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A presentation on Design Requirements for Commercial Sedimentary Geothermal Projects prepared by Chad Augustine for the 2016 SMU Power Plays Conference and Workshop.
The U.S. Department of Energy's (DOE's) Geothermal Technologies Office (GTO) engaged in a multiyear research collaboration among national laboratories, industry experts, and academia to identify a vision for growth of the domestic geothermal industry across a range of geothermal energy types. The effort, called the GeoVision analysis, assessed opportunities to expand geothermal energy deployment by improving technologies, reducing costs, and mitigating barriers. The analysis also evaluated the economic and environmental impacts of such deployment - including industry growth, consumer energy prices, water use, and air emissions - and investigated opportunities for desalination, mineral recovery, and hybridization with other energy technologies for greater efficiencies and lower costs. The GeoVision analysis used a suite of modeling tools and scenarios to evaluate the performance of geothermal technologies relative to other energy technologies. The assessment included evaluating the potential role of existing and future geothermal deployment in both the electric sector and the heating and cooling sector. In the electric sector, the GeoVision analysis considered electricity generation from existing conventional (hydrothermal) geothermal resources as well as unconventional geothermal resources, such as enhanced geothermal systems (EGS). In the heating and cooling sector, the analysis modeled geothermal heat pumps (GHPs, also called ground source heat pumps) and district-heating systems using both conventional and EGS resources. The analysis culminated in a summary report, GeoVision: Harnessing the Heat Beneath Our Feet (DOE 2019), as well as eight supporting task force reports (Lowry et al. 2017, Doughty et al. 2018, Wendt et al. 2018, Augustine et al. 2019, Liu et al. 2019, McCabe et al. 2019, Millstein et al. 2019, Young et al. 2019). Among other results, key findings of the analysis indicate that optimized permitting could potentially double geothermal capacity by 2050; technology improvements could increase geothermal power generation nearly 26-fold from today; and increased geothermal deployment can provide economic and environmental benefits to the United States. The analysis also concludes that GHPs can provide heating and cooling solutions to the equivalent of 28 million households and geothermal district-heating systems could experience exponential growth - from 21 installations today to 17,500 nationwide. In addition to summarizing analytical results about geothermal energy opportunities, the report includes a Roadmap of actionable items on which the stakeholder community can engage to achieve the outcomes of the analysis. The GeoVision Roadmap is a comprehensive call to action to encourage and guide stakeholders toward the shared goal of realizing the deployment levels and resulting benefits identified in the GeoVision analysis.
The U.S. Department of Energy's (DOE's) Geothermal Technologies Office (GTO) engaged in a multiyear research collaboration among national laboratories, industry experts, and academia to identify a vision for growth of the domestic geothermal industry across a range of geothermal energy types. The effort, called the GeoVision analysis, assessed opportunities to expand geothermal energy deployment by improving technologies, reducing costs, and mitigating barriers. The analysis also evaluated the economic and environmental impacts of such deployment - including industry growth, consumer energy prices, water use, and air emissions - and investigated opportunities for desalination, mineral recovery, and hybridization with other energy technologies for greater efficiencies and lower costs. The GeoVision analysis used a suite of modeling tools and scenarios to evaluate the performance of geothermal technologies relative to other energy technologies. The assessment included evaluating the potential role of existing and future geothermal deployment in both the electric sector and the heating and cooling sector. In the electric sector, the GeoVision analysis considered electricity generation from existing conventional (hydrothermal) geothermal resources as well as unconventional geothermal resources, such as enhanced geothermal systems (EGS). In the heating and cooling sector, the analysis modeled geothermal heat pumps (GHPs, also called ground source heat pumps) and district-heating systems using both conventional and EGS resources. The analysis culminated in a summary report, GeoVision: Harnessing the Heat Beneath Our Feet (DOE 2019), as well as eight supporting task force reports (Lowry et al. 2017, Doughty et al. 2018, Wendt et al. 2018, Augustine et al. 2019, Liu et al. 2019, McCabe et al. 2019, Millstein et al. 2019, Young et al. 2019). Among other results, key findings of the analysis indicate that optimized permitting could potentially double geothermal capacity by 2050; technology improvements could increase geothermal power generation nearly 26-fold from today; and increased geothermal deployment can provide economic and environmental benefits to the United States. The analysis also concludes that GHPs can provide heating and cooling solutions to the equivalent of 28 million households and geothermal district-heating systems could experience exponential growth - from 21 installations today to 17,500 nationwide. In addition to summarizing analytical results about geothermal energy opportunities, the report includes a Roadmap of actionable items on which the stakeholder community can engage to achieve the outcomes of the analysis. The GeoVision Roadmap is a comprehensive call to action to encourage and guide stakeholders toward the shared goal of realizing the deployment levels and resulting benefits identified in the GeoVision analysis.
