Long Duration Energy Storage (LDES) Demonstration Projects in the US
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Proceedings of the 2023 Improving Scientific Software Conference
Proceedings of the 2023 Improving Scientific Software Conference
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Physical Review Research
We develop an adaptive method for quantum state preparation that utilizes randomness as an essential component and that does not require classical optimization. Instead, a cost function is minimized to prepare a desired quantum state through an adaptively constructed quantum circuit, where each adaptive step is informed by feedback from gradient measurements in which the associated tangent space directions are randomized. We provide theoretical arguments and numerical evidence that convergence to the target state can be achieved for almost all initial states. We investigate different randomization procedures and develop lower bounds on the expected cost function change, which allows for drawing connections to barren plateaus and for assessing the applicability of the algorithm to large-scale problems.
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Micro ribonucleic acids (miRNA) give our immune systems the ability to recognize viruses and other pathogens by their complementary single-stranded RNA (ssRNA) produced in the reproduction of the pathogen in our cells. When miRNA of a specific sequence is detected in a cell sample, it can be assumed that the immune system is activated and attempting to track down the infection. This pathway can be utilized to diagnose infection from a pathogen before the individual even develops symptoms, aiding in early disease detection and proper treatment. One of the ways that we can detect miRNA is through an assay of clustered regularly interspaced short palindromic repeats or “CRISPR” and the bacterial protein Cas13a. This report details discoveries made while attempting to optimize this assay for miRNA detection. After looking at several different factors within the assay, it was determined that some factors, such as reporter type and metallic ion concentration, are more impactful on the overall assay sensitivity than other factors, such as the overall concentration of Cas13a, CRISPR RNA (crRNA), or ssRNA reporter. It was also discovered that different sequences with different lengths require renewed optimization efforts, as each target has a unique binding affinity determined by the sequence length and composition. This information is crucial in the development of point of care molecular detection devices as they become sensitive enough to identify pathogens before they spread.
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Remote Sensing
High-altitude balloons carrying infrasound sensor payloads can be leveraged toward monitoring efforts to provide some advantages over other sensing modalities. On 10 July 2020, three sets of controlled surface explosions generated infrasound waves detected by a high-altitude floating sensor. One of the signal arrivals, detected when the balloon was in the acoustic shadow zone, could not be predicted via propagation modeling using a model atmosphere. Considering that the balloon’s horizontal motion showed direct evidence of gravity waves, we examined their role in infrasound propagation. Implementation of gravity wave perturbations to the wind field explained the signal detection and aided in correctly predicting infrasound travel times. Our results show that the impact of gravity waves is negligible below 20 km altitude; however, their effect is important above that height. The results presented here demonstrate the utility of balloon-borne acoustic sensing toward constraining the source region of variability, as well as the relevance of complexities surrounding infrasound wave propagation at short ranges for elevated sensing platforms.
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Journal of Applied Mechanics, Transactions ASME
Avoiding stress concentrations is essential to achieve robust parts since failure tends to originate at such concentrations. With recent advances in multimaterial additive manufacturing, it is possible to alter the stress (or strain) distribution by adjusting the material properties in selected locations. Here, we investigate the use of grayscale digital light processing (g-DLP) 3D printing to create modulus gradients around areas of high stress. These gradients prevent failure by redistributing high stresses (or strains) to the neighboring material. The improved material distributions are calculated using finite element analysis. The much-enhanced properties are demonstrated experimentally for thin plates with circular, triangular, and elliptical holes. This work suggests that multimaterial additive manufacturing techniques like g-DLP printing provide a unique opportunity to create tougher engineering materials and parts.
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