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At least 253 records · Page 14

Ion Exchange of Selected Group II Metals and Lead by Crystalline Silicotitanate and Competition for Cs Exchange Sites

A series of batch contact tests were conducted to evaluate the exchange behavior of Ba, Ca, Pb, and Sr onto crystalline silicotitanate (CST) in support of an expedited Cs removal and pretreatment system at the Hanford site. Binary Na/M 2+ and ternary Na/Cs/M 2+ isotherms were generated to understand selectivity, capacity, and competitive impact of each analyte on Cs uptake from a simple 1 M NaOH/4.6 M NaNO 3 simulant. Analyte loading from a 0.1 M NaOH/5.5 M NaNO 3 simulant was assessed to determine the effect of hydroxide concentration on binary Na/M 2+ isotherms. Finally, results from binary and ternary isotherms indicated that group II metals, and Pb do not impact CST performance toward CST at concentrations expected in Hanford tank waste supernate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rigid monoclonal antibodies improve detection of SARS-CoV-2 nucleocapsid protein

Monoclonal antibodies (mAbs) are the basis of treatments and diagnostics for pathogens and other biological phenomena. We conducted a structural characterization of mAbs against the N-terminal domain of nucleocapsid protein (NPNTD) from SARS-CoV-2 using small-angle X-ray scattering and transmission electron microscopy. Our solution-based results distinguished the mAbs’ flexibility and how this flexibility affects the assembly of multiple mAbs on an antigen. By pairing two mAbs that bind different epitopes on the NPNTD, we show that flexible mAbs form a closed sandwich-like complex. With rigid mAbs, a juxtaposition of the antigen-binding fragments is prevented, enforcing a linear arrangement of the mAb pair, which facilitates further mAb polymerization. In a modified sandwich enzyme-linked immunosorbent assay, we show that rigid mAb-pairings with linear polymerization led to increased NPNTD detection sensitivity. These enhancements can expedite the development of more sensitive and selective antigen-detecting point-of-care lateral flow devices, which are critical for early diagnosis and epidemiological studies of SARS-CoV-2 and other pathogens.

60 APPLIED LIFE SCIENCES↗

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗

LCLS-II helium cryoplant and cryo distribution system installation

The helium cryoplant and cryo distribution system (CDS) are key elements of the new superconducting Linac Coherent Light Source (LCLS-II) and will provide superfluid helium to the accelerator. The cryoplant consists of two helium refrigerators with an equivalent 4.5 K refrigeration capacity of 18 kW each. The 37 cryomodules of the LINAC will be operated at a temperature of 2.0 K to accelerate a 4 GeV electron beam that will generate extremely bright X-ray laser light. Two five-stage cold compressor cold boxes will be utilized to provide superfluid helium II for the superconducting cavity structures with a total cooling capacity of 8 kW at 2.0 K. This paper describes the installation of the LCLS-II cryoplant and CDS. The LCLS-II cryoplant was designed and contributed by Jefferson Lab. To expedite the project completion the reuse of proven design and technology from the Jefferson Lab CHL-2 cryoplant was the preferred strategy. The CDS consists of ~260 m thermally shielded and vacuum super insulated transfer lines, two distribution boxes and eight feed and end caps, and was designed and contributed by Fermilab. SLAC installed the cryoplant components into a newly erected building and the CDS components into the existing accelerator tunnel and klystron gallery with strong engineering support from both partner labs.

43 PARTICLE ACCELERATORS↗

Recent developments in 3D-printed membranes for water desalination

The recognition of membrane separations as a vital technology platform for enhancing the efficiency of separation processes has been steadily increasing. Concurrently, 3D printing has emerged as an innovative approach to fabricating reverse osmosis membranes for water desalination and treatment purposes. This method provides a high degree of control over membrane chemistry and structural properties. In particular, when compared to traditional manufacturing techniques, 3D printing holds the potential to expedite customization, a feat that is typically achieved through conventional manufacturing methods but often involves numerous processes and significant costs. This review aims to present the current advancements in membrane manufacturing technology specifically tailored for water desalination purposes, with a particular focus on the development of 3D-printed membranes. A comprehensive analysis of recent progress in 3D-printed membranes is provided. However, conducting experimental work to investigate various influential factors while ensuring consistent results poses a significant challenge. To address this, we explore how membrane manufacturing processes and performance can be effectively pre-designed and guided through the use of molecular dynamics simulations. Finally, this review outlines the challenges faced and presents future perspectives to shed light on research directions for optimizing membrane manufacturing processes and achieving optimal membrane performance.