Here, the short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simply as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m 2 .
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A “bottom-up” probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ~4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP).
Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).
Here, the strategic doping of transition metal ions into copper antimony sulphide (CAS) semiconducting nanostructures can significantly influence their photophysical and pseudocapacitive properties, for which there are few reports and therefore is the focus of this study. Accordingly, highly crystalline metal ion (Mn 2+ , Fe 2+ , Co 2+ , Ni 2+ and Zn 2+ ) doped off-stoichiometric copper rich/poor, antimony-rich/poor, and sulphur-poor CAS nanostructures (10–23 nm) were grown via colloidal (hot-injection) synthesis using metal diethyldithiocarbamate precursors. Importantly, metal ion doping significantly influences the structure and composition of the off-stoichiometric CAS nanostructures. Data from powder X-ray diffraction, Raman spectroscopy, high-resolution scanning/transmission electron microscopy, and energy dispersive X-ray spectroscopy confirm that the heavier metal ion dopants induce a novel phase transformation from famatinite (fCAS) to chalcostibite (cCAS) nanostructures. The influence of the metal ion dopants is also observed in the optical properties of as-synthesized nanostructures. This involves blue-shifted ultraviolet-visible absorption, reduced Urbach tailing, and tunable bandgaps between 2.17 and 2.38 eV. Also, the doped nanostructures display broad visible-near infrared photoluminescence via a triple radiative pathway with relatively short decay lifetimes between 0.2 and 6.1 ns. This is mediated by electronic transitions involving intrinsic (copper/antimony/sulphur interstitial) and extrinsic (metal ion interstitial) defect states. Additionally, electrodes prepared from Mn 2+ -doped fCAS nanostructures show enhanced pseudocapacitance via Na+ surface adsorption and intercalation relative to undoped fCAS electrodes, while Zn 2+ -doped cCAS electrodes exhibit pseudocapacitance via a combination of Na+ surface adsorption, intercalation, and redox reactions. These electrodes exhibit reduced charge transfer resistance, improved electronic conductivity and notably enhanced specific capacitance (∼222 F g −1 ), and charge transport, as measured in 1 M Na 2 SO 4 electrolyte via cyclic voltammetry and electrochemical impedance spectroscopy. To this end, the discovery of the metal ion-induced phase transformation presents a new avenue for optimizing the functional properties of fCAS and cCAS nanostructures, highlighting the critical role of metal ion-related defects in controlling the optical and electrochemical properties, towards potential solar absorption and energy storage applications.
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Recent theoretical advances and molecular-dynamic estimates of the dielectric constant of water have extended the HKF model for aqueous solution chemistry up to 6.0 gigapascals (GPa), which are conditions well beyond the capabilities of conventional NMR spectroscopy (Pan et al., 2013; Sverjensky et al., 2014, see also Wasserman and others, 1995). These developments provide strong motivation to design a simple NMR probe that allows experiments on solutions, at high resolution, to pressures of a few GPa (Pautler et al., 2014; Ochoa et al., 2015; 2016). Here we describe the performance of a compact NMR probe that can reach several GPa pressures. The probe is made by placing a solenoid microcoil inside of a standard piston-cylinder device used in solid-state physics. High pressures are achieved in the sample by applying force to a coaxial piston. Early designs of the probe, although useful, were limited in sample size to ~10-15μL. Here we describe modifications that allow greatly improved resolution and sensitivity, including 1H-1H NMR correlation spectroscopy, on solutions at 2.8 GPa pressure. Sample sizes can be expanded if, instead of a standard NMR spectrometer that is built around a superconducting magnet, one employs a magnetic-resonance imaging (MRI) system that is built around a permanent magnet. The MRI systems can apply larger magnetic field gradients than conventional spectrometers, and thus have more robust shimming capability, which is needed because of the juxtaposition of different alloys in the pressure cell. More importantly, these systems can have magnetic fields that are oriented perpendicular to the magnet bore, which allows rotation of the coil within the axis of the pressure cell to increase sample volumes and pressure. Sensitivity is improved by replacing the traditional, but reduced-volume, closed sample container mounted in the center of the NMR detection coil with an open NMR coil that dangles freely in solution, thus making the sample solution itself the pressure-transmission fluid. The efficacy of these modifications are demonstrated by measuring 1 H NMR spectra for ethyl alcohol and ethyl alcohol/methyl alcohol mixtures at pressures up to 2.8 GPa. As a result, further developments are discussed that will allow geochemists to acquire aqueous solution NMR spectra at higher 3-4 GPa pressures.
