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The composition of the lithium cation (Li + ) solvation shell in mixed linear and cyclic carbonate-based electrolytes has been re-examined using Born–Oppenheimer molecular dynamics and Li + (EC) n (DMC) m cluster calculations.
Many elements are scarcely soluble in aqueous conditions found in high pH environments, such as calcareous grassland soils, unless complexed to strong binding organic ligands. To overcome this limitation, some plants and microbes produce chelators that solubilize micronutrient metals such as Fe, Ni, Cu, and Zn from mineral phases. These complexes are taken up by organisms via specific membrane receptors, thereby differentially impacting the bioavailability of these metals to the plant and microbial community. Although the importance of these chelation strategies for individual organisms has been well established, little is known about which pathways coexist within rhizosphere microbiomes or how they interact and compete for metal binding. Identifying these metallo-organic species within natural ecosystems has remained a formidable analytical challenge due to the vast diversity of compounds and poorly defined metabolic processes in complex soil matrix. Herein, we employed recently developed liquid chromatography (LC) mass spectrometry (MS) methods to characterize the speciation of water-soluble dissolved trace elements (Fe, Ni, Cu, and Zn) from Kansas Prairie soil. Both plant and fungal chelators were identified, revealing compound-specific patterns of chelation to biologically essential metals. Numerous metabolites typically implicated in plant iron acquisition and homeostasis, including mugineic acids, deoxymugineic acid, nicotianamine, and hydroxynicotianamine, dominated the speciation of divalent metals such as Ni, Cu, and Zn (2-57 pmol / g soil). In contrast, the fungal siderophore ferricrocine bound comparatively more trivalent Fe (9pmol / g soil). These results define biochemical pathways that underpin the regulation of metals in the grassland rhizosphere. They also raise new questions about the competition of these compounds for metal binding and their bioavailability to different members of the rhizosphere population. Even small structural differences result in significant differences in their environmental metal speciation, and likely impact metal uptake within the rhizosphere of calcareous soils.
Ethanol to middle distillates (ETMD) is a promising pathway to produce sustainable liquid fuels to decarbonize the hard-to-electrify transportation sectors due to (1) the abundant sugar/starch and lignocellulosic biomass, (2) the existing deployment scale of fuel ethanol production (similar to 29 billion gallons per year globally), and (3) emerging opportunities in C2+ alcohol synthesis from CO2. Here we report a conceptual market-responsive biorefinery centered around a new ETMD pathway based on one-step ethanol to butene-rich olefins (ETO) over a Cu-Zn-Y/Beta catalyst. Specifically, this ethanol conversion pathway comprises one-step ETO, oligomerization, and hydrotreating. This ETO is distinct from that in the conventional ethanol-to-jet process which is based on two-step ethanol to ethylene and ethylene oligomerization to butenes. Butene-rich olefins can be shifted to butadiene-rich products by simply changing the reaction atmosphere from hydrogen to inert gas over the same ETO catalyst. Leveraging the experimental results, baseline techno-economic analysis (TEA) and sensitivity analysis indicate that the ethanol conversion cost is $0.60 per gallon gasoline equivalent (GGE), with opportunities for further cost reduction via improving the liquid hydrocarbon yield and space velocities, and process optimization on balancing dewatering of ethanol feed prior to the ETO step. The minimum fuel selling price (MFSP) of liquid hydrocarbons derived from corn starch ethanol with butadiene as coproduct is $1.64 per GGE, in the range that is cost competitive with petroleum kerosene-type jet fuel. Projected MFSP for cellulosic ethanol (corn stover) derived hydrocarbons is below $3.00 per GGE and co-production of butadiene further reduces the MFSP to $1.70 per GGE. The Well-to-Wake life-cycle analysis indicates that 85% greenhouse gas emission reduction can be achieved when using corn stover compared to petroleum reference and the associated carbon credits will provide significant economic incentives to favor the cellulosic ethanol-derived hydrocarbon fuels. This study demonstrates a low-cost pathway to middle distillate fuels leveraging existing ethanol infrastructure, where catalysis innovation drives the reduction of process complexity and flexible coproduction of a value-added chemical product.
Ettringite is a naturally occurring mineral found in cementitious matrices that is known for its ability to incorporate environmentally mobile oxyanion contaminants. To better assess this immobilization mechanism for contaminants within cementitious waste forms intended for nuclear waste storage, this work explores how mixed oxyanion contaminants compete for ettringite incorporation and influence the evolving mineralogy. Ettringite was precipitated in the presence of TcO4-, IO3-, and/or CrO42-, known contaminants of concern to nuclear waste treatment, over pre-determined precipitation periods. Solution analyses quantified contaminant removal and the collected solid was characterized using bulk and microprobe XRD coupled with PDF and microprobe XRF analyses. Results suggest that =96% IO3- is removed from solution, regardless of ettringite precipitation time or the presence of TcO4- or CrO42-. However, TcO4- removal remained <20%, was not significantly improved with longer ettringite precipitation times, and significantly decreased in the presence of IO3-. When IO3- is comingled with CrO42, gypsum is formed as a secondary mineral phase, which results in oxyanion partitioning among mineral phases, e.g., IO3- incorporation into ettringite and CrO42- incorporation into gypsum via SO42- substitution. Results from this work exemplify the importance of competitive immobilization when assessing waste form performance and environmental risk of contaminant release.
