Ab initio statistical mechanics of surface adsorption and desorption: I. H2_2O on MgO (001) at low coverage

We present a general computational scheme based on molecular dynamics (m.d.) simulation for calculating the chemical potential of adsorbed molecules in thermal equilibrium on the surface of a material. The scheme is based on the calculation of the mean force in m.d. simulations in which the height of a chosen molecule above the surface is constrained, and subsequent integration of the mean force to obtain the potential of mean force and hence the chemical potential. The scheme is valid at any coverage and temperature, so that in principle it allows the calculation of the chemical potential as a function of coverage and temperature. It avoids all statistical mechanical approximations, except for the use of classical statistical mechanics for the nuclei, and assumes nothing in advance about the adsorption sites. From the chemical potential, the absolute desorption rate of the molecules can be computed, provided the equilibration rate on the surface is faster than the desorption rate. We apply the theory by {\em ab initio} m.d. simulation to the case of H$_2$O on MgO (001) in the low-coverage limit, using the Perdew-Burke-Ernzerhof (PBE) form of exchange-correlation. The calculations yield an {\em ab initio} value of the Polanyi-Wigner frequency prefactor, which is more than two orders of magnitude greater than the value of $10^{13}$ s$^{-1}$ often assumed in the past. Provisional comparison with experiment suggests that the PBE adsorption energy may be too low, but the extension of the calculations to higher coverages is needed before firm conclusions can be drawn. The possibility of including quantum nuclear effects by using path-integral simulations is noted.Comment: 11 pages + 10 figure

First-principles kinetic Monte Carlo simulations for heterogeneous catalysis, applied to the CO oxidation at RuO2(110)

We describe a first-principles statistical mechanics approach enabling us to simulate the steady-state situation of heterogeneous catalysis. In a first step density-functional theory together with transition-state theory is employed to obtain the energetics of all relevant elementary processes. Subsequently the statistical mechanics problem is solved by the kinetic Monte Carlo method, which fully accounts for the correlations, fluctuations, and spatial distributions of the chemicals at the surface of the catalyst under steady-state conditions. Applying this approach to the catalytic oxidation of CO at RuO2(110), we determine the surface atomic structure and composition in reactive environments ranging from ultra-high vacuum (UHV) to technologically relevant conditions, i.e. up to pressures of several atmospheres and elevated temperatures. We also compute the CO2 formation rates (turnover frequencies). The results are in quantitative agreement with all existing experimental data. We find that the high catalytic activity of this system is intimately connected with a disordered, dynamic surface ``phase'' with significant compositional fluctuations. In this active state the catalytic function results from a self-regulating interplay of several elementary processes.Comment: 18 pages including 9 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Only a Single Taxonomically Restricted Gene Family in the Drosophila melanogaster Subgroup Can Be Identified with High Confidence

Taxonomically restricted genes (TRGs) are genes that are present only in one clade. Protein-coding TRGs may evolve de novo from previously noncoding sequences: functional ncRNA, introns, or alternative reading frames of older protein-coding genes, or intergenic sequences. A major challenge in studying de novo genes is the need to avoid both false-positives (nonfunctional open reading frames and/or functional genes that did not arise de novo) and false-negatives. Here, we search conservatively for high-confidence TRGs as the most promising candidates for experimental studies, ensuring functionality through conservation across at least two species, and ensuring de novo status through examination of homologous noncoding sequences. Our pipeline also avoids ascertainment biases associated with preconceptions of how de novo genes are born. We identify one TRG family that evolved de novo in the Drosophila melanogaster subgroup. This TRG family contains single-copy genes in Drosophila simulans and Drosophila sechellia. It originated in an intron of a well-established gene, sharing that intron with another well-established gene upstream. These TRGs contain an intron that predates their open reading frame. These genes have not been previously reported as de novo originated, and to our knowledge, they are the best Drosophila candidates identified so far for experimental studies aimed at elucidating the properties of de novo genes

Hsp90 depletion goes wild

Hsp90 reveals phenotypic variation in the laboratory, but is Hsp90 depletion important in the wild? Recent work from Chen and Wagner in BMC Evolutionary Biology has discovered a naturally occurring Drosophila allele that downregulates Hsp90, creating sensitivity to cryptic genetic variation. Laboratory studies suggest that the exact magnitude of Hsp90 downregulation is important. Extreme Hsp90 depletion might reactivate transposable elements and/or induce aneuploidy, in addition to revealing cryptic genetic variation

Complex Adaptations Can Drive the Evolution of the Capacitor [PSI+], Even with Realistic Rates of Yeast Sex

The [PSI+] prion may enhance evolvability by revealing previously cryptic genetic variation, but it is unclear whether such evolvability properties could be favored by natural selection. Sex inhibits the evolution of other putative evolvability mechanisms, such as mutator alleles. This paper explores whether sex also prevents natural selection from favoring modifier alleles that facilitate [PSI+] formation. Sex may permit the spread of “cheater” alleles that acquire the benefits of [PSI+] through mating without incurring the cost of producing [PSI+] at times when it is not adaptive. Using recent quantitative estimates of the frequency of sex in Saccharomyces paradoxus, we calculate that natural selection for evolvability can drive the evolution of the [PSI+] system, so long as yeast populations occasionally require complex adaptations involving synergistic epistasis between two loci. If adaptations are always simple and require substitution at only a single locus, then the [PSI+] system is not favored by natural selection. Obligate sex might inhibit the evolution of [PSI+]-like systems in other species

