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At least 487 records · Page 27

Linear-scaling implementation of the direct random-phase approximation

We report the linear-scaling implementation of the direct random-phase approximation (dRPA) for closed-shell molecular systems. As a bonus, linear-scaling algorithms are also presented for the second-order screened exchange extension of dRPA as well as for the second-order Møller–Plesset (MP2) method and its spin-scaled variants. Our approach is based on an incremental scheme which is an extension of our previous local correlation method [Rolik et al., J. Chem. Phys. 139, 094105 (2013)]. The approach extensively uses local natural orbitals to reduce the size of the molecular orbital basis of local correlation domains. In addition, we also demonstrate that using natural auxiliary functions [M. Kállay, J. Chem. Phys. 141, 244113 (2014)], the size of the auxiliary basis of the domains and thus that of the three-center Coulomb integral lists can be reduced by an order of magnitude, which results in significant savings in computation time. The new approach is validated by extensive test calculations for energies and energy differences. Our benchmark calculations also demonstrate that the new method enables dRPA calculations for molecules with more than 1000 atoms and 10 000 basis functions on a single processor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Remote Sensing Program

Field spectroradiometric and airborne multispectral scanner data were related to vineyard yield and other agronomic variables in an attempt to determine the optimum wavelengths for yield prediction modeling. Reflections between vine canopy reflectance and several management practices were also considered. Spectral analysis of test vines found that, although some correlations with vine yield were significant, they were inadequate for producing a yield prediction model. The findings also indicate that the vines examined through the field spectroradiometers were not truly representative. Geologic linears identified from aerial photographys, LANDSAT images, and maps were compared to gas well locations in three New York' counties. Correlations were found between the dominant trends in regional liners and gas field boundaries and trends. Other projects being conducted under the grant include determining vegetable acreage in mucklands, site selection for windmills, spectral effects of sulfur dioxide, and screening tomato seedlings for salt tolerance.

Philipson, W. R.↗

Development of a photovoltaic module qualification test based on combined-environment accelerated stress data

The U.S. Coast Guard has developed a qualification test to screen photovoltaic modules for utilization on marine aids to navigation. The test is based on a combined-environment of hot and cold saltwater immersion and air pressurization. The test has demonstrated a very high acceleration factor and excellent correlation of electrical failures with modules in a concurrent real-time marine exposure.

Trenchard, S. E.↗

The Autonomic Symptom Profile: a new instrument to assess autonomic symptoms

OBJECTIVE: To develop a new specific instrument called the Autonomic Symptom Profile to measure autonomic symptoms and test its validity. BACKGROUND: Measuring symptoms is important in the evaluation of quality of life outcomes. There is no validated, self-completed questionnaire on the symptoms of patients with autonomic disorders. METHODS: The questionnaire is 169 items concerning different aspects of autonomic symptoms. The Composite Autonomic Symptom Scale (COMPASS) with item-weighting was established; higher scores indicate more or worse symptoms. Autonomic function tests were performed to generate the Composite Autonomic Scoring Scale (CASS) and to quantify autonomic deficits. We compared the results of the COMPASS with the CASS derived from the Autonomic Reflex Screen to evaluate validity. RESULTS: The instrument was tested in 41 healthy controls (mean age 46.6 years), 33 patients with nonautonomic peripheral neuropathies (mean age 59.5 years), and 39 patients with autonomic failure (mean age 61.1 years). COMPASS scores correlated well with the CASS, demonstrating an acceptable level of content and criterion validity. The mean (+/-SD) overall COMPASS score was 9.8 (+/-9) in controls, 25.9 (+/-17.9) in the patients with nonautonomic peripheral neuropathies, and 52.3 (+/-24.2) in the autonomic failure group. Scores of symptoms of orthostatic intolerance and secretomotor dysfunction best predicted the CASS on multiple stepwise regression analysis. CONCLUSIONS: We describe a questionnaire that measures autonomic symptoms and present evidence for its validity. The instrument shows promise in assessing autonomic symptoms in clinical trials and epidemiologic studies.

