Energy-scales convergence for optimal and robust quantum transport in photosynthetic complexes

Underlying physical principles for the high efficiency of excitation energy transfer in light-harvesting complexes are not fully understood. Notably, the degree of robustness of these systems for transporting energy is not known considering their realistic interactions with vibrational and radiative environments within the surrounding solvent and scaffold proteins. In this work, we employ an efficient technique to estimate energy transfer efficiency of such complex excitonic systems. We observe that the dynamics of the Fenna-Matthews-Olson (FMO) complex leads to optimal and robust energy transport due to a convergence of energy scales among all important internal and external parameters. In particular, we show that the FMO energy transfer efficiency is optimum and stable with respect to the relevant parameters of environmental interactions and Frenkel-exciton Hamiltonian including reorganization energy $\lambda$, bath frequency cutoff $\gamma$, temperature $T$, bath spatial correlations, initial excitations, dissipation rate, trapping rate, disorders, and dipole moments orientations. We identify the ratio of \lambda T/\gamma\*g as a single key parameter governing quantum transport efficiency, where g is the average excitonic energy gap.Comment: minor revisions, removing some figures, 19 pages, 19 figure

Interaction between Experiments, Analytical Theories, and Computation

This article is a summary of a talk given at the ACS Centennial Symposium in Physical Chemistry in Philadelphia in 2008, updated with more recent studies. In keeping with the spirit of the symposium, the article is in part historical and in part a review of the newer research. The talk was divided into two parts, the first on different isotopic effects in chemistry, including the mass-independent fractionation phenomenon in gases and H/D isotope effects in enzymes, and the second on two different surface phenomena, “The Bad and the Good”. The “Bad” is the fluorescence intermittency of semiconductor nanoparticles, (quantum dots, QD) being an unwanted feature in sensor applications. The “Good” is the “on water” catalysis of organic reactions, a mode of green chemistry. The possible role of Auger-type mechanisms in trapping and detrapping in the QD and hence in the formation of dark and light periods is explored. Some suggestions are made on the novel “breakpoint” phenomenon discovered for H transfer in a thermophilic enzyme

Angle-dependence of quantum oscillations in YBa2Cu3O6.59 shows free spin behaviour of quasiparticles

Measurements of quantum oscillations in the cuprate superconductors afford a new opportunity to assess the extent to which the electronic properties of these materials yield to a description rooted in Fermi liquid theory. However, such an analysis is hampered by the small number of oscillatory periods observed. Here we employ a genetic algorithm to globally model the field, angular, and temperature dependence of the quantum oscillations observed in the resistivity of YBa2Cu3O6.59. This approach successfully fits an entire data set to a Fermi surface comprised of two small, quasi-2-dimensional cylinders. A key feature of the data is the first identification of the effect of Zeeman splitting, which separates spin-up and spin-down contributions, indicating that the quasiparticles in the cuprates behave as nearly free spins, constraining the source of the Fermi surface reconstruction to something other than a conventional spin density wave with moments parallel to the CuO2 planes.Comment: 8 pages, 4 figure

Handwritten digit classification

Pattern recognition is one of the major challenges in statistics framework. Its goal is the feature extraction to classify the patterns into categories. A well-known example in this field is the handwritten digit recognition where digits have to be assigned into one of the 10 classes using some classification method. Our purpose is to present alternative classification methods based on statistical techniques. We show a comparison between a multivariate and a probabilistic approach, concluding that both methods provide similar results in terms of test-error rate. Experiments are performed on the known MNIST and USPS databases in binary-level image. Then, as an additional contribution we introduce a novel method to binarize images, based on statistical concepts associated to the written trace of the digitDigit, Classification, Images

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Mott physics and first-order transition between two metals in the normal state phase diagram of the two-dimensional Hubbard model

