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The large-scale implementation of renewable energy systems necessitates the development of energy storage solutions to effectively manage imbalances between energy supply and demand. Herein, we investigate such a scalable material solution for energy storage in supercapacitors constructed from readily available material precursors that can be locally sourced from virtually anywhere on the planet, namely cement, water, and carbon black. We characterize our carbon-cement electrodes by combining correlative EDS-Raman spectroscopy with capacitance measurements derived from cyclic voltammetry and galvanostatic charge-discharge experiments using integer and fractional derivatives to correct for rate and current intensity effects. Texture analysis reveals that the hydration reactions of cement in the presence of carbon generate a fractal-like electron-conducting carbon network that permeates the load-bearing cement-based matrix. The energy storage capacity of this space-filling carbon black network of the high specific surface area accessible to charge storage is shown to be an intensive quantity, whereas the high-rate capability of the carbon-cement electrodes exhibits self-similarity due to the hydration porosity available for charge transport. This intensive and self-similar nature of energy storage and rate capability represents an opportunity for mass scaling from electrode to structural scales. The availability, versatility, and scalability of these carbon-cement supercapacitors opens a horizon for the design of multifunctional structures that leverage high energy storage capacity, high-rate charge/discharge capabilities, and structural strength for sustainable residential and industrial applications ranging from energy autarkic shelters and self-charging roads for electric vehicles, to intermittent energy storage for wind turbines and tidal power stations.
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We investigate the spatial and temporal memory effects of traffic density and velocity in the Nagel-Schreckenberg cellular automaton model. We show that the two-point correlation function of vehicle occupancy provides access to spatial memory effects, such as headway, and the velocity autocovariance function to temporal memory effects such as traffic relaxation time and traffic compressibility. We develop stochasticity-density plots that permit determination of traffic density and stochasticity from the isotherms of first- and second-order velocity statistics of a randomly selected vehicle. Specifically, provided ergodicity and stationarity, these stochasticity-density plots permit a direct determination of traffic properties from crowdsourced measurements of velocities of vehicles. We illustrate the predictive prowess of the approach for crowdsourced vehicle speed data collected by anonymous smartphone measurements for the state of Massachusetts, USA, as a powerful alternative to classical traffic property estimates from spatially distributed user counts.
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Concrete is a critical component of deep decarbonization efforts because of both the scale of the industry and because of how its use impacts the building, transportation, and industrial sectors. We use a bottom-up model of current and future building and pavement stocks and construction in the United States to contextualize the role of concrete in greenhouse gas (GHG) reductions strategies under projected and ambitious scenarios, including embodied and use phases of the structures' life cycle. We show that projected improvements in the building sector result in a reduction of 49% of GHG emissions in 2050 relative to 2016 levels, whereas ambitious improvements result in a 57% reduction in 2050, which is 22.5 Gt cumulative saving. The pavements sector shows a larger difference between the two scenarios with a 14% reduction of GHG emissions for projected improvements and a 65% reduction under the ambitious scenario, which is â¼1.35 Gt. This reduction occurs despite the fact that concrete usage in 2050 in the ambitious scenario is over three times that of the projected scenario because of the ways in which concrete lowers use phase emissions. Over 70% of future emissions from new construction are from the use phase.
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Cement is the most produced material in the world. A major player in greenhouse gas emissions, it is the main binding agent in concrete, providing a cohesive strength that rapidly increases during setting. Understanding how such cohesion emerges is a major obstacle to advances in cement science and technology. Here, we combine computational statistical mechanics and theory to demonstrate how cement cohesion arises from the organization of interlocked ions and water, progressively confined in nanoslits between charged surfaces of calcium-silicate-hydrates. Because of the water/ions interlocking, dielectric screening is drastically reduced and ionic correlations are proven notably stronger than previously thought, dictating the evolution of nanoscale interactions during cement hydration. By developing a quantitative analytical prediction of cement cohesion based on Coulombic forces, we reconcile a fundamental understanding of cement hydration with the fully atomistic description of the solid cement paste and open new paths for scientific design of construction materials.