3D printing membranes↗

Accelerating Ocean-Based Renewable Energy Educational Opportunities to Achieve a Clean Energy Future

The United Nations has named 2021–2030 the Decade of Ocean Science for Sustainable Development with goals to 'strengthen the international cooperation needed to develop the scientific research and innovative technologies that can connect ocean science with the needs of society' (IOC 2019 The science we need for the ocean we want: the United Nations decade of ocean science for sustainable development (2021–2030) (Paris) p 24). Important actions that have been identified in support of sustainable development goals include capacity-building, training, and education. This includes educational opportunities for ocean-based renewable energy development in support of a healthy planet and ocean. Offshore wind is experiencing rapid development globally and, while the U.S. offshore wind market is still nascent, it is on the brink of exponential growth based on large cost reductions driven largely by European development and technology advances. Growth is also expected in wave and tidal energy with significant opportunities identified for various distributed markets through the Powering the Blue Economy™ initiative, with longer-term implications for expansion at the utility scale (LiVecchi et al 2019 Powering the blue economy; exploring opportunities for marine renewable energy in maritime markets p 207). In order to expedite progress and maximize benefits to the national, state, and local economies, these development actions will require a broad, diverse, and appropriately trained workforce. The ocean-based renewable energy workforce needs engineers and scientists to develop cost-effective technologies, as well as trade and maritime workers to eventually deploy the technologies at scale. In the United States, educational institutions, state governments, and private developers are taking action to understand job skills and capability requirements and to develop educational and training programs to meet offshore workforce needs; most are focused on offshore wind power, with gaining interest in marine energy. This article explores the workforce requirements of the growing ocean-based renewable energy industry and the current state of education and training programs to meet those requirements in order to identify gaps and make recommendations for further workforce development activities and initiatives. An international view needs to be adopted that incorporates the education and skill needs of early-stage marine energy technologies and evolving offshore wind technologies together with more market-ready offshore renewable energy markets. By accelerating educational development opportunities in ocean-based renewable energy, these growing blue economy markets can deliver significant economic and social benefits.

50 EE - Wind and Water Power Program - Water (EE-4↗

Anticipating water distribution service outages from increasing temperatures

With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.

54 ENVIRONMENTAL SCIENCES↗

CRISPR-GRIT: Guide RNAs with Integrated Repair Templates Enable Precise Multiplexed Genome Editing in the Diploid Fungal Pathogen Candida albicans

Candida albicans, an opportunistic fungal pathogen, causes severe infections in immunocompromised individuals. Limited classes and overuse of current antifungals have led to the rapid emergence of antifungal resistance. Thus, there is an urgent need to understand fungal pathogen genetics to develop new antifungal strategies. Genetic manipulation of C. albicans is encumbered by its diploid chromosomes requiring editing both alleles to elucidate gene function. Although the recent development of CRISPR-Cas systems has facilitated genome editing in C. albicans, large-scale and multiplexed functional genomic studies are still hindered by the necessity of cotransforming repair templates for homozygous knockouts. Here, we present CRISPR-GRIT (Guide RNAs with Integrated Repair Templates), a repair template-integrated guide RNA design for expedited gene knockouts and multiplexed gene editing in C. albicans. Here, we envision that this method can be used for high-throughput library screens and identification of synthetic lethal pairs in both C. albicans and other diploid organisms with strong homologous recombination machinery.

60 APPLIED LIFE SCIENCES↗

Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports

Objectives: This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status. Materials and Methods: We utilized 594 875 electronic pathology reports from 178 121 tumors diagnosed in Kentucky, Louisiana, New Jersey, New Mexico, Seattle, and Utah to train 2 deep-learning algorithms to classify breast cancer patients using their biomarkers test results. We used balanced error rate (BER), demographic parity (DP), equalized odds (EOD), and equal opportunity (EOP) to assess bias. Results: We found differences in predictive accuracy between registries, with the highest accuracy in the registry that contributed the most data (Seattle Registry, BER ratios for all registries >1.25). BER showed no significant algorithmic bias in extracting biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) for race, Hispanic ethnicity, age at diagnosis, or socioeconomic subgroups (BER ratio <1.25). DP, EOD, and EOP all showed insignificant results. Discussion: We observed significant differences in BER by registry, but no significant bias using the DP, EOD, and EOP metrics for socio-demographic or racial categories. This highlights the importance of employing a diverse set of metrics for a comprehensive evaluation of model fairness. Conclusion: A thorough evaluation of algorithmic biases that may affect equality in clinical care is a critical step before deploying algorithms in the real world. We found little evidence of algorithmic bias in our biomarker classification tool. Artificial intelligence tools to expedite information extraction from clinical records could accelerate clinical trial matching and improve care.

