Fluctuation-Driven Molecular Transport in an Asymmetric Membrane Channel

Channel proteins, that selectively conduct molecules across cell membranes, often exhibit an asymmetric structure. By means of a stochastic model, we argue that channel asymmetry in the presence of non-equilibrium fluctuations, fueled by the cell's metabolism as observed recently, can dramatically influence the transport through such channels by a ratchet-like mechanism. For an aquaglyceroporin that conducts water and glycerol we show that a previously determined asymmetric glycerol potential leads to enhanced inward transport of glycerol, but for unfavorably high glycerol concentrations also to enhanced outward transport that protects a cell against poisoning.Comment: REVTeX4, 4 pages, 3 figures; Accepted for publication in Phys. Rev. Let

The nature and role of experiential knowledge for environmental conservation

Understanding the nature and role of experiential knowledge for environmental conservation is a necessary step towards understanding if it should be used and how it might be applied with other types of knowledge in an evidence-based approach. This paper describes the nature of experiential and expert knowledge. It then discusses the role of experiential knowledge as a complement to scientific knowledge and explains the interplay between experiential knowledge with conservation research and practice using a simple conceptual model of how individuals learn. There are five main conclusions: (1) because experiential knowledge will always play a role in decision-making, enhancing ability to learn from experiences (including research) will have a significant influence on the effectiveness of conservation outcomes; (2) while experiential knowledge is qualitatively very different from quantitative information, both are important and complementary; (3) some experiential knowledge can be expressed quantitatively, but experiential knowledge can be difficult to isolate as single facts or propositions and qualitative methods will therefore often be required to elicit experiential knowledge; (4) because each person's expertise is unique, when using experiential knowledge the extent of a person's experience and its relevance to a particular problem need to be specified; and (5) as with any form of knowledge, there are limitations to that derived from personal experience. Synthesis and communication of research is therefore essential to help prevent erroneous thinking and, where possible, experiential knowledge should be used in conjunction with other types of information to guide conservation actions.Publisher PDFPeer reviewe

Infrared Peak Splitting from Phonon Localization in Solid Hydrogen

We show that the isotope effect leads to a completely different spectroscopic signal in hydrogen-deuterium mixtures, compared to pure elements that have the same crystal structure. This is particularly true for molecular vibrations, which are the main source of information about the structure of high-pressure hydrogen. Mass disorder breaks translational symmetry, meaning that vibrations are localized almost to single molecules, and are not zone-center phonons. In mixtures, each observable IR peak corresponds to a collection of many such molecular vibrations, which have a distribution of frequencies depending on local environment. Furthermore discrete groups of environments cause the peaks to split. We illustrate this issue by considering the IR spectrum of the high pressure Phase III structure of hydrogen, recently interpreted as showing novel phases in isotopic mixtures. We calculate the IR spectrum of hydrogen/deuterium mixtures in the $C2/c$ and $Cmca$-12 structures, showing that isotopic disorder gives rise to mode localization of the high frequency vibrons. The local coordination of the molecules leads to discrete IR peaks. The spread of frequencies is strongly enhanced with pressure, such that more peaks become resolvable at higher pressures, in agreement with the recent measurements.Comment: Final author versio

Machine Learning Solvation Environments in Conductive Polymers: Application to ProDOT-2Hex with Solvent Swelling

Automated identification and classification of ion solvation sites in diverse chemical systems will improve the understanding and design of polymer electrolytes for battery applications. We introduce a machine learning approach to classify and characterize ion solvation environments based on feature vectors extracted from all-atom simulations. This approach is demonstrated in poly(3,4-propylenedioxythiophene), which is a promising candidate polymer binder for Li-ion batteries. In the dry polymer, four distinct Li⁺ solvation environments are identified close to the backbone of the polymer. Upon swelling of the polymer with propylene carbonate solvent, the nature of Li⁺ solvation changes dramatically, featuring a rapid diversification of solvation environments. This application of machine learning can be generalized to other polymer condensed-phase systems to elucidate the molecular mechanisms underlying ion solvation

On certain surfaces in the Euclidean space E3{\mathbb{E}}^3

In the present paper we classify all surfaces in \E^3 with a canonical principal direction. Examples of these type of surfaces are constructed. We prove that the only minimal surface with a canonical principal direction in the Euclidean space ${\mathbb{E}}^3$ is the catenoid.Comment: 13 Latex page