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Concrete is one of the most used materials in the world, second only to water. One of the key advantages of this versatile material is its workability in the early stages before setting. Here, we use in situ underwater Raman microspectroscopy to investigate and visualize the early hydration kinetics of ordinary Portland cement (OPC) with submicron spatial and high temporal resolution. First, the spectral features of the C-S-H gel were analyzed in the hydroxyl stretching region to confirm the coexistence of Ca-OH and Si-OH bonds in a highly disordered C-S-H gel. Second, the disordered calcium hydroxide (Ca(OH)2) is experimentally identified for the first time in the mixture before setting, suggesting that Ca(OH)2 crystallization and growth are essential in the setting of cement paste. Finally, the phase transformations of clinker, C-S-H, and Ca(OH)2 are spatially and temporally resolved, and the hydration kinetics are studied by analyzing the spatial relationships of these phases using two-point correlation functions. The results quantitatively validate that the setting occurs as a percolation process, wherein the hydration products intersect and form an interconnected network. This time-space-resolved characterization method can map and quantitatively analyze the heterogeneous reaction of the cementitious colloidal system and thus provide potential application value in the field of cement chemistry and materials design more broadly.
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Using a 3D mean-field lattice-gas model, we analyze the effect of confinement on the nature of capillary phase transition in granular aggregates with varying disorder and their inverse porous structures obtained by interchanging particles and pores. Surprisingly, the confinement effects are found to be much less pronounced in granular aggregates as opposed to porous structures. We show that this discrepancy can be understood in terms of the surface-surface correlation length with a connected path through the fluid domain, suggesting that this length captures the true degree of confinement. We also find that the liquid-gas phase transition in these porous materials is of second order nature near capillary critical temperature, which is shown to represent a true critical temperature, i.e., independent of the degree of disorder and the nature of the solid matrix, discrete or continuous. The critical exponents estimated here from finite-size scaling analysis suggest that this transition belongs to the 3D random field Ising model universality class as hypothesized by F. Brochard and P.G. de Gennes, with the underlying random fields induced by local disorder in fluid-solid interactions.
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It has been recognized that the microporosity of shale organic matter, especially that of kerogen, strongly affects the hydrocarbon recovery process from unconventional reservoirs. So far, the numerical studies on hydrocarbon transport through the microporous phase of kerogen have neglected the effect of poromechanics, that is, the adsorption-induced deformations, by considering kerogen as a frozen, nondeformable, matrix. Here, we use molecular dynamics simulations to investigate methane diffusion in an immature (i.e., with high H/C ratio) kerogen matrix, while explicitly accounting for adsorption-induced swelling and internal matricial motions, covering both phonons and nonperiodic internal deformations. However, in the usual frozen matrix approximation, diffusivity decreases with increasing fluid loading, as evidenced by a loss of free volume, accounting for adsorption-induced swelling that gives rise to an increase in free volume and, hence, in diffusivity. The obtained trend is further rationalized using a Fujita-Kishimoto free volume theory initially developed in the context of diffusion in swelling polymers. We also quantify the enhancing effect of the matrix internal motions (i.e., at fixed volume) and show that it roughly gives an order of magnitude increase in diffusivity with respect to a frozen matrix, thanks to fluctuations in the pore connectivity. We eventually discuss the possible implications of this work to explain the productivity slowdown of hydrocarbon recovery from shale immature reservoirs.
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Capillary effects, such as imbibition drying cycles, impact the mechanics of granular systems over time. A multiscale poromechanics framework was applied to cement paste, which is the most common building material, experiencing broad humidity variations over the lifetime of infrastructure. First, the liquid density distribution at intermediate to high relative humidity is obtained using a lattice gas density functional method together with a realistic nanogranular model of cement hydrates. The calculated adsorption/desorption isotherms and pore size distributions are discussed and compare well with nitrogen and water experiments. The standard method for pore size distribution determination from desorption data is evaluated. Second, the integration of the Korteweg liquid stress field around each cement hydrate particle provided the capillary forces at the nanoscale. The cement mesoscale structure was relaxed under the action of the capillary forces. Local irreversible deformations of the cement nanograins assembly were identified due to liquid-solid interactions. The spatial correlations of the nonaffine displacements extend to a few tens of nanometers. Third, the Love-Weber method provided the homogenized liquid stress at the micrometer scale. The homogenization length coincided with the spatial correlation length of nonaffine displacements. Our results on the solid response to capillary stress field suggest that the micrometer-scale texture is not affected by mild drying, while nanoscale irreversible deformations still occur. These results pave the way for understanding capillary phenomena-induced stresses in heterogeneous porous media ranging from construction materials to hydrogels and living systems.
