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At least 919 records · Page 51

INSPIRE Phase I Development

Sandia National Laboratories (Sandia) and Makel Engineering, Inc developed a pathway towards an advanced multi-modal sensor system suitable for in-situ analysis of exhaled volatile organic compounds (VOCs) for pilots, divers and field patients. Our proposed In-Mask Sensors for Physiological Investigation of Respiratory Exhalation - INSPIRE, will combine micro-gas chromatograph (microGC) and miniature ion mobility spectrometer (IMS) for detection of trace amounts of exhaled breath VOCs with miniature solid state sensors for inorganic compounds found in breath such as oxygen, carbon dioxide, moisture and the inert gases nitrogen, argon and helium. To develop clear developmental pathway towards that goal Sandia demonstrated a new version of its ion-mobility spectrometer detection technology for VOC detection, while Makel demonstrated detection of inorganics and concepts for mask integration. Sandia demonstrated detection of many compounds from the EPA TO-15 Test Mixture, which is representative of many classes of compounds found in air, and can be purchased as a gas standard from a variety of suppliers. The work demonstrated for phase I was sufficient to move the team into phase II of the program, where a full prototype unit will be developed. This CRADA provided clear value to the taxpayer by allowing a US small business to continue to phase II of a competitive STTR proposal for the Air Force. This process will help to transition Sandia’s technology into the marketplace to address a clear DoD requirement.

Moorman, Matthew↗

Online Alpha Monitoring of High Cs-137 Hanford and SRS High Level Waste with Tensioned Metastable Fluid Detectors

The Department of Energy’s Hanford and Savannah River Sites maintain millions of gallons of caustic supernate and salt high activity waste in their high-level waste (HLW) tank farm inventories. The Savannah River Site is currently treating this waste with a calixarene-based solvent extraction of Cs-137 to reduce these inventories. Hanford is employing an at-tank crystalline silico titanate (CST) based solid phase extraction methodology to reduce their liquid HLW inventories. Due to the high solubility of Cs-137 and the relative insolubility of the actinides in these caustic waste forms, the beta to alpha radioactivity ratio can often exceed six orders of magnitude in the feed solutions to these treatment processes. This unique characteristic leads to significant technical challenges in making rapid gross alpha measurements in the presence of the overwhelming beta, gamma, as well as dissolved sodium salt in these HLW matrices. Conventional radioanalytical techniques, such as liquid scintillation analysis or gas flow proportional counting require significant radiochemistry preparation prior to the radiometric measurements for gross alpha activity. These required pretreatments render these technologies untenable for rapid quantification of gross alpha activity that could be required to support on or at-line measurements ensuring a waste stream will meet regulatory requirements. The radiation measurement properties of Tensioned Metastable Fluid Detectors (TMFDs) have been studied by Purdue University’s Taleyarkhan research group for well over a decade. Fluids tensioned to the appropriate degree will rupture when struck by radiation, resulting in a measurable cavitation event. The negative pressure generating this tension can be adjusted by centrifugal rotation or by acoustic means in such a way that these cavitation events can be generated from alpha radiation but will not be generated by beta or gamma radiation. Purdue University and the Savannah River National Laboratory are currently collaborating to develop a gamma/beta blind, spectroscopic alpha measurement system based on the Tensioned Metastable Fluid Detector technology to provide a potential solution for performing rapid gross alpha measurements on these high gamma/beta sample matrices. Measurements using the Indirect Drive Acoustically Tensioned Metastable Fluid Detectors developed as part of this collaboration were performed with an alpha emitting radionuclide. Successful determination of gross alpha activity was observed, indicating a potential pathway for rapid gross alpha measurements in remote-handled shielded cells or in process situations requiring online alpha monitoring. Measurements using this system have been conducted on high beta activity solutions, demonstrating the beta blind capability of this system. Measurements are currently underway to test the system’s capability to measure gross alpha activity on Savannah River Site high level waste high Cs-137 samples that have been measured by the SRNL radiochemistry team. This work was supported by the DOE EM Technology Development program.

