Search

Producing green hydrogen in a cost-competitive manner via water electrolysis will make the long-held dream of meeting energy needs with hydrogen instead of fossil fuel a reality. Although platinum-based catalysts show good performance towards hydrogen evolution reaction (HER), the high cost and scarce abundance challenge their economic viability for large-scale implementation. Here, we engineer high fractions of stacking fault defects in MoNi nanosheets to form a high-performance electrocatalyst (d-MoNi) through a combined chemical and thermal reduction strategy. Using d-MoNi as an electrode for HER afforded ultralow overpotential of 63 and 120 mV at current densities of -500 and -1000 mA cm-2 in 1 M KOH, respectively. Besides, the stacking fault defect-rich d-MoNi exhibits 4 orders of magnitude higher turnover frequency than benchmark 20% Pt/C, together with excellent durability (>100 h) at high current density of 1000 mA cm-2, making it one of the best-performing non-platinum catalysts for HER. The experimental and theoretical results reveal that the abundant stacking faults in d-MoNi induce a compressive strain, decreasing the proton adsorption energy and promoting the concomitant combination of adsorbed hydrogen into molecular hydrogen and the desorption of the molecular hydrogen, therefore enhancing the HER performance. This work provides a new synthetic route to engineer defective metal and metal alloy electrocatalysts for emerging applications in electrochemical energy conversion and storage.

We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly implemented in highly complex or carefully engineered systems, such as animal brains, artificial neural networks, DNA computing systems, and gene regulatory networks, among others. The ability to encode environmental information and use it to make simple predictions is a benchmark of biological resilience and underpins a plethora of adaptive responses in the living hierarchy, spanning prey animal species anticipating the arrival of predators to epigenetic systems in microorganisms learning environmental correlations. Given the ubiquitous and essential presence of learning behaviors in the biosphere, we aimed to explore whether simple, nonliving dissipative structures could also exhibit associative learning. Inspired by previous modeling of associative learning in chemical networks, we simulated simple systems composed of long- and short-term memory chemical species that could encode the presence or absence of temporal correlations between two external species. The ability to learn this association was implemented in Gray-Scott reaction-diffusion spots, emergent chemical patterns that exhibit self-replication and homeostasis. With the novel ability of associative learning, we demonstrate that simple chemical patterns can exhibit a broad repertoire of lifelike behavior, paving the way for in vitro studies of autonomous chemical learning systems, with potential relevance to artificial life, origins of life, and systems chemistry. The experimental realization of these learning behaviors in protocell or coacervate systems could advance a new research direction in astrobiology, since our system significantly reduces the lower bound on the required complexity for autonomous chemical learning.

Previous studies show that city metrics having to do with growth, productivity and overall energy consumption scale superlinearly , attributing this to the social nature of cities. Superlinear scaling results in crises called ‘singularities’, where population and energy demand tend to infinity in a finite amount of time, which must be avoided by ever more frequent ‘resets’ or innovations that postpone the system's collapse. Here, we place the emergence of cities and planetary civilizations in the context of major evolutionary transitions. With this perspective, we hypothesize that once a planetary civilization transitions into a state that can be described as one virtually connected global city, it will face an ‘asymptotic burnout’, an ultimate crisis where the singularity-interval time scale becomes smaller than the time scale of innovation. If a civilization develops the capability to understand its own trajectory, it will have a window of time to affect a fundamental change to prioritize long-term homeostasis and well-being over unyielding growth—a consciously induced trajectory change or ‘homeostatic awakening’. We propose a new resolution to the Fermi paradox: civilizations either collapse from burnout or redirect themselves to prioritizing homeostasis, a state where cosmic expansion is no longer a goal, making them difficult to detect remotely.

