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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

Investigation of design principles for metal-binding and conductive protein assemblies

Throughout the lifetime of this initiative, including renewals, we focused on understanding the fundamental principles of protein-protein interface design that enable predictable and modular spatial and kinetic control of multi-component protein self-assembly in 1D, 2D, and 3D, including the interface with inorganic materials, small molecules, and metal ions. We designed individual protein components that bind specific metal ions, including REEs and transport ions across lipid membranes. We created helical 1D filaments of repeating units with programmed periodicity, pitch, and multi-component environmentally responsive self-assembling protein fibers. We showed that these filaments reversibly assemble and disassemble under specific pH conditions and created end-specific caps that independently tune the balance of attachment and detachment rates at each terminus of the filament. Using similar filaments, we succeeded in binding arrays of heme and chlorophyll molecules and assembling patterned helical coatings around carbon nanotubes in efforts to create de novo conductive nanowires. By arraying REE binding sites in a large circular tandem array with a repeat protein-based cyclic oligomer, we created a molecular scaffold for superradiance and paramagnetic quantum sensing. We created a range of one-component and two-component self-assembling 2D arrays and showed that when designed to engage cell receptors, these arrays can control cell behavior from outside the cell signal to inside the cell. We designed helical repeat proteins with variable lengths displaying charged residues in a pattern matched to the cation lattice of mica. achieved a range of ordered states with an epitaxial match to the underlying crystal lattice. We further applied the learned principles of protein-induced biomineralization to design proteins with an interface lattice matching CaCO 3 and guide the formation of specific crystal forms of CaCO 3 from solution, a significant advance toward the global need to manage carbon. In all cases of mineral lattice matching and biomineralization, we followed assembly using molecularly resolved in situ AFM imaging and extracted information about assembly pathways and energetics, applying deep learning to quantify the dynamics of protein self-organization. We developed techniques for using dynamic metal-dependent interfaces on protein nanopores for discriminatively sensing dilute REEs in solution and demonstrated the use of strong metal-binding interfaces to drive nanocage disassembly for conditional nanocompartmentalization applications. This grant supported 11 people, including Asim Bera, Evans Brackenbrough, Andrew Borst, Nikita Hanikel, Timothy Huddy, Emily Joyce, Alex Young-Seug Kang, Ryan Kibler, Joshua Morris Lubner, Harley Pyles, and Shuai Zhang. The research effort culminated in the production of published papers and theses. Electronic Thesis/Dissertation are distributed by ProQuest/UMI Dissertation Publishing and made available on an open access basis through UW Libraries ResearchWorks Service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fabrication of Self-Cleaning, Reusable Titania Templates for Nanometer and Micrometer Scale Protein Patterning

The photocatalytic self-cleaning characteristics of titania facilitate the fabrication of reuseable templates for protein nanopatterning. In this work, titania nanostructures were fabricated over square centimeter areas by interferometric lithography (IL) and nanoimprint lithography (NIL). With the use of a Lloyd’s mirror two-beam interferometer, self-assembled monolayers of alkylphosphonates adsorbed on the native oxide of a Ti film were patterned by photocatalytic nanolithography. In regions exposed to a maximum in the interferogram, the monolayer was removed by photocatalytic oxidation. In regions exposed to an intensity minimum, the monolayer remained intact. After exposure, the sample was etched in piranha solution to yield Ti nanostructures with widths as small as 30 nm. NIL was performed by using a silicon stamp to imprint a spin-cast film of titanium dioxide resin; after calcination and reactive ion etching, TiO 2 nanopillars were formed. For both fabrication techniques, subsequent adsorption of an oligo(ethylene glycol) functionalized trichlorosilane yielded an entirely passive, protein-resistant surface. Near-UV exposure caused removal of this protein-resistant film from the titania regions by photocatalytic degradation, leaving the passivating silane film intact on the silicon dioxide regions. Proteins labeled with fluorescent dyes were adsorbed to the titanium dioxide regions, yielding nanopatterns with bright fluorescence. Subsequent near-UV irradiation of the samples removed the protein from the titanium dioxide nanostructures by photocatalytic degradation facilitating the adsorption of a different protein. The process was repeated multiple times. These simple methods appear to yield durable, reuseable samples that may be of value to laboratories that require nanostructured biological interfaces but do not have access to the infrastructure required for nanofabrication.

