (http://knots.mit.edu) is a web server that detects knots in protein structures. Several protein structures have been reported to contain intricate knots. The physiological role of knots and their effect on folding and evolution is an area of active research. The user submits a PDB id or uploads a 3D protein structure in PDB or mmCIF format. The current implementation of the server uses the Alexander polynomial to detect knots. The results of the analysis that are presented to the user are the location of the knot in the structure, the type of the knot and an interactive visualization of the knot. The results can also be downloaded and viewed offline. The server also maintains a regularly updated list of known knots in protein structures.

Imaginary-Time Time-Dependent Density Functional Theory and Its Application for Robust Convergence of Electronic States.

Reliable and robust convergence to the electronic ground state within density functional theory (DFT) Kohn-Sham (KS) calculations remains a thorny issue in many systems of interest. In such cases, charge sloshing can delay or completely hinder the convergence. Here, we use an approach based on transforming the time-dependent DFT equations to imaginary time, followed by imaginary-time evolution, as a reliable alternative to the self-consistent field (SCF) procedure for determining the KS ground state. We discuss the theoretical and technical aspects of this approach and show that the KS ground state should be expected to be the long-imaginary-time output of the evolution, independent of the exchange-correlation functional or the level of theory used to simulate the system. By maintaining self-consistency between the single-particle wave functions (orbitals) and the electronic density throughout the determination of the stationary state, our method avoids the typical difficulties encountered in SCF. To demonstrate dependability of our approach, we apply it to selected systems which struggle to converge with SCF schemes. In addition, through the van Leeuwen theorem, we affirm the physical meaningfulness of imaginary-time TDDFT, justifying its use in certain topics of statistical mechanics such as in computing imaginary-time path integrals.

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome.

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants.

Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae.

The progress in genome sequencing has led to a rapid accumulation in GenBank submissions of uncharacterized 'hypothetical' genes. These genes, which have not been experimentally characterized and whose functions cannot be deduced from simple sequence comparisons alone, now comprise a significant fraction of the public databases. Expression analyses of Haemophilus influenzae cells using a combination of transcriptomic and proteomic approaches resulted in confident identification of 54 'hypothetical' genes that were expressed in cells under normal growth conditions. In an attempt to understand the functions of these proteins, we used a variety of publicly available analysis tools. Close homologs in other species were detected for each of the 54 'hypothetical' genes. For 16 of them, exact functional assignments could be found in one or more public databases. Additionally, we were able to suggest general functional characterization for 27 more genes (comprising approximately 80% total). Findings from this analysis include the identification of a pyruvate-formate lyase-like operon, likely to be expressed not only in H.influenzae but also in several other bacteria. Further, we also observed three genes that are likely to participate in the transport and/or metabolism of sialic acid, an important component of the H.influenzae lipo-oligosaccharide. Accurate functional annotation of uncharacterized genes calls for an integrative approach, combining expression studies with extensive computational analysis and curation, followed by eventual experimental verification of the computational predictions.

The PEDANT genome database.

The PEDANT genome database (http://pedant.gsf.de) provides exhaustive automatic analysis of genomic sequences by a large variety of established bioinformatics tools through a comprehensive Web-based user interface. One hundred and seventy seven completely sequenced and unfinished genomes have been processed so far, including large eukaryotic genomes (mouse, human) published recently. In this contribution, we describe the current status of the PEDANT database and novel analytical features added to the PEDANT server in 2002. Those include: (i) integration with the BioRS data retrieval system which allows fast text queries, (ii) pre-computed sequence clusters in each complete genome, (iii) a comprehensive set of tools for genome comparison, including genome comparison tables and protein function prediction based on genomic context, and (iv) computation and visualization of protein-protein interaction (PPI) networks based on experimental data. The availability of functional and structural predictions for 650 000 genomic proteins in well organized form makes PEDANT a useful resource for both functional and structural genomics.

Real-Time TD-DFT with Classical Ion Dynamics: Methodology and Applications.

We present a method for real-time propagation of electronic wave functions, within time-dependent density functional theory (RT-TDDFT), coupled to ionic motion through mean-field classical dynamics. The goal of our method is to treat large systems and complex processes, in particular photocatalytic reactions and electron transfer events on surfaces and thin films. Due to the complexity of these processes, computational approaches are needed to provide insight into the underlying physical mechanisms and are therefore crucial for the rational design of new materials. Because of the short time step required for electron propagation (of order ∼10 attoseconds), these simulations are computationally very demanding. Our methodology is based on numerical atomic-orbital-basis sets for computational efficiency. In the computational package, to which we refer as TDAP-2.0 (Time-evolving Deterministic Atom Propagator), we have implemented a number of important features and analysis tools for more accurate and efficient treatment of large, complex systems and time scales that reach into a fraction of a picosecond. We showcase the capabilities of our method using four different examples: (i) photodissociation into radicals of opposite spin, (ii) hydrogen adsorption on aluminum surfaces, (iii) optical absorption of spin-polarized organic molecule containing a metal ion, and (iv) electron transfer in a prototypical dye-sensitized solar cell.

eReaxFF: A Pseudoclassical Treatment of Explicit Electrons within Reactive Force Field Simulations.

We present a computational tool, eReaxFF, for simulating explicit electrons within the framework of the standard ReaxFF reactive force field method. We treat electrons explicitly in a pseudoclassical manner that enables simulation several orders of magnitude faster than quantum chemistry (QC) methods, while retaining the ReaxFF transferability. We delineate here the fundamental concepts of the eReaxFF method and the integration of the Atom-condensed Kohn-Sham DFT approximated to second order (ACKS2) charge calculation scheme into the eReaxFF. We trained our force field to capture electron affinities (EA) of various species. As a proof-of-principle, we performed a set of molecular dynamics (MD) simulations with an explicit electron model for representative hydrocarbon radicals. We establish a good qualitative agreement of EAs of various species with experimental data, and MD simulations with eReaxFF agree well with the corresponding Ehrenfest dynamics simulations. The standard ReaxFF parameters available in the literature are transferrable to the eReaxFF method. The computationally economic eReaxFF method will be a useful tool for studying large-scale chemical and physical systems with explicit electrons as an alternative to computationally demanding QC methods.

