The Incidence of Geography on Canada's Services Trade

We estimate geographic barriers to export trade in nine service categories for Canada's provinces from 1997 to 2007 using the structural gravity model. Constructed Home, Domestic and Foreign Bias indexes (the last two new) capture the direct plus indirect effect of services trade costs on intra-provincial, inter-provincial and international trade relative to their frictionless benchmarks. Barriers to services international trade are huge relative to inter-provincial trade and large relative to goods international trade. A novel test confirms the fit of structural gravity with services trade data.

How Much Does Geography Deflect Services Trade?

Abstract We estimate geographic barriers to trade in nine service categories for Canada's provinces from 1997 to 2007 with novel high quality bilateral provincial trade data. The border directly reduces average provincial trade with the US relative to interprovincial trade to 2.4% of its borderless level. Incorporating multilateral resistance reduces foreign trade relative to interprovincial to 0.1% of its frictionless potential. Geography reduces services trade some 7 times more than goods trade overall. Surprisingly, intra-provincial (local) trade in services and goods is equally deflected upward, implying that the border increases interprovincial trade much more in services than goods. JEL Classification Codes: F13, F14, F1

Charge-Carrier Dynamics in 2D Hybrid Metal–Halide Perovskites

Hybrid metal–halide perovskites are promising new materials for use in solar cells; however, their chemical stability in the presence of moisture remains a significant drawback. Quasi two-dimensional (2D) perovskites that incorporate hydrophobic organic interlayers offer improved resistance to degradation by moisture, currently still at the cost of overall cell efficiency. To elucidate the factors affecting the optoelectronic properties of these materials, we have investigated the charge transport properties and crystallographic orientation of mixed methylammonium (MA)–phenylethylammonium (PEA) lead iodide thin films as a function of the MA-to-PEA ratio and, thus, the thickness of the “encapsulated” MA lead–halide layers. We find that monomolecular charge-carrier recombination rates first decrease with increasing PEA fraction, most likely as a result of trap passivation, but then increase significantly as excitonic effects begin to dominate for thin confined layers. Bimolecular and Auger recombination rate constants are found to be sensitive to changes in electronic confinement, which alters the density of states for electronic transitions. We demonstrate that effective charge-carrier mobilities remain remarkably high (near 10 cm2V−1s−1) for intermediate PEA content and are enhanced for preferential orientation of the conducting lead iodide layers along the probing electric field. The trade-off between trap reduction, electronic confinement, and layer orientation leads to calculated charge-carrier diffusion lengths reaching a maximum of 2.5 μm for intermediate PEA content (50%)

Illuminating the Devolution of Perovskite Passivation Layers

\ua9 2024 The Author(s). Small Structures published by Wiley-VCH GmbH.Surface treatment of perovskite materials with their layered counterparts has become an ubiquitous strategy for maximizing device performance. While layered materials confer great benefits to the longevity and long-term efficiency of the resulting device stack via passivation of defects and surface traps, numerous reports have previously demonstrated that these materials evolve under exposure to light and humidity, suggesting that they are not fully stable. Therefore, it is crucial to study the behavior of these materials in isolation and in conditions mimicking a device stack. Here, it is shown that perovskite capping layers templated by a range of cations on top of methylammonium lead iodide devolve in conditions commonly found during perovskite fabrication, such as exposure to light, solvent, and moisture. Photophysical, structural, and morphological studies are used to show that the degradation of these layered perovskites occurs via a self-limiting, pinhole-mediated mechanism. This results in the loss of whole perovskite sheets, from a few monolayers to tens of nanometers of material, until the system stabilizes again as demonstrated for exfoliated flakes of PEA2PbI4. This means that initially targeted structures may have devolved, with clear optimization implications for device fabrication

Perovskite-perovskite tandem photovoltaics with optimized bandgaps

We demonstrate four and two-terminal perovskite-perovskite tandem solar cells with ideally matched bandgaps. We develop an infrared absorbing 1.2eV bandgap perovskite, $FA_{0.75}Cs_{0.25}Sn_{0.5}Pb_{0.5}I_3$, that can deliver 14.8 % efficiency. By combining this material with a wider bandgap $FA_{0.83}Cs_{0.17}Pb(I_{0.5}Br_{0.5})_3$ material, we reach monolithic two terminal tandem efficiencies of 17.0 % with over 1.65 volts open-circuit voltage. We also make mechanically stacked four terminal tandem cells and obtain 20.3 % efficiency. Crucially, we find that our infrared absorbing perovskite cells exhibit excellent thermal and atmospheric stability, unprecedented for Sn based perovskites. This device architecture and materials set will enable 'all perovskite' thin film solar cells to reach the highest efficiencies in the long term at the lowest costs

Combining isotope ratios for provenancing Viking Age iron artefacts in the British Isles: a pilot study

Stable and radiogenic isotope analysis – particularly using lead isotope analysis (LIA) - has previously been shown to be a useful tool for the provenancing of ancient metal artefacts of silver and copper and its alloys, but less progress has been made in the provenancing of iron artefacts, despite their importance and frequency in the archaeological record. In this pilot study we investigate for the first time the possibilities of iron isotope analysis in combination with trace strontium isotope analysis and LIA for the provenancing of iron objects believed to be from the Viking Age in the British Isles. Previous studies have shown that analysis of each of these isotopes can contribute to provenancing iron artefacts, but they are not individually resolutory. In this proof-of-concept study, we examine the Fe, Sr and Pb isotopes of 7 artefacts believed to derive from the Viking Age: 3 from Meols - a former Viking seaport on Wirral and 4 samples from the probable location of the AD 1066 Battle of Fulford in North Yorkshire. We also examine an additional artefact of unknown antiquity from Bebington Heath – a possible location of the AD 937 Battle of Brunanburh. Although the pilot data set is too small to make definitive conclusions, it has paved the way for a fuller study involving 100 samples (including 30 from the former Viking camp of Torksey, Lincolnshire) funded by the NEIF fund of the UK National Environmental Research Council. The high range of 87Sr/86Sr values in the present data set of 8 is beyond what would be expected for bog iron (with a cut-off ~ 0.709) and suggests that mined ore was being used, a preliminary conclusion supported by the narrow range of Fe isotope data