36 MATERIALS SCIENCE↗

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quality and uptake of antenatal and postnatal care in Haiti

Background: Despite improvement, maternal mortality in Haiti remains high at 359/100,000 live births. Improving access to high quality antenatal and postnatal care has been shown to reduce maternal mortality and improve newborn outcomes. Little is known regarding the quality and uptake of antenatal and postnatal care among Haitian women. Methods: Exit interviews were conducted with all pregnant and postpartum women seeking care from large health facilities (n = 10) in the Nord and Nord-Est department and communes of St. Marc, Verrettes, and Petite Rivière in Haiti over the study period (March-April 2015; 3–4 days/facility). Standard questions related to demographics, previous pregnancies, current pregnancy, and services/satisfaction during the visit were asked. Total number of antenatal visits were abstracted from charts of recently delivered women (n = 1141). Provider knowledge assessments were completed by antenatal and postnatal care providers (n = 39). Frequencies were calculated for descriptive variables and multivariable logistic regression was used to explore predictors of receiving 5 out of 10 counseling messages among pregnant women. Results: Among 894 pregnant women seeking antenatal care, most reported receiving standard clinical service components during their visit (97% were weighed, 80% had fetal heart tones checked), however fewer reported receiving recommended counseling messages (44% counselled on danger signs, 33% on postpartum family planning). Far fewer women were seeking postnatal care (n = 63) and similar service patterns were reported. Forty-three percent of pregnant women report receiving at least 5 out of 10 counseling messages. Pregnant women on a repeat visit and women with greater educational attainment had greater odds of reporting having received 5 out of 10 counseling messages (2nd visit: adjusted odds ratio [aOR] =1.70, 95% confidence interval [CI]: 1.09–2.66; 5+ visit: aOR = 5.44, 95% CI: 2.91–10.16; elementary school certificate: aOR = 2.06, 95% CI: 1.17–3.63; finished secondary school or more aOR = 1.97, 95% CI = 1.05–3.02). Chart reviews indicate 27% of women completed a single antenatal visit and 36% completed the recommended 4 visits. Conclusions: Antenatal and postnatal care uptake in Haiti is sub-optimal. Despite frequent reports of provision of standard service components, counseling messages are low. Consistent provision of standardized counseling messages with regular provider trainings is recommended to improve quality and uptake of care in Haiti.

59 BASIC BIOLOGICAL SCIENCES↗

Oxide Semiconductor Sensors for Monitoring Advanced Energy Conversion and Manufacturing Processes at High Temperature