60 APPLIED LIFE SCIENCES↗

Biosensors for the detection of chorismate and cis,cis -muconic acid in Corynebacterium glutamicum

Abstract Corynebacterium glutamicum ATCC 13032 is a promising microbial chassis for industrial production of valuable compounds, including aromatic amino acids derived from the shikimate pathway. In this work, we developed two whole-cell, transcription factor based fluorescent biosensors to track cis,cis-muconic acid (ccMA) and chorismate in C. glutamicum. Chorismate is a key intermediate in the shikimate pathway from which value-added chemicals can be produced, and a shunt from the shikimate pathway can divert carbon to ccMA, a high value chemical. We transferred a ccMA-inducible transcription factor, CatM, from Acinetobacter baylyi ADP1 into C. glutamicum and screened a promoter library to isolate variants with high sensitivity and dynamic range to ccMA by providing benzoate, which is converted to ccMA intracellularly. The biosensor also detected exogenously supplied ccMA, suggesting the presence of a putative ccMA transporter in C. glutamicum, though the external ccMA concentration threshold to elicit a response was 100-fold higher than the concentration of benzoate required to do so through intracellular ccMA production. We then developed a chorismate biosensor, in which a chorismate inducible promoter regulated by natively expressed QsuR was optimized to exhibit a dose-dependent response to exogenously supplemented quinate (a chorismate precursor). A chorismate–pyruvate lyase encoding gene, ubiC, was introduced into C. glutamicum to lower the intracellular chorismate pool, which resulted in loss of dose dependence to quinate. Further, a knockout strain that blocked the conversion of quinate to chorismate also resulted in absence of dose dependence to quinate, validating that the chorismate biosensor is specific to intracellular chorismate pool. The ccMA and chorismate biosensors were dually inserted into C. glutamicum to simultaneously detect intracellularly produced chorismate and ccMA. Biosensors, such as those developed in this study, can be applied in C. glutamicum for multiplex sensing to expedite pathway design and optimization through metabolic engineering in this promising chassis organism. One-Sentence Summary High-throughput screening of promoter libraries in Corynebacterium glutamicum to establish transcription factor based biosensors for key metabolic intermediates in shikimate and β-ketoadipate pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗

The Physical and Engineering Limits of Coupled In situ TEM Experiments

Almost all future energy systems (advanced nuclear reactors, fusion energy system, concentrating solar-thermal power (CSP), and wind technologies) are limited by degradation of key material systems exposed to multiple environmental stressors. The degradation during exposure to high temperatures, radiation, mechanical loading, and chemical attack is often dictated by mechanisms active at the microstructural level. The nature of these mechanisms and the associated variations between sequential and concurrent interplay can be explored if the transmission electron microscope (TEM) is utilized as a toolbox for exploration [1]. One such tool developed at Sandia National Laboratories to couple several of these environments is the In situ Ion Irradiation TEM (I3TEM) [2]. Several studies over the last decade utilizing this tool have shown that the scientific intuition developed over decades of sequential experiments is not always a good indicator of concurrent mechanisms or failure routes. This presentation will highlight the recent and planned additions into the I3TEM facility of a Waviks gas injection system and Raman system, respectively, as can be seen in Fig. 1, permitting environmental degradation from gas species leaked into the pole piece region during quantitative mechanical loading (indentation, monotonic loading, high temperature creep, irradiation induced creep, and high-cycle fatigue); multi-beam ion irradiation (energies ranging from 1 keV to 48 MeV and species from H to Au); laser exposure (20 W and 1064 nm), or various combinations thereof that are already possible [3]. This addition permits the facility to explore both sequential or concurrently the four axes of stressors: thermal, mechanical, radiation, and chemical. This information can be directly coupled to modeling, expediting the refinement and validation of both atomistic and mesoscale models.

degradation↗

Rewiring cell-free metabolic flux in E. coli lysates using a block—push—pull approach

Abstract Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the ‘block—push—pull’ concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

59 BASIC BIOLOGICAL SCIENCES↗

Methods to Account for CAP-88 PC-Omitted Nuclides in Radioactive Air Emissions From DOE Facilities

Routine research and development activities at US Department of Energy facilities can result in the release of radioactive emissions, potentially exposing the public and the environment. Such emissions are subject to certain Clean Air Act regulations, specifically those outlined in 40 CFR Part 61, Subpart H, which are enforced by the US Environmental Protection Agency. Compliance is determined in part with a dose standard. Doses to members of the public from most US Department of Energy facility airborne emissions are modeled using CAP-88 PC software, the latest version of which contains more than 1,200 radionuclides. Radioactive effluents from US Department of Energy facilities may contain radioisotopes that are not available in CAP-88 PC, and those radioisotopes must still be evaluated to determine whether doses to members of the public are below established limits. CAP-88 PC-omitted radionuclides can be accounted for using alternate methods, including the use of surrogate radionuclides. Here, this paper elucidates the process of accounting for CAP-88 PC-omitted radionuclides by providing criteria and rationale for surrogate selection, a compilation of surrogate radionuclides used in the past by US Department of Energy facilities, a discussion of alternate methods used to account for CAP-88 PC-omitted radionuclides and a comparison of methods and impacts on receptor doses. Ultimately, this paper aims to aid in the process of surrogate selection and consequently to simplify and expedite compliance with Clean Air Act regulations.