We present a new approach to exoplanet characterization using techniques from complexity science, with potential applications to biosignature detection. This agnostic method makes use of the temporal variability of light reflected or emitted from a planet. We use a technique known as epsilon machine reconstruction to compute the statistical complexity, a measure of the minimal model size for time series data. We demonstrate that statistical complexity is an effective measure of the complexity of planetary features. Increasing levels of qualitative planetary complexity correlate with increases in statistical complexity and Shannon entropy, demonstrating that our approach can identify planets with the richest dynamics. We also compare Earth time series with Jupiter data, and find that for the three wavelengths considered Earth’s average complexity and entropy rate are approximately 50% and 43% higher than Jupiter’s, respectively. The majority of schemes for the detection of extraterrestrial life rely upon biochemical signatures and planetary context. However, it is increasingly recognized that extraterrestrial life could be very different from life on Earth. Under the hypothesis that there is a correlation between the presence of a biosphere and observable planetary complexity, our technique offers an agnostic and quantitative method for the measurement thereof.

Point source spectrophotometric ("single-point") light curves of Earth-like planets contain a surprising amount of information about the spatial features of those worlds. Spatially resolving these light curves is important for assessing time-varying surface features and the existence of an atmosphere, which in turn is critical to life on Earth and significant for determining habitability on exoplanets. Given that Earth is the only celestial body confirmed to harbor life, treating it as a proxy exoplanet by analyzing time-resolved spectral images provides a benchmark in the search for habitable exoplanets. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) provides such an opportunity, with observations of ~5000 full-disk sunlit Earth images each year at ten wavelengths with high temporal frequency. We disk-integrate these spectral images to create single-point light curves and decompose them into principal components (PCs). Using machine learning techniques to relate the PCs to six preselected spatial features, we find that the first and fourth PCs of the single-point light curves, contributing ~83.23% of the light curve variability, contain information about low and high clouds, respectively. Surface information relevant to the contrast between land and ocean reflectance is contained in the second PC, while individual land sub-types are not easily distinguishable (, Accepted by AJ, 10 pages, 2 tables, 13 figures

The structural form and elemental distribution of material originating from different Fukushima Daiichi Nuclear Power Plant reactors (Units 1 and 3) is hereby examined to elucidate their contrasting release dynamics and the current in-reactor conditions to influence future decommissioning challenges. Complimentary computed X-ray absorption tomography and X-ray fluorescence data show that the two suites of Si-based material sourced from the different reactor Units have contrasting internal structure and compositional distribution. The known event and condition chronology correlate with the observed internal and external structures of the particulates examined, which suggest that Unit 1 ejecta material sustained a greater degree of melting than that likely derived from reactor Unit 3. In particular, we attribute the near-spherical shape of Unit 1 ejecta and their internal voids to there being sufficient time for surface tension to round these objects before the hot (and so relatively low viscosity) silicate melt cooled to form glass. In contrast, a more complex internal form associated with the sub-mm particulates invoked to originate from Unit 3 suggest a lower peak temperature, over a longer duration. Using volcanic analogues, we consider the structural form of this material and how it relates to its environmental particulate stability and the bulk removal of residual materials from the damaged reactors. We conclude that the brittle and angular Unit 3 particulate are more susceptible to further fragmentation and particulate generation hazard than the round, higher-strength, more homogenous Unit 1 material.

As part of its ambitious long term energy strategy, Switzerland plans to phase out nuclear power production and replace most or all of its significant share of national electricity production (40%) by renewables, in particular by photovoltaics (PV) and wind energy. The existing large fraction of hydropower and significant pumped-storage hydro capacity in the mountainous regions of the country will potentially provide valuable balancing and ancillary services for the management of intermittent production from PV and wind. We present a set of calculations based on data from the current Swiss electricity system, which investigate the effect of different PV-wind mixing ratio scenarios on required import and export from foreign neighbors. It is shown that the current hydropower is a good basis to deal with intermittent energy sources and to keep import rates of electricity at current levels in a fully renewable Switzerland as long as the PV-wind ratio is small. For higher PV-shares, forced export and import will increase but appear acceptable if PV-contribution stays below 0.6. Enlargement of reservoir capacity or oversizing of intermittent renewables can further reduce required import effectively. These findings are quantitatively specific for Switzerland but qualitatively transferable to similar mountainous environments with abundant hydropower resources.