Biofuels produced from both terrestrial and algal biomass feedstocks can contribute to energy security while providing economic, environmental, and social benefits. To assess the potential for land competition between these two feedstock types in the United States, we evaluate a scenario in which 41.5 x 109 L yr-1 of second-generation biofuels are produced on pastureland, the most likely land base where both feedstock types may be deployed. This total includes 12.0 x 109 L yr-1 of biofuels from open-pond microalgae production and 29.5 x 109 L yr-1 of biofuels from terrestrial dedicated feedstock supply systems. Under these scenarios, open-pond microalgae production is projected to use 1.2 million ha of private pastureland, while terrestrial dedicated feedstock supply systems would use 14.0 million ha of private pastureland. A spatial meta-analysis indicates that potential competition for land under these scenarios would be concentrated in 110 counties, containing 1.0 and 1.7 million hectares of algal and terrestrial dedicated feedstock production, respectively. A land competition index applied to these 110 counties suggests that 38 to 59 counties could experience competition for upwards of 40% of a county’s pastureland. However, this combined 2.7 million ha represents only 2%-5% of total pastureland in the U.S., with the remaining 12.5 million ha of algal or terrestrial dedicated feedstock production on pastureland in non-competing areas.
Acetoclastic methanogenesis is a key metabolic process in anaerobic digestion, a technology with broad applications in biogas production and waste treatment. Acetoclastic methanogenesis is known to be performed by two archaeal genera, Methanosaeta and Methanosarcina. The conventional model posits that Methanosaeta populations are more competitive at low acetate levels (<1 mM) than Methanosarcina and vice versa at higher acetate concentrations. While this model is supported by an extensive body of studies, reports of inconsistency have grown that Methanosaeta were observed to outnumber Methanosarcina at elevated acetate levels. In this study, monitoring of anaerobic digesters treating animal wastewater unexpectedly identified Methanosaeta as the dominant acetoclastic methanogen population at both low and high acetate levels during organic overloading. The surprising competitiveness of Methanosaeta at elevated acetate was further supported by the enrichment of Methanosaeta with high concentrations of acetate (20 mM). The dominance of Methanosaeta in the methanogen community could be reproduced in anaerobic digesters with the direct addition of acetate to above 20 mM, again supporting the competitiveness of Methanosaeta over Methanosarcina at elevated acetate levels. This study for the first time systematically demonstrated that the dominance of Methanosaeta populations in anaerobic digestion could be linked to the competitiveness of Methanosaeta at elevated acetate concentrations. Given the importance of acetoclastic methanogenesis in biological methane production, findings from this study could have major implications for developing strategies for more effective control of methanogenic treatment processes.
We investigate chaotic advection and diffusion in autocatalytic reactions for time-periodic sine flow computationally using a mapping method with operator splitting. We specifically consider three different autocatalytic reaction schemes: a single autocatalytic reaction, competitive autocatalytic reactions, which can provide insight into problems of chiral symmetry breaking and homochirality, and competitive autocatalytic reactions with recycling. In competitive autocatalytic reactions, species B and C both undergo an autocatalytic reaction with species A such that A+B→2B and A+C→2C. Small amounts of initially spatially localized B and C and a large amount of spatially homogeneous A are advected by the velocity field, diffuse, and react until A is completely consumed and only B and C remain. We find that local finite-time Lyapunov exponents (FTLEs) can accurately predict the final average concentrations of B and C after the reaction completes. The species that starts in the region with the larger FTLE has, with high probability, the larger average concentration at the end of the reaction. If B and C start in regions with similar FTLEs, their average concentrations at the end of the reaction will also be similar. When a recycling reaction is added, the system evolves towards a single species state, with the FTLE often being useful in predicting which species fills the entire domain and which is depleted. The FTLE approach is also demonstrated for competitive autocatalytic reactions in journal bearing flow, an experimentally realizable flow that generates chaotic dynamics.
Data competitions rely on real-time leaderboards to rank competitor entries and stimulate algorithm improvement. While such competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised learning competition is vulnerable to overfitting, where the winning solutions are so closely tuned to the particular set of provided data that they cannot generalize to the underlying problem of interest to the host. This paper outlines some important considerations for strategically designing relevant and informative data sets to maximize the learning outcome from hosting a competition based on our experience. It also describes a postcompetition analysis that enables robust and efficient assessment of the strengths and weaknesses of solutions from different competitors, as well as greater understanding of the regions of the input space that are well-solved. The postcompetition analysis, which complements the leaderboard, uses exploratory data analysis and generalized linear models (GLMs). The GLMs not only expand the range of results we can explore, they also provide more detailed analysis of individual subquestions including similarities and differences between algorithms across different types of scenarios, universally easy or hard regions of the input space, and different learning objectives. When coupled with a strategically planned data generation approach, the methods provide richer and more informative summaries to enhance the interpretation of results beyond just the rankings on the leaderboard. The methods are illustrated with a recently completed competition to evaluate algorithms capable of detecting, identifying, and locating radioactive materials in an urban environment.