To optimize the operation and functionality of high temperature systems such as slagging gasifiers, coal boilers and glass/steel smelters, it is important to monitor temperature, corrosion and erosion of the refractory used in such systems. Both thermocouple and failure sensors (and arrays of these) would be useful to monitor the health of any refractory or coatings in these systems. Many of such type of sensors are installed into the systems through open access ports within the refractory; however, there are some disadvantages of this approach where corrosive/erosive gas and molten materials can penetrate and compromise the system. The current work presents the development and performance of refractory with embedded high temperature sensors such as thermocouples, thermistors, and various spallation/crack monitoring sensors, which may be used within a variety of refractory brick in different high temperature processes and applications. The objective of our work is to develop high-temperature sensors composed of electroceramic materials that are chemically stable at high temperatures (750°-1500°C) and high pressures (up to 1000 psi) that can be used in monitoring temperature, corrosion and erosion process in refractory used in high energy systems. The high-temperature sensors investigated in this work were composed of various oxide composites directly embedded into the refractory oxides. The composites used for this work were synthesized by a mixed-oxide route. Metal oxides were inserted within a matrix material composed of refractory oxides (Al2O3, ZrO2, etc.). The physical and electrical properties were specifically manipulated by altering the level of percolation of the conductive species (metal oxides) within the refractory constituent (refractory oxide). An example of one of these embedded sensors consisted of an electroceramic-based thermocouple fabricated with two separate oxide composite compositions which were patterned to produce a couple within the interior of a refractory matrix. The thermocouple successfully displayed thermoelectric voltage trend (as a function of temperature), and the voltage was 220.0 mV near 1400 °C. In addition, corrosion tests on the refractory embedded sensors were performed. To evaluate corrosion in the refractory was exposed to high-temperature glass compositions over a 90 h period. The penetration of the glass through the refractory could be monitored by both an amperometric and voltametric based sensor. With this experiment, it was demonstrated that the embedded sensor could dynamically monitor the corrosion process, and thus, provide real-time feedback on both temperature and the refractory health.

20 FOSSIL-FUELED POWER PLANTS↗

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates

Abstract The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli . We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

59 BASIC BIOLOGICAL SCIENCES↗

An On-Demand Electric Transit Case Study of New Rochelle, New York

Here, this article characterizes the performance and ridership patterns of an on-demand transit (ODT) service utilizing lightweight electric vehicles (EVs) in New Rochelle, New York. Ridership sociodemographics, travel patterns (both temporal and spatiotemporal), and energy use from the service were explored using travel and survey data from September 2019 through December 2023. The ODT service was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service was utilized primarily for short trips (86% under 2 mi), with approximately one-third of riders using the ODT service to connect to a train or bus. The costs associated with fueling/charging were compared for different types of fleet vehicles, and the small, right-sized EVs were found to have annual charging costs that were roughly half of the refueling costs for conventional hybrid vans, and 24 times lower than a fleet of diesel buses. Evaluating the vehicle fleet and mapping current socio-spatial travel demand can inform system performance, guide service area development, and support future planning such as expansion to nearby communities and transit hubs. The findings in this case study suggest that on-demand electric transit may be a significant and growing space for advancing highly valued public mobility services. Public transport interventions that consider right-sized, electric, on-demand vehicles can help improve mobility access and reduce energy use and refueling costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Erosion-Corrosion Detection in Carbon Steel Pipe Loops using SRNLs Thickness and Mass Loss Measurement Coupons - 20464

Structural health of waste transfer infrastructure is of utmost importance to DOE and communities surrounding their active sites. A Fitness-for-Service (FFS) program for the Waste Transfer System has been implemented by the US Department of Energy (DOE) for the purposes of evaluating and quantifying the degradation of critical components. Currently, the method of approach is to section and evaluate pipelines that have been removed at end service. In order to augment data collection methods applied to making lifespan estimates of waste transfer system components, Florida International University (FIU) has been investigating new-technology based strategies for quantifying the rate of degradation. Present research considers the option of a coupon system installed on a section of pipe at points of interest that will provide easy access to high resolution measurements of erosion/corrosion rates during operation. Researchers at Savannah River National Laboratory (SRNL) have developed this novel solution for in situ erosion and corrosion measurements in many applicable locations such as tanks, pipes, ducts, and injection points. The coupons are approximately 12.7 mm (1/2 inch) in diameter and 25.4 mm (1 inch) in length and can be placed in the pipe sections using Swagelok compression fittings. The coupon design allows for monitoring of the total degradation resulting from corrosion and erosion. High-resolution Ultrasonic Thickness (UT) testing allows in-situ monitoring of both degradation mechanisms. When removed from the system mass loss resulting from corrosion and erosion may also be evaluated. Experimental testing at FIU implemented the SRNL coupon system in a 6.10 meter (20 foot) pipe loop system comprised of 50.8 mm (2 inch) and 76.2 mm (3 inch) pipe sections in order to replicate expected use cases at the sites. Operational conditions were emulated by pumping abrasive materials through the pipeline at full capacity and collecting measurements from the SRNL coupons. Initial testing was conducted by circulating water followed by a mixture of sand and water for uniform wear rates. Thickness changes and mass loss were measured, and the surface exposed to the process fluid was observed for visual evidence of characteristic wear patterns resulting from an erosive environment. The test matrix consisted of several hours of operation and using fine, medium and coarse grain sands. Test results were analyzed to check for all three parameters (mass loss/gain, thickness change and surface patters) which could provide estimates of the remaining useful life of the pipe sections. Thus, the research presents the findings of this evaluation of the SRNL coupons as a means for conducting high accuracy, cost effective in-situ analysis of pipeline and waste transfer systems for erosion and corrosion susceptibility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possible design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.