For doped two-dimensional Mott insulators in their normal state, the challenge is to understand the evolution from a conventional metal at high doping to a strongly correlated metal near the Mott insulator at zero doping. To this end, we solve the cellular dynamical mean-field equations for the two-dimensional Hubbard model using a plaquette as the reference quantum impurity model and continuous-time quantum Monte Carlo method as impurity solver. The normal-state phase diagram as a function of interaction strength $U$, temperature $T$, and filling $n$ shows that, upon increasing $n$ towards the Mott insulator, there is a surface of first-order transition between two metals at nonzero doping. That surface ends at a finite temperature critical line originating at the half-filled Mott critical point. Associated with this transition, there is a maximum in scattering rate as well as thermodynamic signatures. These findings suggest a new scenario for the normal-state phase diagram of the high temperature superconductors. The criticality surmised in these systems can originate not from a T=0 quantum critical point, nor from the proximity of a long-range ordered phase, but from a low temperature transition between two types of metals at finite doping. The influence of Mott physics therefore extends well beyond half-filling.Comment: 27 pages, 16 figures, LaTeX, published versio

An Investigation of the Requirements for Excimer Formation and Charge Stabilization in Model Pi-Stacked Assemblies

Formation of -stacked excimers plays an important role in many systems, ranging from biological phenomena and polymer formation and function to photovoltaic devices and organic molecular electronics. In these systems, the geometrical reorganization of the ground state upon photoexcitation is still a subject of debate. In this work, we compare the dynamics of excimer formation and hole (charge) stabilization in fluorene and fluorene-based model systems. We use a variety of gas-phase methods to examine the spectroscopy and dynamics of these systems, including Two-Color Resonant Two-Photon Ionization (2CR2PI), Hole-Burning (HB), Laser Induced Fluorescence (LIF), and Dispersed Fluorescence (DF). In order to quantify the clusters’ geometry, minimum, and relative energies, calculations using Density Functional Theory and high level ab initio methods are reported. These techniques were applied to better understand the energetic properties and behaviors of these model systems in their ground (S0), excited (S1), and ionized (M+•) states to probe the geometrical reorganization resulting in excimer formation and stabilization of charge. As model systems, we used fluorene based assemblies that are covalently linked by utilizing methylene or cyclohexane bridges, which connect two or more fluorene sub-units together. These are compared with clusters interacting at the van der Waals contact distance (3.5 Å). It was found that in both covalently linked and vdW bound systems, excimer formation is dominant; however, the excimer state is stabilized by covalent linkage. We also find cases in which the geometric requirements for excimer formation are not met. Almost every system studied displayed the ability to stabilize charge in its ionic state and therefore showed that the requirements necessary to delocalize charge are less stringent than those necessary for excimer formation

Multi-heme Cytochromes in Shewanella oneidensis MR-1:Structures, functions and opportunities

Multi-heme cytochromes are employed by a range of microorganisms to transport electrons over distances of up to tens of nanometers. Perhaps the most spectacular utilization of these proteins is in the reduction of extracellular solid substrates, including electrodes and insoluble mineral oxides of Fe(III) and Mn(III/IV), by species of Shewanella and Geobacter. However, multi-heme cytochromes are found in numerous and phylogenetically diverse prokaryotes where they participate in electron transfer and redox catalysis that contributes to biogeochemical cycling of N, S and Fe on the global scale. These properties of multi-heme cytochromes have attracted much interest and contributed to advances in bioenergy applications and bioremediation of contaminated soils. Looking forward there are opportunities to engage multi-heme cytochromes for biological photovoltaic cells, microbial electrosynthesis and developing bespoke molecular devices. As a consequence it is timely to review our present understanding of these proteins and we do this here with a focus on the multitude of functionally diverse multi-heme cytochromes in Shewanella oneidensis MR-1. We draw on findings from experimental and computational approaches which ideally complement each other in the study of these systems: computational methods can interpret experimentally determined properties in terms of molecular structure to cast light on the relation between structure and function. We show how this synergy has contributed to our understanding of multi-heme cytochromes and can be expected to continue to do so for greater insight into natural processes and their informed exploitation in biotechnologies