61 RADIATION PROTECTION AND DOSIMETRY↗

Transverse emittance growth due to rf noise in crab cavities: Theory, measurements, cure, and high luminosity LHC estimates

The High-Luminosity LHC (HL-LHC) upgrade with planned operation from 2029 onward has a goal of achieving a tenfold increase in the integrated number of recorded collisions thanks to a doubling of the intensity per bunch ( 2.2 × 10 11 protons) and a reduction of β * (the β value in the two high luminosity detectors, namely ATLAS and CMS) to 15 cm. Such an increase in recorded collisions would significantly expedite new discoveries and exploration. Crab cavities are an important component of the HL-LHC upgrade and will contribute strongly to achieving an increase in the number of recorded collisions. However, noise injected through the crab cavity radio frequency (rf) system could cause significant transverse emittance growth and limit luminosity lifetime. We presented a theoretical formalism relating transverse emittance growth to rf noise in an earlier work. In this follow-up paper, we summarize measurements in the super-proton synchrotron (SPS) at CERN that validate the theory, we present estimates of the emittance growth rates using state-of-the-art rf and low-level rf (LLRF) technologies, and we set the rf noise specifications to achieve acceptable performance. A novel dedicated feedback system acting through the crab cavities to mitigate emittance growth will be required. In this work, we develop a theoretical formalism to evaluate the performance of such a feedback system in any collider, identify limiting components, present simulation results to validate these studies, and derive key design parameters for an HL-LHC implementation of such a feedback system. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Self-selecting vapor growth of transition-metal-halide single crystals

Transition-metal halides can host a large variety of novel phenomena, such as magnetism in the monolayer limit, quantum spin liquid and spiral spin liquid states, topological magnons, and chiral phonons. Sizable high-quality single crystals are necessary for investigations of magnetic and lattice excitations by, for example, inelastic neutron scattering. In this paper, we review a less well-known vapor transport technique, self-selecting vapor growth, and report our growths of transition-metal halides using this technique. We report the growth and characterizations of sizable single crystals of α–RuCl 3 , CrCl 3 , Ru 1–x Cr x Cl 3 , and CrBr 3 . In order to expedite the conversion of starting powder to single crystals, we modified the technique by cooling the growth ampoule through an appropriate temperature range. Our work shows that the self-selecting vapor transport technique can provide large single crystals of transition-metal halides, demonstrating its potential for providing high-quality single crystals of quantum materials.

2-dimensional systems↗

Feedback-based quantum algorithm inspired by counterdiabatic driving

In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to iteratively construct quantum circuits. Here, we propose a substantial enhancement by implementing a protocol that uses ideas from quantum Lyapunov control and the counterdiabatic driving protocol, a key concept from quantum adiabaticity. Our approach introduces an additional control field inspired by counterdiabatic driving. We apply our algorithm to prepare ground states in one-dimensional quantum Ising spin chains. Comprehensive simulations demonstrate a remarkable acceleration in population transfer to low-energy states within a significantly reduced time frame compared to conventional feedback-based quantum algorithms. This acceleration translates to a reduced quantum circuit depth, a critical metric for potential quantum computer implementation. We validate our algorithm on the IBM cloud computer, highlighting its efficacy in expediting quantum computations for many-body systems and combinatorial optimization problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Generalized approach for rapid entropy calculation of liquids and solids

We build a comprehensive methodology for the fast computation of entropy across both solid and liquid phases. The proposed method utilizes a single trajectory of molecular dynamics (MD) to facilitate the calculation of entropy, which is composed of three components. The electronic entropy is determined through the temporal average acquired from density functional theory MD simulations. The vibrational entropy, typically the predominant contributor to the total entropy, even within the liquid state, is evaluated by computing the phonon density of states via the velocity autocorrelation function. The most arduous component to quantify, the configurational entropy, is assessed by probability analysis of the local structural arrangement and atomic distribution. We illustrate, through a variety of examples, that this method is both a versatile and valid technique for characterizing the thermodynamic states of both solids and liquids. Furthermore, this method is employed to expedite the calculation of melting temperatures, demonstrating its practical utility in computational thermodynamics.

36 MATERIALS SCIENCE↗