Designing materials for electrochemical carbon dioxide recycling

Electrochemical carbon dioxide recycling provides an attractive approach to synthesizing fuels and chemical feedstocks using renewable energy. On the path to deploying this technology, basic and applied scientific hurdles remain. Integrating catalytic design with mechanistic understanding yields scientific insights and progresses the technology towards industrial relevance. Catalysts must be able to generate valuable carbon-based products with better selectivity, lower overpotentials and improved current densities with extended operation. Here, we describe progress and identify mechanistic questions and performance metrics for catalysts that can enable carbon-neutral renewable energy storage and utilization

Sulfur-Modulated Tin Sites Enable Highly Selective Electrochemical Reduction of CO2 to Formate

Electrochemical reduction of carbon dioxide (CO2RR) to formate provides an avenue to the synthesis of value-added carbon-based fuels and feedstocks powered using renewable electricity. Here, we hypothesized that the presence of sulfur atoms in the catalyst surface could promote undercoordinated sites, and thereby improve the electrochemical reduction of CO2 to formate. We explored, using density functional theory, how the incorporation of sulfur into tin may favor formate generation. We used atomic layer deposition of SnSx followed by a reduction process to synthesize sulfur-modulated tin (Sn(S)) catalysts. X-ray absorption near-edge structure (XANES) studies reveal higher oxidation states in Sn(S) compared with that of tin in Sn nanoparticles. Sn(S)/Au accelerates CO2RR at geometric current densities of 55 mA cm−2 at −0.75 V versus reversible hydrogen electrode with a Faradaic efficiency of 93%. Furthermore, Sn(S) catalysts show excellent stability without deactivation (<2% productivity change) following more than 40 hours of operation. With rapid advances in the efficient and cost-effective conversion of sunlight to electrical power, the development of storage technologies for renewable energy is even more urgent. Using renewable electricity to convert CO2 into formate simultaneously addresses the need for storage of intermittent renewable energy sources and the need to reduce greenhouse gas emissions. We report an increase of greater than 4-fold in the current density (hence the rate of reaction) in formate electrosynthesis compared with relevant controls. Our catalysts also show excellent stability without deactivation (<2% productivity change) following more than 40 hours of operation. The electrochemical reduction of carbon dioxide (CO2RR) offers a compelling route to energy storage and high-value chemical manufacture. The presence of sulfur atoms in catalyst surfaces promotes undercoordinated sites, thereby improving the electrochemical reduction of CO2 to formate. The resulting sulfur-modulated tin catalysts accelerate CO2RR at geometric current densities of 55 mA cm−2 at −0.75 V versus RHE with a Faradaic efficiency of 93%

Vacuum Ambiguity in de Sitter Space at Strong Coupling

It is well known that in the weak coupling regime, quantum field theories in de Sitter space do not have a unique vacuum, but a class of vacua parametrized by a complex parameter $\alpha$, i.e., the so-called $\alpha$-vacua. In this article, using gauge/gravity duality, we calculate the symmetric two-point function of strongly coupled ${\cal N}=4$ supersymmetric Yang-Mills theory on $dS_3$. We find that there is a class of de Sitter invariant vacua, parametrized by a set of complex parameters $\{\alpha_{\nu}\}$.Comment: 17 pages in JHEP style, references adde

Exotic particles below the TeV from low scale flavour theories

A flavour gauge theory is observable only if the symmetry is broken at relatively low energies. The intrinsic parity-violation of the fermion representations in a flavour theory describing quark, lepton and higgsino masses and mixings generically requires anomaly cancellation by new fermions. Benchmark supersymmetric flavour models are built and studied to argue that: i) the flavour symmetry breaking should be about three orders of magnitude above the higgsino mass, enough also to efficiently suppress FCNC and CP violations coming from higher-dimensional operators; ii) new fermions with exotic decays into lighter particles are typically required at scales of the order of the higgsino mass.Comment: 19 pages, references added, one comment and one footnote added, results unchange

Vascular adaptation to exercise in humans: Role of hemodynamic stimuli

On the 400th anniversary of Harvey’s Lumleian lectures, this review focuses on “hemodynamic” forces associated with the movement of blood through arteries in humans and the functional and structural adaptations that result from repeated episodic exposure to such stimuli. The late 20th century discovery that endothelial cells modify arterial tone via paracrine transduction provoked studies exploring the direct mechanical effects of blood flow and pressure on vascular function and adaptation in vivo. In this review, we address the impact of distinct hemodynamic signals that occur in response to exercise, the interrelationships between these signals, the nature of the adaptive responses that manifest under different physiological conditions, and the implications for human health. Exercise modifies blood flow, luminal shear stress, arterial pressure, and tangential wall stress, all of which can transduce changes in arterial function, diameter, and wall thickness. There are important clinical implications of the adaptation that occurs as a consequence of repeated hemodynamic stimulation associated with exercise training in humans, including impacts on atherosclerotic risk in conduit arteries, the control of blood pressure in resistance vessels, oxygen delivery and diffusion, and microvascular health. Exercise training studies have demonstrated that direct hemodynamic impacts on the health of the artery wall contribute to the well-established decrease in cardiovascular risk attributed to physical activity. © 2017 the American Physiological Society

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms.