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Organic matter is responsible for the generation of hydrocarbons during the thermal maturation of source rock formation. This geochemical process engenders a network of organic hosted pores that governs the flow of hydrocarbons from the organic matter to fractures created during the stimulation of production wells. Therefore, it can be reasonably assumed that predictions of potentially recoverable confined hydrocarbons depend on the geometry of this pore network. Here, we analyze mesoscale structures of three organic porous networks at different thermal maturities. We use electron tomography with subnanometric resolution to characterize their morphology and topology. Our 3D reconstructions confirm the formation of nanopores and reveal increasingly tortuous and connected pore networks in the process of thermal maturation. We then turn the binarized reconstructions into lattice models including information from atomistic simulations to derive mechanical and confined fluid transport properties. Specifically, we highlight the influence of adsorbed fluids on the elastic response. The resulting elastic energy concentrations are localized at the vicinity of macropores at low maturity whereas these concentrations present more homogeneous distributions at higher thermal maturities, due to pores' topology. The lattice models finally allow us to capture the effect of sorption on diffusion mechanisms with a sole input of network geometry. Eventually, we corroborate the dominant impact of diffusion occurring within the connected nanopores, which constitute the limiting factor of confined hydrocarbon transport in source rocks.
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An atomistic and mesoscopic assessment of the effect of alkali uptake in cement paste is performed. Semi-grand canonical Monte Carlo simulations indicate that Na and K not only adsorb at the pore surface of calcium silicate hydrates (C-S-H) but also adsorb in the C-S-H hydrated interlayer up to concentrations of the order of 0.05 and 0.1 mol/kg, respectively. Sorption of alkali is favored as the Ca/Si ratio of C-S-H is reduced. Long timescale simulations using the Activation Relaxation Technique indicate that characteristic diffusion times of Na and K in the C-S-H interlayer are of the order of a few hours. At the level of individual grains, Na and K adsorption leads to a reduction of roughly 5% of the elastic moduli and to volume expansion of about 0.25%. Simulations using the so-called primitive model indicate that adsorption of alkali ions at the pore surface can reduce the binding between C-S-H grains by up to 6%. Using a mesoscopic model of cement paste, the combination of individual grain swelling and changes in inter-granular cohesion was estimated to lead to overall expansive pressures of up to 4 MPa-and typically of less than 1 MPa-for typical alkali concentrations observed at the proximity of gel veins caused by the alkali-silica reaction.
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PURPOSE: To make the Boston keratoprosthesis (B-KPro), together with its carrier corneal graft, more easily procured, transported and stored, as well as less expensive, easier for the surgeon to implant and safer for the patient, it is proposed that the B-KPro-graft combination be pre-assembled by an expert technician, followed by sterilization with gamma ray irradiation (GI) allowing long-term storage at room temperature. For this to be possible, it must be shown that the B-KPro itself (not only the graft) remains unharmed by the irradiation. METHODS: Polymethyl methacrylate (PMMA) discs and B-KPros were submitted to either ethylene oxide sterilization or different doses of GI. Cell biocompatibility, mechanical strength and optical quality were evaluated. The feasibility of assembling the B-KPro to a corneal graft, and gamma-radiate afterwards, was also assessed. RESULTS: There were no differences in cell biocompatibility between the samples. The optical evaluation showed high levels of transparency for all the groups. The absorbance of ultraviolet was higher for the groups treated with GI. The mechanical evaluation by nanoindentation showed no alterations of the PMMA discs after GI. The flexure test revealed a similar mechanical behavior. Technically, pre-assembly and GI of the B-KPro revealed no problems. CONCLUSIONS: Sterilization of B-KPro using GI has no detrimental influence on the device. The pre-assembly of B-KPro to a donor cornea, followed by gamma sterilization, emerges as an efficient and safe procedure.