Anatomy of the Photochemical Reaction: Excited-State Dynamics Reveals the C-H Acidity Mechanism of Methoxy Photo-oxidation on Titania.

Light-driven chemical reactions on semiconductor surfaces have potential for addressing energy and pollution needs through efficient chemical synthesis; however, little is known about the time evolution of excited states that determine reaction pathways. Here, we study the photo-oxidation of methoxy (CH3O) derived from methanol on the rutile TiO2(110) surface using ab initio simulations to create a molecular movie of the process. The movie sequence reveals a wealth of information on the reaction intermediates, time scales, and energetics. The reaction is broken in three stages, described by Lewis structures directly derived from the "hole" wave functions that lead to the concept of "photoinduced C-H acidity". The insights gained from this work can be generalized to a set of simple rules that can predict the efficiency of photo-oxidation reactions in reactant-catalyst pairs.

Lineage-specific differences in the amino acid substitution process.

In Darwinian evolution, mutations occur approximately at random in a gene, turned into amino acid mutations by the genetic code. Some mutations are fixed to become substitutions and some are eliminated from the population. Partitioning pairs of closely related species with complete genome sequences by average population size of each pair, we looked at the substitution matrices generated for these partitions and compared the substitution patterns between species. We estimated a population genetic model that relates the relative fixation probabilities of different types of mutations to the selective pressure and population size. Parameterizations of the average and distribution of selective pressures for different amino acid substitution types in different population size comparisons were generated with a Bayesian framework. We found that partitions in population size as well as in substitution type are required to explain the substitution data. Selection coefficients were found to decrease with increasingly radical amino acid substitution and with increasing effective population size. To further explore the role of underlying processes in amino acid substitution, we analyzed embryophyte (plant) gene families from TAED (The Adaptive Evolution Database), where solved structures for at least one member exist in the Protein Data Bank. Using PAML, we assigned branches to three categories: strong negative selection, moderate negative selection/neutrality, and positive diversifying selection. Focusing on the first and third categories, we identified sites changing along gene family lineages and observed the spatial patterns of substitution. Selective sweeps were expected to create primary sequence clustering under positive diversifying selection. Co-evolution through direct physical interaction was expected to cause tertiary structural clustering. Under both positive and negative selection, the substitution patterns were found to be nonrandom. Under positive diversifying selection, significant independent signals were found for primary and tertiary sequence clustering, suggesting roles for both selective sweeps and direct physical interaction. Under strong negative selection, the signals were not found to be independent. All together, a complex interplay of population genetic and protein thermodynamics forces is suggested.

Complex microsatellite dynamics in the myostatin gene within ruminants.

A microsatellite has previously been identified in myostatin in cattle. Sequencing of this region from other artiodactyls coupled with phylogenetic analysis has been used to uncover the potential origins of the microsatellite event, which appears either to have been born twice or to have been gained and lost within ruminants. While caprids and ovids share the ancestral state with pigs and other mammals, microsatellite activity (length polymorphism) is uncovered in both deer and bovids. The dynamic process of microsatellite evolution, including birth, is discussed here in light of several models. Finally, these models are evaluated in the context of patterns of microsatellite conservation between closely related mammalian genomes.

How gene order is influenced by the biophysics of transcription regulation.

What are the forces that shape the structure of prokaryotic genomes: the order of genes, their proximity, and their orientation? Coregulation and coordinated horizontal gene transfer are believed to promote the proximity of functionally related genes and the formation of operons. However, forces that influence the structure of the genome beyond the level of a single operon remain unknown. Here, we show that the biophysical mechanism by which regulatory proteins search for their sites on DNA can impose constraints on genome structure. Using simulations, we demonstrate that rapid and reliable gene regulation requires that the transcription factor (TF) gene be close to the site on DNA the TF has to bind, thus promoting the colocalization of TF genes and their targets on the genome. We use parameters that have been measured in recent experiments to estimate the relevant length and times scales of this process and demonstrate that the search for a cognate site may be prohibitively slow if a TF has a low copy number and is not colocalized. We also analyze TFs and their sites in a number of bacterial genomes, confirm that they are colocalized significantly more often than expected, and show that this observation cannot be attributed to the pressure for coregulation or formation of selfish gene clusters, thus supporting the role of the biophysical constraint in shaping the structure of prokaryotic genomes. Our results demonstrate how spatial organization can influence timing and noise in gene expression.

Phylogenetic web profiler.

SUMMARY: Phylogenetic Web Profiler (PWP) is a web-based service designed to perform phylogenetic profiling of proteins against genomes. The current version offers a selection of 63 completed genomes and available plasmids as annotated in the PEDANT genome database. Unlike currently available applications, this tool offers several choices of ortholog prediction parameters including E-value cutoff, percent length difference tolerance, and annotation similarity. Additional features include tight integration with the PEDANT database and tools to analyze properties of predicted proteins. PWP should prove very useful for the analysis of functional-linkage between proteins.

SNAPper: gene order predicts gene function.

UNLABELLED: SNAPper is a network service for predicting gene function based on the conservation of gene order. AVAILABILITY: The SNAPper server is available at http://pedant.gsf.de/snapper. SNAPper-based functional predictions will soon be offered as part of the PEDANT genome analysis server http://pedant.gsf.de.