Nanotechnology for catalysis and solar energy conversion

This roadmap on Nanotechnology for Catalysis and Solar Energy Conversion focuses on the application of nanotechnology in addressing the current challenges of energy conversion: 'high efficiency, stability, safety, and the potential for low-cost/scalable manufacturing' to quote from the contributed article by Nathan Lewis. This roadmap focuses on solar-to-fuel conversion, solar water splitting, solar photovoltaics and bio-catalysis. It includes dye-sensitized solar cells (DSSCs), perovskite solar cells, and organic photovoltaics. Smart engineering of colloidal quantum materials and nanostructured electrodes will improve solar-to-fuel conversion efficiency, as described in the articles by Waiskopf and Banin and Meyer. Semiconductor nanoparticles will also improve solar energy conversion efficiency, as discussed by Boschloo et al in their article on DSSCs. Perovskite solar cells have advanced rapidly in recent years, including new ideas on 2D and 3D hybrid halide perovskites, as described by Spanopoulos et al 'Next generation' solar cells using multiple exciton generation (MEG) from hot carriers, described in the article by Nozik and Beard, could lead to remarkable improvement in photovoltaic efficiency by using quantization effects in semiconductor nanostructures (quantum dots, wires or wells). These challenges will not be met without simultaneous improvement in nanoscale characterization methods. Terahertz spectroscopy, discussed in the article by Milot et al is one example of a method that is overcoming the difficulties associated with nanoscale materials characterization by avoiding electrical contacts to nanoparticles, allowing characterization during device operation, and enabling characterization of a single nanoparticle. Besides experimental advances, computational science is also meeting the challenges of nanomaterials synthesis. The article by Kohlstedt and Schatz discusses the computational frameworks being used to predict structure–property relationships in materials and devices, including machine learning methods, with an emphasis on organic photovoltaics. The contribution by Megarity and Armstrong presents the 'electrochemical leaf' for improvements in electrochemistry and beyond. In addition, biohybrid approaches can take advantage of efficient and specific enzyme catalysts. These articles present the nanoscience and technology at the forefront of renewable energy development that will have significant benefits to society

Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition

Physiological dysregulation may underlie aging and many chronic diseases, but is chal-lenging to quantify because of the complexity of the underlying systems. Recently, we de-scribed a measure of physiological dysregulation, DM, that uses statistical distance to assess the degree to which an individual’s biomarker profile is normal versus aberrant. However, the sensitivity of DM to details of the calculation method has not yet been sys-tematically assessed. In particular, the number and choice of biomarkers and the defini-tion of the reference population (RP, the population used to define a “normal” profile) may be important. Here, we address this question by validating the method on 44 common clinical biomarkers from three longitudinal cohort studies and one cross-sectional survey. DMs calculated on different biomarker subsets show that while the signal of physiological dysregulation increases with the number of biomarkers included, the value of additional markers diminishes as more are added and inclusion of 10-15 is generally sufficient. As long as enough markers are included, individual markers have little effect on the final met-ric, and even DMs calculated from mutually exclusive groups of markers correlate with each other at r~0.4-0.5. We also used data subsets to generate thousands of combina-tions of study populations and RPs to address sensitivity to differences in age range, sex, race, data set, sample size, and their interactions. Results were largely consistent (but not identical) regardless of the choice of RP; however, the signal was generally clearer with a younger and healthier RP, and RPs too different from the study population per-formed poorly. Accordingly, biomarker and RP choice are not particularly important in most cases, but caution should be used across very different populations or for fine-scale analyses. Biologically, the lack of sensitivity to marker choice and better performance of younger, healthier RPs confirm an interpretation of DM physiological dysregulation and as an emergent property of a complex system

Increased Mortality Exposure within the Family Rather than Individual Mortality Experiences Triggers Faster Life-History Strategies in Historic Human Populations

Life History Theory predicts that extrinsic mortality risk is one of the most important factors shaping (human) life histories. Evidence from contemporary populations suggests that individuals confronted with high mortality environments show characteristic traits of fast life-history strategies: they marry and reproduce earlier, have shorter birth intervals and invest less in their offspring. However, little is known of the impact of mortality experiences on the speed of life histories in historical human populations with generally higher mortality risk, and on male life histories in particular. Furthermore, it remains unknown whether individual-level mortality experiences within the family have a greater effect on life-history decisions or family membership explains life-history variation. In a comparative approach using event history analyses, we study the impact of family versus individual-level effects of mortality exposure on two central life-history parameters, ages at first marriage and first birth, in three historical human populations (Germany, Finland, Canada). Mortality experience is measured as the confrontation with sibling deaths within the natal family up to an individual's age of 15. Results show that the speed of life histories is not adjusted according to individual-level mortality experiences but is due to family-level effects. The general finding of lower ages at marriage/reproduction after exposure to higher mortality in the family holds for both females and males. This study provides evidence for the importance of the family environment for reproductive timing while individual-level mortality experiences seem to play only a minor role in reproductive life history decisions in humans