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Órganos Artificiales , Enfermedades de la Córnea/cirugía , Rayos gamma , Prótesis e Implantes , Esterilización/métodos , Materiales Biocompatibles , Humanos , Ensayo de Materiales , Preservación de Órganos/métodos , Polimetil MetacrilatoRESUMEN
In a context of growing attention for shale gas, the precise impact of organic matter (kerogen) on hydrocarbon recovery from unconventional reservoirs still has to be assessed. Kerogen's microstructure is characterized by a very disordered pore network that greatly affects hydrocarbon transport. The specific structure and texture of this organic matter at the nanoscale is highly dependent on its origin. In this study, by the use of statistical physics and molecular dynamics, we shed some new lights on hydrocarbon transport through realistic molecular models of kerogen at different level of maturity [ Bousige et al. Nat. Mater. 2016 , 15 , 576 ]. Despite the apparent complexity, severe confinement effects controlled by the porosity of the various kerogens allow linear alkanes (from methane to dodecane) transport to be studied only via the self-diffusion coefficients of the species. The decrease of the transport coefficients with the amount of adsorbed fluid can be described by a free volume theory. Ultimately, the transport coefficients of hydrocarbons can be expressed simply as a function of the porosity (volume fraction of void) of the microstructure, thus paving the way for shale gas recovery predictions.
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By means of extensive lattice-element simulations, we investigate stress transmission and its relation with failure properties in increasingly disordered porous systems. We observe a non-Gaussian broadening of stress probability density functions under tensile loading with increasing porosity and disorder, revealing a gradual transition from a state governed by single-pore stress concentration to a state controlled by multipore interactions and metric disorder. This effect is captured by the excess kurtosis of stress distributions and shown to be nicely correlated with the second moment of local porosity fluctuations, which appears thus as a (dis)order parameter for the system. By generating statistical ensembles of porous textures with varying porosity and disorder, we derive a general expression for the fracture stress as a decreasing function of porosity and disorder. Focusing on critical sites where the local stress is above the global fracture threshold, we also analyze the transition to failure in terms of a coarse-graining length. These findings provide a general framework which can also be more generally applied to multiphase and structural heterogeneous materials.
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Despite recent focus on shale gas, hydrocarbon recovery from the ultraconfining and disordered porosity of organic matter in shales (kerogen) remains poorly understood. Key aspects such as the breakdown of hydrodynamics at the nanoscale and strong adsorption effects lead to unexplained non-Darcy behaviors. Here, molecular dynamics and statistical mechanics are used to elucidate hydrocarbon mixture transport through a realistic molecular model of kerogen [ Bousige, C.; et al. Nat. Mater. 2016 , 15 , 576 ]. Owing to strong adsorption effects, velocity cross-correlations between the mixture components and between molecules of the same species are shown to be negligible. This allows estimation of each component permeance from its self-diffusivity, which can be obtained from single-component data. These permeances are found to scale with the reciprocal of the alkane length and decrease with the number of adsorbed molecules following a simple free volume theory, therefore allowing mixture transport prediction as a function of the amount of trapped fluid.
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More than 44% of building energy consumption in the USA is used for space heating and cooling, and this accounts for 20% of national CO2emissions. This prompts the need to identify among the 130 million households in the USA those with the greatest energy-saving potential and the associated costs of the path to reach that goal. Whereas current solutions address this problem by analysing each building in detail, we herein reduce the dimensionality of the problem by simplifying the calculations of energy losses in buildings. We present a novel inference method that can be used via a ranking algorithm that allows us to estimate the potential energy saving for heating purposes. To that end, we only need consumption from records of gas bills integrated with a building's footprint. The method entails a statistical screening of the intricate interplay between weather, infrastructural and residents' choice variables to determine building gas consumption and potential savings at a city scale. We derive a general statistical pattern of consumption in an urban settlement, reducing it to a set of the most influential buildings' parameters that operate locally. By way of example, the implications are explored using records of a set of (N= 6200) buildings in Cambridge, MA, USA, which indicate that retrofitting only 16% of buildings entails a 40% reduction in gas consumption of the whole building stock. We find that the inferred heat loss rate of buildings exhibits a power-law data distribution akin to Zipf's law, which provides a means to map an optimum path for gas savings per retrofit at a city scale. These findings have implications for improving the thermal efficiency of cities' building stock, as outlined by current policy efforts seeking to reduce home heating and cooling energy consumption and lower associated greenhouse gas emissions.