DiPrete, David [Savannah River National Laboratory↗

Volumetric Additive Manufacturing of Dormant Catalytic Chemistries to Generate Silicone Micro‐ and Millifluidic Devices and Instant Molds

Tomographic volumetric additive manufacturing (T‐VAM) rapidly prints solid objects within minutes, accessing photochemistries that are traditionally challenging for layer‐based additive manufacturing methods. This includes high‐viscosity materials, air‐free chemistries, and solid‐state systems. Catalytic chemistries are appealing as a pathway to engineering advanced materials, including tough thermosets, silicone elastomers, and complex block copolymers. However, photoactivated dormant catalytic chemistries, where the catalyst irreversibly activates upon exposure to light, are incompatible with typical tomographic VAM approaches. To address this limitation, a zero‐dose optimization strategy is devised to preserve dormant catalysts in desired regions by keeping them unexposed to light. VAM printed micro‐ and millifluidic devices and instant molds are successfully produced within minutes in silicones polymerized using photoactivated dormant platinum photohydrosilylation catalysts. The printed channels are programmed to be 500 and 2500 µm for the micro‐ and millifluidic devices, and print fidelity is assessed by X‐ray computed tomography. This work demonstrates the potential of zero‐dose optimization to expand the range of chemistries accessible for VAM, enabling the rapid fabrication of complex devices.

Additive Manufacturing↗

Programming Amphiphilic Peptoid Oligomers for Hierarchical Assembly and Inorganic Crystallization

Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-D-201-03: During-Treatment Delivery Monitoring System for TomoTherapy

Purpose: Multiple error pathways can lead to delivery errors during the treatment course that cannot be caught with pre-treatment QA. While in vivo solutions are being developed for linacs, no such solution exists for tomotherapy. The purpose of this study is to develop a near real-time system for tomotherapy that can monitor the delivery and dose accumulation process during the treatment-delivery, which enable the user to assess the impact of delivery variations and/or errors and to interrupt the treatment if necessary. Methods: A program running on a tomotherapy planning station fetches the raw DAS data during treatment. Exit detector data is extracted as well as output, gantry angle, and other machine parameters. For each sample, the MLC open-close state is determined. The delivered plan is compared with the original plan via a Monte Carlo dose engine which transports fluence deviations from a pre-treatment Monte Carlo run. A report containing the difference in fluence, dose and DVH statistics is created in html format. This process is repeated until the treatment is completed. Results: Since we only need to compute the dose for the difference in fluence for a few projections each time, dose with 2% statistical uncertainty can be computed in less than 1 second on a 4-core cpu. However, the current bottleneck in this near real-time system is the repeated fetching and processing the growing DAS data file throughout the delivery. The frame rate drops from 10Hz at the beginning of treatment to 5Hz after 3 minutes and to 2Hz after 10 minutes. Conclusion: A during-treatment delivery monitor system has been built to monitor tomotherapy treatments. The system improves patient safety by allowing operators to assess the delivery variations and errors during treatment delivery and adopt appropriate actions.

60 APPLIED LIFE SCIENCES↗

Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland

Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. We could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.

97 MATHEMATICS AND COMPUTING↗

Analysis of Natural Gas Fuel Cell Plant Configurations (Rev. 1)

This report presents the results of an updated Pathway Study for natural gas fueled, fuel cell (NGFC) power systems with carbon capture and storage (CCS). The results quantify the performance and cost benefits for a series of projected gains made through the development of advances in the component technologies or improvements in plant operation and maintenance. The results represent the potential future benefits of NGFC technology development. They also provide DOE with a basis to select the most appropriate development path for NGFC, and to measure and prioritize the contribution of its R&D program to future power systems technology.