Resolving spatially-varying exoplanet features from single-point light curves is essential for determining whether Earth-like worlds harbor geological features and/or climate systems that influence habitability. To evaluate the feasibility and requirements of this spatial feature resolving problem, we present an analysis of multi-wavelength single-point light curves of Earth, where it plays the role of a proxy exoplanet. Here, ~10,000 DSCOVR/EPIC frames collected over a two-year period were integrated over the Earth's disk to yield a spectrally-dependent point source and analyzed using singular value decomposition. We found that, between the two dominant principal components (PCs), the second PC contains surface-related features of the planet, while the first PC mainly includes cloud information. We present the first two-dimensional (2D) surface map of Earth reconstructed from light curve observations without any assumptions of its spectral properties. This study serves as a baseline for reconstructing the surface features of Earth-like exoplanets in the future., Accepted by ApJL, 7 pages, 4 figures

We present a potential new mode of natural computing in which simple, heat-driven fluid flows perform Boolean logic operations. The system comprises a two-dimensional single-phase fluid that is heated from below and cooled from above, with two obstacles placed on the horizontal mid-plane. The obstacles remove all vertical momentum that flows into them. The horizontal momentum extraction of the obstacles is controlled in a binary fashion, and constitutes the 2-bit input. The output of the system is a thresholded measure of the energy extracted by the obstacles. Due to the existence of multiple attractors in the phase space of this system, the input–output relationships are equivalent to those of the OR, XOR or NAND gates, depending on the threshold and obstacle separation. The ability to reproduce these logical operations suggests that convective flows might have the potential to perform more general computations, despite the fact that they do not involve electronics, chemistry or multiple fluid phases.

In this review, we describe some of the central philosophical issues facing origins-of-life research and provide a targeted history of the developments that have led to the multidisciplinary field of origins-of-life studies. We outline these issues and developments to guide researchers and students from all fields. With respect to philosophy, we provide brief summaries of debates with respect to (1) definitions (or theories) of life, what life is and how research should be conducted in the absence of an accepted theory of life, (2) the distinctions between synthetic, historical, and universal projects in origins-of-life studies, issues with strategies for inferring the origins of life, such as (3) the nature of the first living entities (the “bottom up” approach) and (4) how to infer the nature of the last universal common ancestor (the “top down” approach), and (5) the status of origins of life as a science. Each of these debates influences the others. Although there are clusters of researchers that agree on some answers to these issues, each of these debates is still open. With respect to history, we outline several independent paths that have led to some of the approaches now prevalent in origins-of-life studies. These include one path from early views of life through the scientific revolutions brought about by Linnaeus (von Linn.), Wöhler, Miller, and others. In this approach, new theories, tools, and evidence guide new thoughts about the nature of life and its origin. We also describe another family of paths motivated by a” circularity” approach to life, which is guided by such thinkers as Maturana & Varela, Gánti, Rosen, and others. These views echo ideas developed by Kant and Aristotle, though they do so using modern science in ways that produce exciting avenues of investigation. By exploring the history of these ideas, we can see how many of the issues that currently interest us have been guided by the contexts in which the ideas were developed. The disciplinary backgrounds of each of these scholars has influenced the questions they sought to answer, the experiments they envisioned, and the kinds of data they collected. We conclude by encouraging scientists and scholars in the humanities and social sciences to explore ways in which they can interact to provide a deeper understanding of the conceptual assumptions, structure, and history of origins-of-life research. This may be useful to help frame future research agendas and bring awareness to the multifaceted issues facing this challenging scientific question., This project/publication was supported by the ELSI Origins Network (EON), which is supported by a grant from the John Templeton Foundation. T.F.’s work on this article was supported by an ELSI Origins Network (EON) Long-Term Visitor Award and by an UNAM-DGAPA-PAPIIT project (IA104717).

