Inelastic Quantum Transport

We solve a Schrodinger equation for inelastic quantum transport that retains full quantum coherence, in contrast to previous rate or Boltzmann equation approaches. The model Hamiltonian is the zero temperature 1d Holstein model for an electron coupled to optical phonons (polaron), in a strong electric field. The Hilbert space grows exponentially with electron position, forming a non-standard Bethe lattice. We calculate nonperturbatively the transport current, electron-phonon correlations, and quantum diffusion. This system is a toy model for the constantly branching ``wavefunction of the universe''.Comment: revtex, 13 pages, 4 figure

Spectral Properties of Quasiparticle Excitations Induced by Magnetic Moments in Superconductors

The consequences of localized, classical magnetic moments in superconductors are explored and their effect on the spectral properties of the intragap bound states is studied. Above a critical moment, a localized quasiparticle excitation in an s-wave superconductor is spontaneously created near a magnetic impurity, inducing a zero-temperature quantum transition. In this transition, the spin quantum number of the ground state changes from zero to 1/2, while the total charge remains the same. In contrast, the spin-unpolarized ground state of a d-wave superconductor is found to be stable for any value of the magnetic moment when the normal-state energy spectrum possesses particle-hole symmetry. The effect of impurity scattering on the quasiparticle states is interpreted in the spirit of relevant symmetries of the clean superconductor. The results obtained by the non-self-consistent (T matrix) and the self-consistent mean-field approximations are compared and qualitative agreement between the two schemes is found in the regime where the coherence length is longer than the Fermi length.Comment: to appear in Phys. Rev. B55, May 1st (1997

Local Electronic Structure of a Single Magnetic Impurity in a Superconductor

The electronic structure near a single classical magnetic impurity in a superconductor is determined using a fully self-consistent Koster-Slater algorithm. Localized excited states are found within the energy gap which are half electron and half hole. Within a jellium model we find the new result that the spatial structure of the positive-frequency (electron-like) spectral weight (or local density of states), can differ strongly from that of the negative frequency (hole-like) spectral weight. The effect of the impurity on the continuum states above the energy gap is calculated with good spectral resolution for the first time. This is also the first three-dimensional self-consistent calculation for a strong magnetic impurity potential.Comment: 13 pages, RevTex, change in heuristic picture, no change in numerical result

Local Electronic Structure of Defects in Superconductors

The electronic structure near defects (such as impurities) in superconductors is explored using a new, fully self-consistent technique. This technique exploits the short-range nature of the impurity potential and the induced change in the superconducting order parameter to calculate features in the electronic structure down to the atomic scale with unprecedented spectral resolution. Magnetic and non-magnetic static impurity potentials are considered, as well as local alterations in the pairing interaction. Extensions to strong-coupling superconductors and superconductors with anisotropic order parameters are formulated.Comment: RevTex source, 20 pages including 22 figures in text with eps

Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

<p>Abstract</p> <p>Background</p> <p><it>Geobacter sulfurreducens </it>is a member of the <it>Geobacter </it>species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for <it>Geobacter sulfurreducens</it>. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of <it>G. sulfurreducens </it>using thermodynamic variability analysis.</p> <p>Findings</p> <p>As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in <it>E. coli </it>by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of <it>G. sulfurreducens </it>that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility) is significant for these reactions.</p> <p>Conclusions</p> <p>Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of Δ_rG' of every reaction in the model leading to the prediction of regulatory sites in the metabolic network, thereby characterizing the regulatory network in both a model organism such as <it>E. coli </it>as well as a non model organism such as <it>G. sulfurreducens</it>.</p

Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

<p>Abstract</p> <p>Background</p> <p>In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.</p> <p>Results</p> <p>To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of <it>Escherichia coli </it>(931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.</p> <p>Conclusion</p> <p>Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.</p

Defect passivation of transition metal dichalcogenides via a charge transfer van der Waals interface.