NASA Discipline Cardiopulmonary↗

Integrated Component-Specific Measurements to Develop Emission Factors for Compressors and Gas Gathering Lines

The Department of Energy (DOE) National Energy Technology Laboratory (NETL) and other critical stakeholders (e.g., U.S. Environmental Protection Agency (USEPA), state regulators, and industry) seek to more accurately characterize and quantify methane emissions from compressors and gathering lines within the Gathering and Boosting (G&B) segment of the natural gas system network. These efforts will reduce uncertainties in emissions estimates in USEPA’s current Green House Gas Inventory (GHGI) under their Greenhouse Gas Reporting Program (GHGRP). For this study, four G&B stations in the Gulf Coast Area were visited four times over the course of one year. Components were classified according to equipment and component type and emissions from select components were measured using multiple measurement technologies. The following major equipment types were considered: i) compressors, ii) separators, iii) dehydrators, iv) coalescers, v) slug catchers, vi) yard piping, vii) tanks, and viii) gathering lines. Individual components on each equipment type were further divided into the following main categories: i) connectors, ii) valves, iii) pressure relief valves (PRV), iv) meters, v) gauges, vi) regulators, vii) pneumatic device vents, and viii) compressor vents (e.g., distance piece vents [DPVs] and rod packing vents [RPVs]). Components were screened for the presence of leaks and venting emissions with an optical gas imaging (OGI) camera, and methane emission rates were measured using a microdilution high volume sampler. Downwind emissions were measured using an Open Path Fourier Transform Infrared (OP-FTIR) Spectrometer. Data were evaluated to assess correlation with site, equipment, time, and operational variables. Key findings and recommendations from the study include: A) Different counting methodologies can result in vastly different component counts, thus influencing total emissions calculations using Subpart W population EFs. A standard methodology should be adopted for classifying and counting components in order to minimize inconsistencies across studies and instruct stakeholders responsible for GHGI reporting. B) Results support current component subcategories listed in USEPA Subpart W, including the subdivision of connectors (flanged and “other”) and pneumatic device vents (intermittent, continuous low bleed, and continuous high bleed). C) Emission rates vary across sites and a relationship between higher emissions and compressor age was observed for some components. D) Component emission rates varied between field campaigns. The type of components contributing to overall measured emissions also varied among field campaigns. However, the emission rate variability was larger between different components (of the same category) than the variability in one component over the four field campaigns. Therefore, when calculating emission factors, it is not necessary to take repeat measurements to capture component variability. E) Measuring the emission rate of a sample for an extended period of time is not necessary to capture the average component emission rate. F) For reporting purposes, excluding liquid lines from site-wide screening may have a negligible effect on component-related emissions. However, from a site management perspective, malfunctioning components were not uncommon on liquid lines and contributed substantially to fugitive emissions at some sites. G) Population EFs, whether including or excluding liquid lines, were a conservative estimate of fugitive emissions. Leaker EFs consistently underestimated emissions at the field sites. Measurements at more sites, particularity sites in other areas of the country, need to be completed before determining the accuracy of EFs.

03 NATURAL GAS↗

Alginate based 3D hydrogels as an in vitro co-culture model platform for the toxicity screening of new chemical entities