We present recent results concerning the attractor landscape, memory, hysteresis and computation that can emerge in simple convective obstacle flows. In these systems a single phase fluid is heated from below and cooled from above. Small obstacles (one or two) are placed on the horizontal mid plane of the system and extract some fraction of the fluid’s horizontal or vertical momentum. Horizontal momentum sinks tend to attract convection plumes. Vertical momentum sinks are bistable; the obstacle will either align with a convection cell centre or convection plume depending on initial conditions and the history of the system. The resulting attractor landscape can be exploited to produce a single bit memory or even elementary Boolean logic.

This work explores the stability and hysteresis effects that occur when a small sink of momentum is introduced into a heat-driven, two-dimensional convective flow. As per standard fluid mechanical intuition, the system minimizes work generation and dissipation when one component of momentum is extracted. However, when the sink absorbs all incoming momentum, the system configures itself such that one of the convection plumes aligns directly with the sink. This state is the most hydrodynamically stable, but it maximizes, rather than minimizes extracted mechanical work. Furthermore, in the case of only vertical momentum extraction, there are two attractors, with different stabilities. Numerical experiments involving slow variations of the horizontal momentum extraction show a clear history dependence. This hysteresis preserves information about the system's past states, and hence represents a primitive memory. The momentum sink can also be used to manipulate the horizontal position of the flow field, with potential applications in microfluidics and laminar convection systems. This simple system exhibits the phenomena of autocatalysis (during the initial growth of the convection plumes), negative feedback (the attractors are either fully or quasistable), memory, and elementary computation.

This paper proposes new avenues for origins research that apply modern concepts from stochastic thermodynamics, information thermodynamics and complexity science. Most approaches to the emergence of life prioritize certain compounds, reaction pathways, environments or phenomena. What they all have in common is the objective of reaching a state that is recognizably alive, usually positing the need for an evolutionary process. As with life itself, this correlates with a growth in the complexity of the system over time. Complexity often takes the form of an intuition or a proxy for a phenomenon that defies complete understanding. However, recent progress in several theoretical fields allows the rigorous computation of complexity. We thus propose that measurement and control of the complexity and information content of origins-relevant systems can provide novel insights that are absent in other approaches. Since we have no guarantee that the earliest forms of life (or alien life) used the same materials and processes as extant life, an appeal to complexity and information processing provides a more objective and agnostic approach to the search for life's beginnings. This paper gives an accessible overview of the three relevant branches of modern thermodynamics. These frameworks are not commonly applied in origins studies, but are ideally suited to the analysis of such non-equilibrium systems. We present proposals for the application of these concepts in both theoretical and experimental origins settings.

Three-dimensional (3-D) snow analysis techniques provide comprehensive and accurate snow microstructure data. Nevertheless, there remains a requirement for less elaborate methods for snow characterization, as numerical snow models such as SNOWPACK are presently based on two-dimensional (2-D) grain analysis. We present a detailed assessment of various methods and shape descriptors used for snow characterization from digitized images. Dendricity, the ratio of the square of grain perimeter to its area, allows distinction between new and old snow while sphericity distinguishes between faceted and rounded grains. The concept of sphericity is based on curvature, yet another powerful shape descriptor. However, curvatures obtained from images of disaggregated snow grains depend on both resolution and methods chosen. We compared the standard parabola method with a cubic smoothing spline approach for curvature measurement. Applying both methods to parametrically generated shapes, descriptor values were compared with their analytical counterparts. The spline method was found to be able to measure a wider range of curvatures accurately, but both methods suffered from a filtering effect. Although some descriptor errors were as high as 50%, a method for effectively outlining snow grains was found. As well as assessing the classification potential of 2-D analysis on full samples, new descriptors were also investigated.