Integration of transition metal dichalcogenides (TMDs) into next-generation semiconductor platforms has been limited due to a lack of effective passivation techniques for defects in TMDs. The formation of an organic-inorganic van der Waals interface between a monolayer (ML) of titanyl phthalocyanine (TiOPc) and a ML of MoS2 is investigated as a defect passivation method. A strong negative charge transfer from MoS2 to TiOPc molecules is observed in scanning tunneling microscopy. As a result of the formation of a van der Waals interface, the ION/IOFF in back-gated MoS2 transistors increases by more than two orders of magnitude, whereas the degradation in the photoluminescence signal is suppressed. Density functional theory modeling reveals a van der Waals interaction that allows sufficient charge transfer to remove defect states in MoS2. The present organic-TMD interface is a model system to control the surface/interface states in TMDs by using charge transfer to a van der Waals bonded complex

anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data

Background: Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification extremely difficult. Furthermore, not only the actual measurement but also the subsequent interpretation of quantitative metabolome data to obtain mechanistic insights is still lacking behind the current expectations. Recently, the method of network-embedded thermodynamic (NET) analysis was introduced to address some of these open issues. Building upon principles of thermodynamics, this method allows for a quality check of measured metabolite concentrations and enables to spot metabolic reactions where active regulation potentially controls metabolic flux. So far, however, widespread application of NET analysis in metabolomics labs was hindered by the absence of suitable software. Results: We have developed in Matlab a generalized software called 'anNET' that affords a user-friendly implementation of the NET analysis algorithm. anNET supports the analysis of any metabolic network for which a stoichiometric model can be compiled. The model size can span from a single reaction to a complete genome-wide network reconstruction including compartments. anNET can (i) test quantitative data sets for thermodynamic consistency, (ii) predict metabolite concentrations beyond the actually measured data, (iii) identify putative sites of active regulation in the metabolic reaction network, and (iv) help in localizing errors in data sets that were found to be thermodynamically infeasible. We demonstrate the application of anNET with three published Escherichia coli metabolome data sets. Conclusion: Our user-friendly and generalized implementation of the NET analysis method in the software anNET allows users to rapidly integrate quantitative metabolome data obtained from virtually any organism. We envision that use of anNET in labs working on quantitative metabolomics will provide the systems biology and metabolic engineering communities with a mean to proof the quality of metabolome data sets and with all further benefits of the NET analysis approach.

Evidence for a Massive Post-Starburst Galaxy at z ~ 6.5

We present results from a search for high-redshift J--band ``dropout'' galaxies in the portion of the GOODS southern field that is covered by extremely deep imaging from the Hubble Ultradeep Field (HUDF).Using observations at optical, near-infrared and mid-infrared wavelengths from the Hubble and Spitzer Space Telescopes and the ESO-VLT, we search for very massive galaxies at high redshifts and find one particularly remarkable candidate. Its spectral energy distribution is consistent with a galaxy at z ~ 6.5 and a stellar mass of 6x10e11 M(sun) (for a Salpeter IMF). We interpret a prominent photometric break between the near-infrared and Spitzer bandpasses as the 3646A Balmer discontinuity. The best-fitting models have low reddening and ages of several hundred Myr, placing the formation of the bulk of the stars at z > 9. Alternative models of dusty galaxies at z ~ 2.5 are possible but provide significantly poorer fits. The object is detected with Spitzer at 24 micron. This emission originats from an obscured active nucleus or star formation. We present optical and near-infrared spectroscopy which has, thus far, failed to detect any spectral features. This helps limit the solution in which the galaxy is a starburst or active galaxy at z ~ 2.5. If the high-redshift interpretation is correct, this object would be an example of a galaxy that formed by a process strongly resembling traditional models of monolithic collapse, in a way which a very large mass of stars formed within a remarkably short period of time, at very high redshift.Comment: Accepted for publication in Ap.J. 31 pages, 6 diagram