97 MATHEMATICS AND COMPUTING↗

Substrate Engineered Interconnected Graphene Electrodes with Ultrahigh Energy and Power Densities for Energy Storage Applications

Supercapacitors combine the advantages of electrochemical storage technologies like high energy density batteries and high power density capacitors. At 5-10 W h Kg -1 , the energy densities of current supercapacitors are still significantly lower than energy densities of lead acid (20-35 W h Kg -1 ), Ni-metal hydride (40-100 W h Kg -1 ) and Li-ion (120-170 W h Kg -1 ) batteries. Recently, graphene based supercapacitors have shown energy density of 40-80 W h kg -1 . However, their performance is mainly limited due to the reversible agglomeration and restacking of individual graphene layers caused by π-π interactions. The restacking of graphene layers leads to significant decrease of ion-accessible surface area and the low capacitance of graphene based supercapacitors. Here, we introduce a microstructure substrate based method to produce fully delaminated and stable interconnected graphene structure using flash reduction of GO in a few seconds. With this structure, here we achieve the highest amount of volumetric capacitance obtained so far by any type of pure carbon based material. The affordable and scalable production method is capable of producing electrodes with energy density of 0.37 Wh cm -3 and power density of 416.6 W cm -3 . This electrode maintained more than 91 % of its initial capacitance after 5000 cycles. Moreover, combining with ionic liquid, this solvent free graphene electrode material is highly promising for on-chip electronics, micro supercapacitors as well as high power applications.

25 ENERGY STORAGE↗

Patterns of Care in Proton Radiation Therapy for Pediatric Central Nervous System Malignancies

Purpose: Proton beam therapy (PBT) potentially allows for improved sparing of normal tissues, hopefully leading to decreased late side effects in children. Using a national registry, we sought to perform a patterns-of-care analysis for children receiving PBT for primary malignancies of the central nervous system (CNS). Methods and Materials: Using the National Cancer Data Base, we identified pediatric patients with primary CNS malignancies that were diagnosed between 2004 and 2012. We used a standard t test for comparison of means and χ{sup 2} testing to identify differences in demographic and clinical characteristics. Univariate and multivariate logistical regression was applied to identify predictors of PBT use. Results: We identified 4637 pediatric patients receiving radiation therapy from 2004 to 2012, including a subset of 267 patients treated with PBT. We found that PBT use increased with time from <1% in 2004 to 15% in 2012. In multivariate logistical regression, we found the following to be predictors of receipt of PBT: private insurance, the highest income bracket, younger age, living in a metropolitan area, and residing >200 miles from a radiation treatment facility (P<.05). Conclusions: We noted the proportion of children receiving PBT to be significantly increasing over time from <1% to 15% from 2004 to 2012. We also observed important disparities in receipt of PBT based on socioeconomic status. Children from higher-income households and with private insurance were more likely to use this expensive technology. As we continue to demonstrate the potential benefits of PBT in children, efforts are needed to expand the accessibility of PBT for children of all socioeconomic backgrounds and regions of the country.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Building a road map for tailoring multilayer polyelectrolyte films