Rayleigh-Benard convection is a canonical example of spontaneous pattern formation in a nonequilibrium system. It has been the subject of considerable theoretical and experimental study, primarily for systems with constant (temperature or heat flux) boundary conditions. In this investigation, we have explored the behavior of a convecting fluid system with negative feedback boundary conditions. At the upper and lower system boundaries, the inward heat flux is defined such that it is a decreasing function of the boundary temperature. Thus the system's heat transport is not constrained in the same manner that it is in the constant temperature or constant flux cases. It has been suggested that the entropy production rate (which has a characteristic peak at intermediate heat flux values) might apply as a selection rule for such a system. In this work, we demonstrate with Lattice Boltzmann simulations that entropy production maximization does not dictate the steady state of this system, despite its success in other, somewhat similar scenarios. Instead, we will show that the same scaling law of dimensionless variables found for constant boundary conditions also applies to this system.

The effects of heat transfer by ventilation in snow are investigated theoretically. We draw together standard analytical results for fluid flow in porous media and apply them to the case of steady flows induced by periodic roughness elements. These solutions are used to estimate the relative magnitude of ventilation heat transfer in snow. We conclude that topography-driven ventilation is unlikely to have a significant impact on the larger scale energy balance of snow-covered regions since the airflow is confined to a shallow penetration depth or just the roughness elements themselves, rather than the bulk snowpack. In particular, for the limiting case of very warm and moisture saturated air flowing over a melting snow cover, we show that latent and sensible heat due to ventilation have about equal contributions and that this contribution is small compared to the overall surface flux as predicted by the Monin-Obukhov theory.

We present results from a series of experiments in which fresh snow roughness was measured by means of digital photography and analyzed using the random field approach. The aim of the paper is to investigate the scaling properties of fresh-snow-covered surfaces and to capture key roughness length scales which can characterize the surface geometry and the size of the snow crystals. Results from our experiments show the following: (1) fresh snow roughness exhibits two distinguished scaling regimes, one at scales comparable with the crystals size and another one at larger scales; (2) we confirm that the large scales are built up during snowfall and their scaling behavior is consistent with that of Ballistic Deposition (BD) processes; and (3) we suggest that the crossover length scale separating the two scaling regimes effectively defines a representative length scale of the aggregated snow crystals on the surface. The definition of this length scale is independent of the difficulties associated with measuring snow grain sizes by means of standard microscopic analysis of disaggregated crystals. Furthermore it can be obtained from a low-cost and quick experimental procedure. Results from this study provide a plausible justification for the wide scatter of aerodynamic roughness length values encountered in the literature for fresh snow. Moreover, they provide insight on the key roughness length scales which should be used for the modeling of this parameter.

[1] The deposition and attachment mechanism of settling snow crystals during snowfall dictates the very initial structure of ice within a natural snowpack. In this letter we apply ballistic deposition as a simple model to study the structural evolution of the growing surface of a snowpack during its formation. The roughness of the snow surface is predicted from the behaviour of the time dependent height correlation function. The predictions are verified by simple measurements of the growing snow surface based on digital photography during snowfall. The measurements are in agreement with the theoretical predictions within the limitations of the model which are discussed. The application of ballistic deposition type growth models illuminates structural aspects of snow from the perspective of formation which has been ignored so far. Implications of this type of growth on the aerodynamic roughness length, density, and the density correlation function of new snow are discussed.

The prospect of a renewable transition seems plausible for many countries, but can be shrouded in risks, costs and challenges. This paper illuminates a path for such a transition with a numerical investigation, aimed at resolving the power dynamics of a country powered only by renewable generators. The focus was Switzerland, with its considerable hydropower infrastructure and plans to phase out nuclear energy. The model uses optimal power flow calculations to compute the transmission of electricity, and also accounts for the movement of water within the hydropower system. Results suggest that the renewable goal is attainable and will not require radical re-building of the country's transmission infrastructure. Under our assumptions, it was found that the transmission grid is placed under slightly lower stress on average, in renewable scenarios. Despite matching supply and demand on average, the fully renewable system required a $ 107% increase in electrical exchange with neighbouring countries to compensate for seasonal variability, and additional intermittency of electrical supply. Simulation results are described for three scenarios: Current, Intermediate, and Renewable. The bulk power statistics, temporal dynamics, distributions of line use, and spatial patterns are presented, and the implications of the results are discussed.