Maximizing MeV x-ray dose in relativistic laser-solid interactions
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We propose an operating-envelope-aware, prosumer-centric, and efficient energy community that aggregates individual and shared community distributed energy resources and transacts with a regulated distribution system operator (DSO) under a generalized net energy metering tariff design. To ensure safe network operation, the DSO imposes dynamic export and import limits, known as dynamic operating envelopes, on end-users' revenue meters. Given the operating envelopes, we propose an incentive-aligned community pricing mechanism under which the decentralized optimization of community members' benefit implies the optimization of overall community welfare. The proposed pricing mechanism satisfies the cost-causation principle and ensures the stability of the energy community in a coalition game setting. Numerical examples provide insights into the characteristics of the proposed pricing mechanism and quantitative measures of its performance.
Newly developed high thermal conductivity polymer composite 3D printing filaments are used to characterize the thermal properties as a function of print orientation. The thermal conductivity of a printed part is anisotropic and varies by 2-6 times depending on the print direction - demonstrating higher conductivity in the deposition direction (in-plane) than in the two directions perpendicular to the deposition direction (cross-plane and through-plane). Therefore, deposition path planning greatly affects the overall heat dissipation rate and the performance of the heat sink. Traditionally, 3D printing slicers generate deposition paths based solely on geometric constraints. This work investigates a new approach of deposition path planning assisted by computational predictions of the heat sink thermal performance. The proposed approach uses a thermal simulation of a 3D-printed part, accounting for the anisotropic thermal properties, and the orientation of the local material properties are assigned based on the deposition path in multiple print orientations. The performances predicted via the simulations are compared, and the optimal deposition path is determined. For the highest thermal conductivity 3D printing filament (~ 12 W/m- K in-plane), a heat sink printed with the print direction parallel to the fins z-axis had ~20% improved performance in comparison to a heat sink with print direction perpendicular to the fins z-axis. Moreover, a plastic 3D printed heat sink was able to perform within 7% of an extruded Aluminum heat sink with similar geometry under natural convection. The computational predictions show the same trend as experimental measurements using 3D printed heat sinks.
Many tracking PV systems avoid row-to-row shading by backtracking in morning and afternoon. Because the common single-axis backtracking implementation assumes the array is in a horizontal plane, it does not fully prevent row-to-row shading in arrays installed on cross-axis slopes, e.g. an east-west slope for a tracker with north-south axis alignment. This paper presents the simulated effect of reduced self-shading on annual production with two modified backtracking strategies. Depending on the array geometry and the steepness of the cross-axis grade, using a modified backtracking strategy improved annual yield by 3-10%.
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Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.
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This software library presents efficient and multithreaded implementations of matrix low rank approximation via column selection in C++17 code. The algorithms are described in Fornace, Mark, and Michael Lindsey. "Column and row subset selection using nuclear scores: algorithms and theory for Nystro m approximation, CUR decomposition, and graph Laplacian reduction." arXiv preprint arXiv:2407.01698 (2024). The presented methods are by-and-large ver novel, have provable approximation guarantees, multiple use-cases, and exhibit higher quality approximations on a variety of studied examples.
Miscanthus is a leading bioenergy crop with enormous lignocellulose production potential for biofuels and chemicals. However, lignocellulose recalcitrance leads to biomass process difficulty for an efficient bioethanol production. Hence, it becomes essential to identify the integrative impact of lignocellulose recalcitrant factors on cellulose accessibility for biomass enzymatic hydrolysis. In this study, we analyzed four typical pairs of Miscanthus accessions that showed distinct cell wall compositions and sorted out three major factors that affected biomass saccharification for maximum bioethanol production. Among the three optimal (i.e., liquid hot water, H 2 SO 4 and NaOH) pretreatments performed, mild alkali pretreatment (4% NaOH at 50 °C) led to almost complete biomass saccharification when 1% Tween-80 was co-supplied into enzymatic hydrolysis in the desirable Miscanthus accessions. Consequently, the highest bioethanol yields were obtained at 19% (% dry matter) from yeast fermentation, with much higher sugar–ethanol conversion rates by 94–98%, compared to the other Miscanthus species subjected to stronger pretreatments as reported in previous studies. By comparison, three optimized pretreatments distinctively extracted wall polymers and specifically altered polymer features and inter-linkage styles, but the alkali pretreatment caused much increased biomass porosity than that of the other pretreatments. Based on integrative analyses, excellent equations were generated to precisely estimate hexoses and ethanol yields under various pretreatments and a hypothetical model was proposed to outline an integrative impact on biomass saccharification and bioethanol production subjective to a predominate factor (CR stain) of biomass porosity and four additional minor factors (DY stain, cellulose DP, hemicellulose X/A, lignin G-monomer). Using four pairs of Miscanthus samples with distinct cell wall composition and varied biomass saccharification, this study has determined three main factors of lignocellulose recalcitrance that could be significantly reduced for much-increased biomass porosity upon optimal pretreatments. It has also established a novel standard that should be applicable to judge any types of biomass process technology for high biofuel production in distinct lignocellulose substrates. Hence, this study provides a potential strategy for precise genetic modification of lignocellulose in all bioenergy crops.
We present a systematic optimization of nighttime thermoelectric power generation system utilizing radiative cooling. We show that an electrical power density >2 W/m 2 , two orders of magnitude higher than the previously reported experimental result, is achievable using existing technologies. This system combines radiative cooling and thermoelectric power generation and operates at night when solar energy harvesting is unavailable. The thermoelectric power generator (TEG) itself covers less than 1 percent of the system footprint area when achieving this optimal power generation, showing economic feasibility. We study the influence of emissivity spectra, thermal convection, thermoelectric figure of merit and the area ratio between the TEG and the radiative cooler on the power generation performance. We optimize the thermal radiation emitter attached to the cold side and propose practical material implementation. The importance of the optimal emitter is elucidated by the gain of 153% in power density compared to regular blackbody emitters.
In this paper, we experimentally demonstrate a broadband Archimedes spiral delay line with high packing density on a silicon photonic platform. This high density is achieved by optimizing the gap between the adjacent waveguides (down to sub-micron scale) in the spiral configuration. However, care must be taken to avoid evanescent coupling, the presence of which will cause the spiral to behave as a novel type of distributed spiral resonator. To this end, an analytical model of the resonance phenomenon was developed for a simple spiral. Moreover, it is demonstrated that this distributed spiral resonator effect can be minimized by ensuring that adjacent waveguides in the spiral configuration have different propagation constants ( β ). Experimental validations were accomplished by fabricating and testing multiple spiral waveguides with varying lengths (i.e., 0.4, 0.8, and 1.4 mm) and separation gaps (i.e., 300 and 150 nm). Finally, a Linear Density Figure of Merit (LDFM) is introduced to evaluate the packing efficiency of various spiral designs in the literature. In this work, the optimum experimental design with mitigated resonance had a length of 1.4mm and occupied an area of 60 × 60µm, corresponding to an LDFM of 388km -1 .
The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses.
Despite rapid advancements in power conversion efficiency in the last decade, perovskite solar cells still perform below their thermodynamic efficiency limits. Non-radiative recombination, in particular, has limited the external radiative efficiency and open circuit voltage in the highest performing devices. We review the historical progress in enhancing perovskite external radiative efficiency and determine key strategies for reaching high optoelectronic quality. Specifically, we focus on non-radiative recombination within the perovskite layer and highlight novel approaches to reduce energy losses at interfaces and through parasitic absorption. By strategically targeting defects, it is likely that the next set of record-performing devices with ultra-low voltage losses will be achieved.