Prediction of human response to potential therapeutic drugs is through conventional methods of in vitro cell culture assays and expensive in vivo animal testing. Alternatives to animal testing require sophisticated in vitro model systems that must replicate in vivo like function for reliable testing applications. Advancements in biomaterials have enabled the development of three-dimensional (3D) cell encapsulated hydrogels as in vitro drug screening tissue model systems. In this study, we have developed an in vitro platform to enable high density 3D culture of liver cells combined with a monolayer growth of target breast cancer cell line (MCF-7) in a static environment as a representative example of screening drug compounds for hepatotoxicity and drug efficacy. Alginate hydrogels encapsulated with serial cell densities of HepG2 cells (10{sup 5}-10{sup 8} cells/ml) are supported by a porous poly-carbonate disc platform and co-cultured with MCF-7 cells within standard cell culture plates during a 3 day study period. The clearance rates of drug transformation by HepG2 cells are measured using a coumarin based pro-drug. The platform was used to test for HepG2 cytotoxicity 50% (CT{sub 50}) using commercially available drugs which further correlated well with published in vivo LD{sub 50} values. The developed test platform allowed us to evaluate drug dose concentrations to predict hepatotoxicity and its effect on the target cells. The in vitro 3D co-culture platform provides a scalable and flexible approach to test multiple-cell types in a hybrid setting within standard cell culture plates which may open up novel 3D in vitro culture techniques to screen new chemical entity compounds. - Graphical abstract: Display Omitted Highlights: > A porous support disc design to support the culture of desired cells in 3D hydrogels. > Demonstrated the co-culture of two cell types within standard cell-culture plates. > A scalable, low cost approach to toxicity screening involving multiple cell types.

60 APPLIED LIFE SCIENCES↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

Applying Shannon's information theory to bacterial and phage genomes and metagenomes

All sequence data contain inherent information that can be measured by Shannon’s uncertainty theory. Such measurement is valuable in evaluating large data sets, such as metagenomic libraries, to prioritize their analysis and annotation, thus saving computational resources. Here, Shannon’s index of complete phage and bacterial genomes was examined. The information content of a genome was found to be highly dependent on the genome length, GC content, and sequence word size. In metagenomic sequences, the amount of information correlated with the number of matches found by comparison to sequence databases. A sequence with more information (higher uncertainty) has a higher probability of being significantly similar to other sequences in the database. Measuring uncertainty may be used for rapid screening for sequences with matches in available database, prioritizing computational resources, and indicating which sequences with no known similarities are likely to be important for more detailed analysis.

59 BASIC BIOLOGICAL SCIENCES↗

A systematic decision-making methodology to formalize the selection of degree of realism in screening analysis of probabilistic risk assessment

In the nuclear power domain, Probabilistic Risk Assessment (PRA) is used to inform decision-making for Nuclear Power Plants (NPPs). Recently, there has been an increase in the utilization of modeling and simulation (M&S) to support the estimation of PRA inputs. Risk analysts should carefully select the PRA items that require M&S and their degree of realism (DoR) with consideration of the required resources. To support this selection, this article formulates a systematic decision-making approach for the DoR selection. The DoR selection is made based on two predictive decision-making attributes: the predicted differences in safety risk estimate (ΔSaRi) and the cost of analysis (ΔCAN). This research also develops and quantifies causal models to estimate ΔSaRi and ΔCAN. The causal model-based prediction of ΔSaRi and ΔCAN helps reduce the trial-and-error nature of the DoR selection in the PRA screening analysis and provides insights for DoR selection and the gradual refinements of PRA realism. This approach is demonstrated for a case study on fire PRA of NPPs, where an adequate DoR is selected from two fire models: an engineering correlation and a zone model.

Alkhatib, Sari [Department of Nuclear, Plasma, and↗

Thin Film Approaches to the SRF Cavity Problem Fabrication and Characterization of Superconducting Thin Films