On the statistical mechanics of prion diseases

We simulate a two-dimensional, lattice based, protein-level statistical mechanical model for prion diseases (e.g., Mad Cow disease) with concommitant prion protein misfolding and aggregation. Our simulations lead us to the hypothesis that the observed broad incubation time distribution in epidemiological data reflect fluctuation dominated growth seeded by a few nanometer scale aggregates, while much narrower incubation time distributions for innoculated lab animals arise from statistical self averaging. We model `species barriers' to prion infection and assess a related treatment protocol.Comment: 5 Pages, 3 eps figures (submitted to Physical Review Letters

Dynamic reconfiguration of human brain networks during learning

Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes -- flexibility and selection -- must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we explore the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.Comment: Main Text: 19 pages, 4 figures Supplementary Materials: 34 pages, 4 figures, 3 table

Trends and patterns in the public awareness of palliative care, euthanasia, and end-of-life decisions in 3 central european countries using big data analysis from google: retrospective analysis

BackgroundEnd-of-life decisions, specifically the provision of euthanasia and assisted suicide services, challenge traditional medical and ethical principles. Austria and Germany have decided to liberalize their laws restricting assisted suicide, thus reigniting the debate about a meaningful framework in which the practice should be embedded. Evidence of the relevance of assisted suicide and euthanasia for the general population in Germany and Austria is limited. ObjectiveThe aim of this study is to examine whether the public awareness documented by search activities in the most frequently used search engine, Google, on the topics of palliative care, euthanasia, and advance health care directives changed with the implementation of palliative care services and new governmental regulations concerning end-of-life decisions. MethodsWe searched for policies, laws, and regulations promulgated or amended in Austria, Germany, and Switzerland between 2004 and 2020 and extracted data on the search volume for each search term topic from Google Trends as a surrogate of public awareness and interest. Annual averages were analyzed using the Joinpoint Regression Program. ResultsImportant policy changes yielded significant changes in search trends for the investigated topics. The enactment of laws regulating advance health care directives coincided with a significant drop in the volume of searches for the topic of euthanasia in all 3 countries (Austria: −24.48%, P=.02; Germany: −14.95%, P<.001; Switzerland: −11.75%, P=.049). Interest in palliative care increased with the availability of care services and the implementation of laws and policies to promote palliative care (Austria: 22.69%, P=.01; Germany: 14.39, P<.001; Switzerland: 17.59%, P<.001). The search trends for advance health care directives showed mixed results. While interest remained steady in Austria within the study period, it increased by 3.66% (P<.001) in Switzerland and decreased by 2.85% (P<.001) in Germany. ConclusionsOur results demonstrate that legal measures securing patients’ autonomy at the end of life may lower the search activities for topics related to euthanasia and assisted suicide. Palliative care may be a meaningful way to raise awareness of the different options for end-of-life care and to guide patients in their decision-making process regarding the same

Carbon Dioxide and Water Electrolysis Using New Alkaline Stable Anion Membranes

The recent development and market introduction of a new type of alkaline stable imidazole-based anion exchange membrane and related ionomers by Dioxide Materials is enabling the advancement of new and improved electrochemical processes which can operate at commercially viable operating voltages, current efficiencies, and current densities. These processes include the electrochemical conversion of CO2 to formic acid (HCOOH), CO2 to carbon monoxide (CO), and alkaline water electrolysis, generating hydrogen at high current densities at low voltages without the need for any precious metal electrocatalysts. The first process is the direct electrochemical generation of pure formic acid in a three-compartment cell configuration using the alkaline stable anion exchange membrane and a cation exchange membrane. The cell operates at a current density of 140 mA/cm2 at a cell voltage of 3.5 V. The power consumption for production of formic acid (FA) is about 4.3–4.7 kWh/kg of FA. The second process is the electrochemical conversion of CO2 to CO, a key focus product in the generation of renewable fuels and chemicals. The CO2 cell consists of a two-compartment design utilizing the alkaline stable anion exchange membrane to separate the anode and cathode compartments. A nanoparticle IrO2 catalyst on a GDE structure is used as the anode and a GDE utilizing a nanoparticle Ag/imidazolium-based ionomer catalyst combination is used as a cathode. The CO2 cell has been operated at current densities of 200 to 600 mA/cm2 at voltages of 3.0 to 3.2 respectively with CO2 to CO conversion selectivities of 95–99%. The third process is an alkaline water electrolysis cell process, where the alkaline stable anion exchange membrane allows stable cell operation in 1 M KOH electrolyte solutions at current densities of 1 A/cm2 at about 1.90 V. The cell has demonstrated operation for thousands of hours, showing a voltage increase in time of only 5 μV/h. The alkaline electrolysis technology does not require any precious metal catalysts as compared to polymer electrolyte membrane (PEM) design water electrolyzers. In this paper, we discuss the detailed technical aspects of these three technologies utilizing this unique anion exchange membrane