Demand response (DR) of building HVAC load can provide crucial demand-side flexibility for the future smart grid. Compared to direct load control, price-based control can respect the customers’ autonomy and privacy. However, it is challenging for price-based control to attain provable performance guarantees under future uncertainty. In this paper, we propose a framework for a utility to perform price-based control of flexible building load within the utility’s service area, in order to attain competitive performance guarantees in terms of controlling the system peak demand under future uncertainty. By adopting a two-step approach, our online price-based control solution can attain a provable competitive ratio for all possible realizations within a given uncertainty set. Simulation experiments demonstrate that, with a robustification procedure, our solution can perform well not only for worst-case inputs, but also for average-case inputs.
We show evidence that the competition between the antiferromagetic metallic phase and the charge- and orbital-ordered insulating phase at the reentrant phase boundary of a layered manganite, LaSr2Mn2O7, can be manipulated using ultrafast optical excitation. The time- dependent evolution of the Jahn-Teller superlattice reflection, which indicates the formation of the charge and orbital order, was measured at different laser fluences. The laser-induced enhancement and reduction the Jahn-Teller reflection intensity shows a reversal of sign between earlier (~10 ns) and later (~150 ns) time delays during the relaxation after photo excitation. This effect is consistent with a scenario whereby the laser excitation modulates the local competition between the metallic and the insulating phases.
Over the past two years, a wave energy converter control systems competition (WECCCOMP) has been in progress, with the objective of comparing different wave energy converter (WEC) control paradigms on a standard benchmark problem. The target system is a point absorber, corresponding to a single float with an absolute reference, of the WaveStar WEC prototype. The system was modelled in WEC-Sim, with the hydrodynamic parameters validated against tank test data. Competitors were asked to design and implement a WEC control system for this model, with performance evaluated across six sea states. The evaluation criteria included a weighted combination of average converted power, peak/average power, and the degree to which the system physical constraints were exploited or temporarily exceeded.
Two anomaly-detection criteria are proposed for transactive energy systems with competitive markets. Participants of transactive energy systems seek an optimal power allocation through hybrid economic-control methods to facilitate the integration of various types of distributed energy resources to power distribution systems. In transactive energy systems, every participant is assumed to be a rational entity, and consumers have diminishing marginal utility and suppliers have increasing marginal cost. With the first proposed anomaly-detection criterion, the monotonicity of marginal cost and marginal utility are examined. The impact of line flow constraints is also taken into consideration. Then, the second anomaly-detection criterion is proposed for TESs with marginal cost and marginal utility which change faster than a certain rate. The second criterion is more accurate than the first one for TES with marginal cost and marginal utility which change faster than a certain rate, but it requires the knowledge of that rate. Neither criteria requires more data than those necessary to find the optimal power allocation and the market-clear price in a transactive energy system. Therefore, the proposed criteria do not disclose any more data than necessary. As the monotonicity of marginal cost and marginal utility in a TES with competitive markets results in convex objective functions in an optimization problem and strongly convex ones when marginal cost and marginal utility changes faster than a certain rate, the two detection criteria are also applicable to anomaly detection of general convex optimization problems. Simulations are carried out to show the efficacy of the proposed criteria to detect anomalies caused by cyberattacks.
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The SADC region has significant natural resource potential to increase renewable energy generation, improve electricity reliability, and support economic development. This research finds an apparent lack of confidence from electricity infrastructure investors in SAPP wholesale electricity markets, which increases risk perception and lowers the likelihood of capital deployment. With respect to free market fundamentals, competitive market obstacles and renewable energy development obstacles are characterized. Stakeholders identified the top obstacles to well-functioning competitive markets as insufficient transmission infrastructure for interconnection and regional movement of electricity, dominance of national single-buyer markets, and lack of or weak nation-state regulatory frameworks. Stakeholders prioritized the top three obstacles for renewable energy development as a lack of viable commercial arrangements for variable renewable energy (VRE) balancing, lack of functional and consistent nation-level regulations, and higher project costs related to reliance on imported equipment. With respect to potential solution options, stakeholders prioritized the development of new cost allocation and finance methods to facilitate new transmission expansion, training to educate new or potential new market entrants on SAPP processes, as well as modeling and analysis of regional SAPP participation benefits disaggregated to the nation-state level. From these perspectives, this research identified strategy options for consideration including transitioning SAPP to a regional transmission operator (RTO) for operation and planning of cross-border transmission facilities and market administration, shifting operations of SAPP member transmission systems to Independent System Operators (ISOs), establishing a regional regulatory authority and enhancing market data transparency. Implementing these reforms is expected to be challenging, but not insurmountable, given the domestic political, legal, and jurisdictional complexities of the SADC region.
Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.