Superconducting Radio Frequency (SRF) cavities are responsible for the acceleration of charged particles to relativistic velocities in most modern linear accelerators, such as those employed at high-energy research facilities like Thomas Jefferson National Laboratory’s CEBAF and the LHC at CERN. Recognizing SRF as primarily a surface phenomenon enables the possibility of applying thin films to the interior surface of SRF cavities, opening a formidable tool chest of opportunities by combining and designing materials that offer greater performance benefit. Thus, while improvements in radio frequency cavity design and refinements in cavity processing techniques have improved accelerator performance and efficiency – 1.5 GHz bulk niobium SRF cavities have achieved accelerating gradients in excess of 35 MV/m – there exist fundamental material bounds in bulk superconductors limiting the maximally sustained accelerating field gradient (≈ 45 MV/m for Nb) where inevitable thermodynamic breakdown occurs. With state of the art Nb based cavity design fast approaching these theoretical limits, novel material innovations must be sought in order to realize next generation SRF cavities. One proposed method to improve SRF performance is to utilize thin film superconducting-insulating-superconducting (SIS) multilayer structures to effectively magnetically screen a bulk superconducting layer such that it can operate at higher field gradients before suffering critically detrimental SRF losses. This dissertation focuses on the production and characterization of thin film superconductors for such SIS layers for radio frequency applications. Correlated studies on structure, surface morphology and superconducting properties of epitaxial Nb and MgB2 thin films are presented.

Beringer, Douglas↗

Descriptors for Cu facets for CO2 reduction reaction activity

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO2R) reduction to valuable hydrocarbons and oxygenates. Herein, leveraging density functional theory calculations of the CO adsorption energy ΔE_CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE_CO and the recently experimentally measured CO2R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining the ab initio thermodynamics of the early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically preferred step, and notably shows a volcano trend with the experimental currents where the maximum CO2R current corresponds to the moderate CHO* formation energy. Importantly, we show that increasing the step and kink density of the Cu termination not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. We also explain why (741) is exceptional with high CO2R activity as measured experimentally due to its relatively low activity toward the hydrogen evolution reaction compared with the other Cu surfaces. Beyond the general CO adsorption energy that only shows a linear trend with CO2R activity, we show that the reaction CO* → CHO* free energy is a descriptor that displays a volcano relationship with the overall CO2R activity on Cu facets.

machine learning↗

Applications of Landsat imagery to a coastal inlet stability study

Polcyn and Lyzenga (1975) and Middleton and Barber (1976) have demonstrated that it is possible to correlate the radiance values of a multispectral imagery, such as Landsat imagery, with the depth related information. The present study is one more example of such an effort. Two sets of Landsat magnetic tape were obtained and displayed on the screen of an Image-100 computer. Spectral analysis was performed to produce various signatures, their extent, and location. Subsequent ground truth observations and measurements were gathered by means of hydrographic surveys and low altitude aerial photographs for interpretation and calibration of the Landsat data. Finally, a coastal engineering assessment based on the Landsat data was made. Recommendations regarding the navigational canal alignment and dredging practice are presented in the light of inlet stability.

Wang, Y.-H.↗

Selection for optimal crew performance - Relative impact of selection and training

An empirical study supporting Helmreich's (1986) theoretical work on the distinct manner in which training and selection impact crew coordination is presented. Training is capable of changing attitudes, while selection screens for stable personality characteristics. Training appears least effective for leadership, an area strongly influenced by personality. Selection is least effective for influencing attitudes about personal vulnerability to stress, which appear to be trained in resource management programs. Because personality correlates with attitudes before and after training, it is felt that selection may be necessary even with a leadership-oriented training cirriculum.

Chidester, Thomas R.↗

Using first-principles calculations to screen for fragile magnetism: Case study of LaCrGe 3 and LaCrSb 3

In this study, we present a coupled experimental/theoretical investigation of pressure effect on the ferromagnetism of LaCrGe 3 and LaCrSb 3 compounds. The magnetic, electronic, elastic, and mechanical properties of LaCrGe 3 and LaCrSb 3 at ambient condition are studied by first-principles density-functional theory calculations. The pressure dependences of the magnetic properties of LaCrGe 3 and LaCrSb 3 are also investigated. The ferromagnetism in LaCrGe 3 is rather fragile, with a ferro- to paramagnetic transition at a relatively small pressure (around 7 GPa from our calculations, and 2 GPa in experiments). The key parameter controlling the magnetic properties of LaCrGe 3 is found to be the proximity of the peak of Cr density of states to the Fermi level, a proximity that is strongly correlated with the distance between Cr atoms along the c axis, suggesting that there would be a simple way to suppress magnetism in systems with one-dimensional arrangement of magnetic atoms. By contrast, the ferromagnetism in LaCrSb 3 is not fragile. In conclusion, our theoretical results are consistent with our experimental results and demonstrate the feasibility of using first-principles calculations to aid experimental explorations in screening for materials with fragile magnetism.