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Conservación de los Recursos Energéticos/métodos , Industria de la Construcción/métodos , Calor , Modelos Teóricos , Remodelación Urbana/métodos , MassachusettsRESUMEN
The statistics of velocities in the cellular automaton model of Nagel and Schreckenberg for traffic are studied. From numerical simulations, we obtain the probability distribution function (PDF) for vehicle velocities and the velocity-velocity (vv) covariance function. We identify the probability to find a standing vehicle as a potential order parameter that signals nicely the transition between free congested flow for a sufficiently large number of velocity states. Our results for the vv covariance function resemble features of a second-order phase transition. We develop a 3-body approximation that allows us to relate the PDFs for velocities and headways. Using this relation, an approximation to the velocity PDF is obtained from the headway PDF observed in simulations. We find a remarkable agreement between this approximation and the velocity PDF obtained from simulations.
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Modelos Teóricos , Vehículos a Motor , ProbabilidadRESUMEN
Strength and other mechanical properties of cement and concrete rely upon the formation of calcium-silicate-hydrates (C-S-H) during cement hydration. Controlling structure and properties of the C-S-H phase is a challenge, due to the complexity of this hydration product and of the mechanisms that drive its precipitation from the ionic solution upon dissolution of cement grains in water. Departing from traditional models mostly focused on length scales above the micrometer, recent research addressed the molecular structure of C-S-H. However, small-angle neutron scattering, electron-microscopy imaging, and nanoindentation experiments suggest that its mesoscale organization, extending over hundreds of nanometers, may be more important. Here we unveil the C-S-H mesoscale texture, a crucial step to connect the fundamental scales to the macroscale of engineering properties. We use simulations that combine information of the nanoscale building units of C-S-H and their effective interactions, obtained from atomistic simulations and experiments, into a statistical physics framework for aggregating nanoparticles. We compute small-angle scattering intensities, pore size distributions, specific surface area, local densities, indentation modulus, and hardness of the material, providing quantitative understanding of different experimental investigations. Our results provide insight into how the heterogeneities developed during the early stages of hydration persist in the structure of C-S-H and impact the mechanical performance of the hardened cement paste. Unraveling such links in cement hydrates can be groundbreaking and controlling them can be the key to smarter mix designs of cementitious materials.
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Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp(2)/sp(3) hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.
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We develop a model of transport in multiscale porous media which accounts for adsorption in the different porosity scales. This model employs statistical mechanics to upscale molecular simulation and describe adsorption and transport at larger time and length scales. Using atom-scale simulations, which capture the changes in adsorption and transport with temperature, pressure, pore size, etc., this approach does not assume any adsorption or flow type. Moreover, by relating the local chemical potential µ(r) and density ρ(r), the present model accounts for adsorption effects and possible changes in the confined fluid state upon transport. This model constitutes a bottom-up framework of adsorption and transport in multiscale materials as it (1) describes the adsorption-transport interplay, (2) accounts for the hydrodynamics breakdown at the nm scale, and (3) is multiscale.
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Understanding the composition dependence of the hardness in materials is of primary importance for infrastructures and handled devices. Stimulated by the need for stronger protective screens, topological constraint theory has recently been used to predict the hardness in glasses. Herein, we report that the concept of rigidity transition can be extended to a broader range of materials than just glass. We show that hardness depends linearly on the number of angular constraints, which, compared to radial interactions, constitute the weaker ones acting between the atoms. This leads to a predictive model for hardness, generally applicable to any crystalline or glassy material.