Because of the high costs associated with ascertainment of families, most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. Although microsatellite markers spaced every 10 cM typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carried out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 single-nucleotide polymorphisms. Of the ~1100 families, 972 were informative for further analyses, and mean information content was 0.86 after pruning for linkage disequilibrium. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with bipolar II disorder (BPII) and 702 subjects with recurrent major depression. Three affection status models (ASMs) were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus recurrent major depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (non-parametric pairs LOD 3.4 for rs1046943 at 119 cM) and 9q21 (non-parametric pairs logarithm of odds (LOD) 3.4 for rs722642 at 78 cM) using only BPI and schizoaffective (SA), BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis, we observed 59 parametric LODs of 2 or greater, many of which are likely to be close to maximum possible scores. Although some linkage findings may be false positives, the results could help prioritize the search for rare variants using whole exome or genome sequencing

New Constraints (and Motivations) for Abelian Gauge Bosons in the MeV-TeV Mass Range

We survey the phenomenological constraints on abelian gauge bosons having masses in the MeV to multi-GeV mass range (using precision electroweak measurements, neutrino-electron and neutrino-nucleon scattering, electron and muon anomalous magnetic moments, upsilon decay, beam dump experiments, atomic parity violation, low-energy neutron scattering and primordial nucleosynthesis). We compute their implications for the three parameters that in general describe the low-energy properties of such bosons: their mass and their two possible types of dimensionless couplings (direct couplings to ordinary fermions and kinetic mixing with Standard Model hypercharge). We argue that gauge bosons with very small couplings to ordinary fermions in this mass range are natural in string compactifications and are likely to be generic in theories for which the gravity scale is systematically smaller than the Planck mass - such as in extra-dimensional models - because of the necessity to suppress proton decay. Furthermore, because its couplings are weak, in the low-energy theory relevant to experiments at and below TeV scales the charge gauged by the new boson can appear to be broken, both by classical effects and by anomalies. In particular, if the new gauge charge appears to be anomalous, anomaly cancellation does not also require the introduction of new light fermions in the low-energy theory. Furthermore, the charge can appear to be conserved in the low-energy theory, despite the corresponding gauge boson having a mass. Our results reduce to those of other authors in the special cases where there is no kinetic mixing or there is no direct coupling to ordinary fermions, such as for recently proposed dark-matter scenarios.Comment: 49 pages + appendix, 21 figures. This is the final version which appears in JHE

Electrically controlled long-distance spin transport through an antiferromagnetic insulator

Spintronics uses spins, the intrinsic angular momentum of electrons, as an alternative for the electron charge. Its long-term goal is in the development of beyond-Moore low dissipation technology devices. Recent progress demonstrated the long-distance transport of spin signals across ferromagnetic insulators. Antiferromagnetically ordered materials are however the most common class of magnetic materials with several crucial advantages over ferromagnetic systems. In contrast to the latter, antiferromagnets exhibit no net magnetic moment, which renders them stable and impervious to external fields. In addition, they can be operated at THz frequencies. While fundamentally their properties bode well for spin transport, previous indirect observations indicate that spin transmission through antiferromagnets is limited to short distances of a few nanometers. Here we demonstrate the long-distance, over tens of micrometers, propagation of spin currents through hematite (\alpha-Fe2O3), the most common antiferromagnetic iron oxide, exploiting the spin Hall effect for spin injection. We control the spin current flow by the interfacial spin-bias and by tuning the antiferromagnetic resonance frequency with an external magnetic field. This simple antiferromagnetic insulator is shown to convey spin information parallel to the compensated moment (N\'eel order) over distances exceeding tens of micrometers. This newly-discovered mechanism transports spin as efficiently as the net magnetic moments in the best-suited complex ferromagnets. Our results pave the way to ultra-fast, low-power antiferromagnet-insulator-based spin-logic devices that operate at room temperature and in the absence of magnetic fields