36 MATERIALS SCIENCE↗

Correlated Response of Protein Side-Chain Fluctuations and Conformational Entropy to Ligand Binding

The heterogeneous fast side-chain dynamics of proteins plays crucial roles in molecular recognition and binding. Site-specific NMR experiments quantify these motions by measuring the model-free order parameter (O axis 2 ) on a scale of 0 (most flexible) to 1 (least flexible) for each methyl-containing residue of proteins. In this work, we have examined ligand-induced variations in the fast side-chain dynamics and conformational entropy of calmodulin (CaM) using five different CaM–peptide complexes. O axis 2 of CaM in the ligand-free (O axis,U 2 ) and ligand-bound (O axis,B 2 ) states are calculated from molecular dynamics trajectories and conformational energy surfaces obtained using the adaptive biasing force (ABF) method. ΔO axis 2 = O axis,B 2 – O axis,U 2 follows a Gaussian-like unimodal distribution whose second moment is a potential indicator of the binding affinity of these complexes. The probability for the binding-induced O axis,U 2 → O axis,B 2 transition decreases with increasing magnitude of ΔO axis 2 , indicating that large flexibility changes are improbable for side chains of CaM after ligand binding. A linear correlation established between ΔOaxis2 and the conformational entropy change of the protein makes possible the determination of the conformational entropy of binding of protein–ligand complexes. The results not only underscore the functional importance of fast side-chain fluctuations but also highlight key motional and thermodynamic correlates of protein–ligand binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metabolomic Profiling of Wild-type and Mutant Soybean Root Nodules Using Laser-ablation Electrospray Ionization Mass Spectrometry Reveals Altered Metabolism

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is complex. In order to document the changes in plant metabolism due to the symbiosis, we utilized laser ablation electrospray ionization mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have altered nodule ultrastructure. Results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid (JA), correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+) and ineffective (nifH mutant, fix-) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. This study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Agtuca, Beverly J.↗

Genotypic variation in aluminum resistance, cellular aluminum fractions, callose and pectin formation and organic acid accumulation in roots of Populus hybrids

Soil acidity and aluminum (Al) toxicity are major factors limiting crop yield and forest productivity worldwide. Hybrid poplar (Populus spp.) was used as a model to assess genotypic variation in Al resistance and physiological stress responses to Al in a woody tree species. Eight hybrid crosses of P. trichocarpa, P. deltoides and P. nigra were exposed to Al in solution culture. Resistance to Al varied by genotype and hybrid cross, with P. trichocarpa x P. deltoides crosses being most resistant, P. trichocarpa x P. nigra being intermediate and P. deltoides x P. nigra being most sensitive to Al. Total root Al accumulation was not a good indicator of Al resistance/sensitivity. However, the partitioning of Al into apoplastic and symplastic fractions indicated that differences in sensitivity among genotypes were associated with Al uptake into the symplasm. Aluminum treatment increased callose and pectin concentrations of root tips in all genotypes, but more prominently in Al sensitive genotypes/hybrids. In Al sensitive genotypes, higher levels of symplastic Al accumulation correlated with elevated concentrations of citrate, malate, succinate or formate in root tips, whereas organic acid accumulation was not as pronounced in Al resistant genotypes. These findings suggest that exclusion of Al from the symplast is associated with Al resistance. Further screening of Al tolerant poplar genotypes could yield successful candidates to be utilized for sustainable reforestation/reclamation and carbon sequestration projects where soil acidity may limit tree growth.

54 ENVIRONMENTAL SCIENCES↗

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