Researchers are moving a step closer to a definite road map for building layer-by-layer (LbL) assembled polyelectrolyte films, with the assistance of the Liquids Reflectometer at Oak Ridge National Laboratory's Spallation Neutron Source, in Oak Ridge, Tennessee. Scientists using the liquids reflectometer have successfully taken snapshots in close to real time of these multilayered structures for different applications when they modify the structure and function parameters. Polyelecrolytes are polymers that carry charge in aqueous solutions. They contain chemical groups that dissociate in water, making such polymers charged. Most polyelectrolytes are water soluble. They are important components in foods, soaps, shampoos, and cosmetics products. They show promise for such environmental work as oil recovery and water treatment. Polyelectrolytes are compelling because researchers can chemically modify how they interact with water for multiple applications. When two types of polyelectrolytes of opposite charge are assembled at a surface in a sequential way using the LbL assembly technique, 'the result is the forming of surface films, useful for coatings, biomedical implants and devices, controlling adhesion of biological molecules, and controlling delivery of therapeutic molecules from surfaces,' said Svetlana Sukhishvili of the Stevens Institute of Technology in New Jersey, the lead chemist on the collaboration. 'Medical doctors often prefer to deliver multiple therapeutic compounds from the coatings in a time-resolved manner,' Sukhishvili said. 'To assist them, material scientists need to learn how to build coatings in which polymer layering will not be compromised when exposed to normal physiological conditions.' 'Being able to control these properties, understanding how what you do to the materials affects their properties, this allows you to apply them to situations where interacting with an environment is very helpful, whether in a biological context or any other kind of water soluble context,' said John Ankner, lead instrument scientist for the Liquids Reflectometer. Ankner said that when several parameters are systematically altered, that allows researchers to map out the whole range of structures in the polymer. 'This work really sets a road map for how to get started with synthesizing polyelectrolyte materials for specific applications. Then, one can say, ok, this methylated material, the one that is 30% charged, is going to be what we want to use for a particular application.' The ORNL collaboration with the Stevens Institute has been conducting a series of experiments at the SNS to study layered film stratification in these polymers. Researchers stitch the polyelectrolyte chains in the LbL films together through what is called ionic pairing and arrange them within fuzzy, ultrathin layers that lie parallel to a solid surface substrate. Exposure of these films to aqueous solutions that contain salt (i.e., conditions that imitate real life) can compromise this film layering, as the salt ions act to weaken the ionic pairing that binds such layers together. So salt solutions are of key interest in studying how to make such layers for use in human applications. In the first research, Ankner, Sukhishvili and her student Li Xu looked at the effects of the layering of two types of LbL films of changing the charge density with a salt solution, and of blocking access to a charged site by nearby groups. The films were composed of positively charged variants of PDMA, a methyl polymer, and PDEA, an ethyl polymer. The other component of both systems is the ion exchanger polystyrene sulfonate (PSS) which features a fixed negative charge. First, a silicon substrate was dipped into solutions of PDMA and PDEA in dilute sodium chloride for a fixed time. Depending on the deposition time and the concentration of the solution, a nanometer-thick monolayer of the polymer adsorbs to the silicon surface. The film buildup is then continued by depositing a layer of PSS, and the cycle is repeated. The PDMA (methyl)/PSS and PDEA (ethyl)/PSS films were then annealed in varying concentrations of aqueous salt solutions. The chemists wanted to know if in these multi-layer cake-like assemblies, the structure can be systematically altered by varying the salt concentration, time in solution, and ultimately other environmental parameters, such as temperature or pH. Neutron reflectivity of the layered films exhibits the quality of the layering, in particular the concentration of the layers and how intermixed they are with adjacent layers. In this research, neutron reflectivity data from films built from 10%, 40%, and 100% charged PDMA or PDEA polyelectrolytes and 100% charged PSS were quantitatively compared to predicted, layered arrangements until the models produced reflectivity patterns matching those of the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks

Abstract Background Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from parallel sequencing provide available information about the affinity and accessibility of genome and are commonly used features in binding sites prediction. The attention mechanism in deep learning has shown its capability to learn long-range dependencies from sequential data, such as sentences and voices. Until now, no study has applied this approach in binding site inference from massively parallel sequencing data. The successful applications of attention mechanism in similar input contexts motivate us to build and test new methods that can accurately determine the binding sites of transcription factors. Results In this study, we propose a novel tool (named DeepGRN) for transcription factors binding site prediction based on the combination of two components: single attention module and pairwise attention module. The performance of our methods is evaluated on the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge datasets. The results show that DeepGRN achieves higher unified scores in 6 of 13 targets than any of the top four methods in the DREAM challenge. We also demonstrate that the attention weights learned by the model are correlated with potential informative inputs, such as DNase-Seq coverage and motifs, which provide possible explanations for the predictive improvements in DeepGRN. Conclusions DeepGRN can automatically and effectively predict transcription factor binding sites from DNA sequences and DNase-Seq coverage. Furthermore, the visualization techniques we developed for the attention modules help to interpret how critical patterns from different types of input features are recognized by our model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Indirect Validation of Probe Speed Data on Arterial Corridors

This study aimed to estimate the accuracy of probe speed data on arterial corridors on the basis of roadway geometric attributes and functional classification. It was assumed that functional class (medium and low) along with other road characteristics (such as weighted average of the annual average daily traffic, average signal density, average access point density, and average speed) were available as correlation factors to estimate the accuracy of probe traffic data. This study tested these factors as predictors of the fidelity of probe traffic data by using the results of an extensive validation exercise. This study showed strong correlations between these geometric attributes and the accuracy of probe data when they were assessed by using average absolute speed error. Linear models were regressed to existing data to estimate appropriate models for medium- and low-type arterial corridors. The proposed models for medium- and low-type arterials were validated further on the basis of the results of a slowdown analysis. These models can be used to predict the accuracy of probe data indirectly in medium and low types of arterial corridors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values

About 80 % of the precipitation at the Colorado River's headwaters is snow, and the resulting snowmelt-driven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the high-elevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of high-elevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths.

54 ENVIRONMENTAL SCIENCES↗

XFEL structures of the human MT2 melatonin receptor reveal the basis of subtype selectivity

The human MT 1 and MT 2 melatonin receptors are G-protein-coupled receptors (GPCRs) that help to regulate circadian rhythm and sleep patterns. Drug development efforts have targeted both receptors for the treatment of insomnia, circadian rhythm and mood disorders, and cancer, and MT 2 has also been implicated in type 2 diabetes. Here in this paper we report X-ray free electron laser (XFEL) structures of the human MT 2 receptor in complex with the agonists 2-phenylmelatonin (2-PMT) and ramelteon6 at resolutions of 2.8 Å and 3.3 Å, respectively, along with two structures of function-related mutants: H208 5.46 A (superscripts represent the Ballesteros–Weinstein residue numbering nomenclature7) and N86 2.50 D, obtained in complex with 2-PMT. Comparison of the structures of MT 2 with a published structure of MT 1 reveals that, despite conservation of the orthosteric ligand-binding site residues, there are notable conformational variations as well as differences in [ 3 H]melatonin dissociation kinetics that provide insights into the selectivity between melatonin receptor subtypes. A membrane-buried lateral ligand entry channel is observed in both MT 1 and MT 2 , but in addition the MT 2 structures reveal a narrow opening towards the solvent in the extracellular part of the receptor. We provide functional and kinetic data that support a prominent role for intramembrane ligand entry in both receptors, and suggest that there might also be an extracellular entry path in MT 2 . Our findings contribute to a molecular understanding of melatonin receptor subtype selectivity and ligand access modes, which are essential for the design of highly selective melatonin tool compounds and therapeutic agents.

59 BASIC BIOLOGICAL SCIENCES↗