Abstract The doping levels of conjugated polymers significantly influence their conductivity, energetics, and optical properties. Recently, a highly conductive n‐doped polymer called poly (3,7‐dihydrobenzo[1,2‐b:4,5‐b′]difuran‐2,6‐dione) (poly(benzodifurandione), n‐PBDF) is discovered, opening new possibilities for n‐type conducting polymers in printed electronics and other fields. Controlling the doping level of n‐PBDF is of great interest due to its wide range of potential applications. Here controlled dedoping and redoping of n‐PBDF is reported and a mechanistic understating of such a process is provided. Dedoping occurs through electron transfer and proton capture, wherein the ionic dopants, tris(4‐bromophenyl)ammoniumyl hexachloroantimonate (Magic Blue), exhibit efficient proton capture ability and stronger interaction with n‐PBDF, resulting in high dedoping efficiency. Moreover, chemically dedoped PBDF can be redoped using various proton‐coupled electron transfer agents. By manipulating the doping levels of n‐PBDF thin films, ranging from highly doped to dedoped states, the system demonstrates controllable conductivity in five orders of magnitude, adjustable optical properties, and energetics. As a result, these characteristics demonstrate the potential applications of n‐PBDF in organic electrochemical transistors and thermoelectrics.
Doping-induced solubility control is a patterning technique for semiconducting polymers, which utilizes the reduction in polymer solubility upon p-type doping to provide direct, optical control of film topography and doping level. In situ direct-write patterning and imaging are demonstrated, revealing sub-diffraction-limited topographic features. Here, photoinduced force microscopy shows that doping level can be optically modulated with similar resolution.
Abstract Liquid crystals (LCs) are omnipresent in living matter, whose chirality is an elegant and distinct feature in certain plant tissues, the cuticles of crabs, beetles, arthropods, and beyond. Taking inspiration from nature, researchers have recently devoted extensive efforts toward developing chiral liquid crystalline materials with self‐organized nanostructures and exploring their potential applications in diverse fields ranging from dynamic photonics to energy and safety issues. In this review, an account on the state of the art of emerging chiral liquid crystalline nanostructured materials and their technological applications is provided. First, an overview on the significance of chiral liquid crystalline architectures in various living systems is given. Then, the recent significant progress in different chiral liquid crystalline systems including thermotropic LCs (cholesteric LCs, cubic blue phases, achiral bent‐core LCs, etc.) and lyotropic LCs (DNA LCs, nanocellulose LCs, and graphene oxide LCs) is showcased. The review concludes with a perspective on the future scope, opportunities, and challenges in these truly advanced functional soft materials and their promising applications.
In both chemical and electrochemical doping of organic semiconductors (OSCs), a counterion, either from the electrolyte or ionized dopant, balances the charge introduced to the OSC. Despite the large influence of this counterion on OSC optical and electronic response, there remains substantial debate on how a fundamental parameter, ion size, impacts these properties. Here, this work resolves much of this debate by accounting for two doping regimes. In the low-doping regime, the Coulomb binding energies between charge carriers on the OSC and the counterions are significant, and larger counterions lead to decreased Coulomb interactions, more delocalized charge carriers, and higher electrical conductivities. In the high-doping regime, the Coulomb binding energies become negligible due to the increased dielectric constant of the films and a smoothing of the energy landscape; thereby, the electrical conductivities depend primarily on the extent of morphological disorder in the OSC. Moreover, in regioregular poly(3-hexylthiophene), rr-P3HT, smaller counterions lead to greater bipolaron concentrations in the low-doping regime due to the increased Coulomb interactions. Emphasizing the impact of the counterion size, it is shown that larger counterions can lead to increased thermoelectric power factors for rr-P3HT.
Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.