03 NATURAL GAS↗

CO2 Reduction on Supported Ru/Al2O3 Catalysts: Cluster Size Dependence of Product Selectivity

The catalytic performance of a series of Ru/Al2O3 catalysts with Ru content in the 0.1-5% range was examined in the reduction of CO2 with H2. At low Ru loadings (≤0.5 %) where the active metal phase is highly dispersed (mostly atomically) on the alumina support CO is formed with high selectivity. With increasing metal loading the selectivity toward CH4 formation increases, while that for CO production decreases. In the 0.1% Ru/Al2O3 catalyst Ru is mostly present in atomic dispersion as STEM images obtained from the fresh sample prior to catalytic testing reveal. STEM images recorded form this same sample following temperature programmed reaction test clearly show the agglomeration of small metal particles (and atoms) into 3D clusters. The clustering of the highly dispersed metal phase is responsible for the observed dramatic selectivity change during elevated temperature tests: dramatic decrease in CO, and large increase in CH4 selectivity. Apparent activation energies, estimated from the slopes of Arrhenius plots, of 82 kJ/mol and 62 kJ/mol for CO and CH4 formation were determined, respectively, regardless of Ru loading. These results suggest that the formation of CO and CH4 follow different reaction pathways, or proceed on active centers of different nature. Reactions with CO2/H2 and CO/H2 mixtures (under otherwise identical reaction conditions) reveal that the onset temperature of CO2 reduction is about 150 ºC lower than of CO reduction. We thank Dr. Feng Gao for carrying out the H2 chemisorption measurements on all the Ru/Al2O3 catalysts discussed in this work. The catalyst preparation and catalytic measurements were supported by a Laboratory Directed Research and Development (LDRD) project, while the TEM work was supported by the Chemical Imaging Initiative at the Pacific Northwest National Laboratory (PNNL). PNNL is operated for the US Department of Energy by Battelle under contract number DE-AC05-76RL01830. JHK also acknowledges the support of this work by the 2013 Research Fund of UNIST (Ulsan National Institute of Science and Technology, Ulsan, Korea).

CO/CH4 selectivity↗

Role of oligomer structures in the surface chemistry of amidinate metal complexes used for atomic layer deposition of thin films

The beginning steps of the thermal chemistry of Cu(I)-2-(tert-butylimino)-5,5-dimethyl-pyrrolidinate on metal surfaces were characterized using temperature-programmed desorption experiments and density functional theory (DFT). The relative stability of the initial dimer relative to its dissociation on metal surfaces was evaluated. Several molecular desorption temperatures were identified on Ni(110), but all correspond to dimers, either containing the initial Cu ions or after their removal; no monomer was ever detected. DFT calculations also indicated preferential bonding on Cu(110) as a dimer, albeit with a distorted configuration, via the Cu atoms and in registry with the lattice of the substrate. Furthermore, a potential dissociation pathway of the adsorbed dimer was identified involving the partial detachment of the ligands via the scission of one Cu–N bond at the time and migration to adjacent surface sites. This process is accompanied by the reduction of the Cu centers of the metal–organic complex, indicating that it may be the rate-limiting reaction that leads to further fragmentation of the ligands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Life-cycle analysis of energy use, greenhouse gas emissions, and water consumption in the 2016 MYPP algal biofuel scenarios

The Department of Energy (DOE) Bioenergy Technologies Office (BETO) Multi-year Program Plan (MYPP) describes the bioenergy objectives pursued by BETO, the strategies for achieving those objectives, the current state of technology (SOT), and a number of design cases that explore cost and operational performance required to advance the SOT towards middle and long term goals (MYPP, 2016). Two options for converting algae to biofuel intermediates were considered in the MYPP, namely algal biofuel production via lipid extraction and algal biofuel production by thermal processing. The first option, lipid extraction, is represented by the Combined Algae Processing (CAP) pathway in which algae are hydrolyzed in a weak acid pretreatment step. The treated slurry is fermented for ethanol production from sugars. The fermentation stillage contains most of the lipids from the original biomass, which are recovered through wet solvent extraction. The process residuals after lipid extraction, which contain much of the original mass of amino acids and proteins, are directed to anaerobic digestion (AD) for biogas production and recycle of N and P nutrients. The second option, thermal processing, comprises direct hydrothermal liquefaction (HTL) of the wet biomass, separation of aqueous, gas, and oil phases, and treatment of the aqueous phase with catalytic hydrothermal gasification (CHG) to produce biogas and to recover N and P nutrients. The present report describes a life cycle analysis of energy use and greenhouse gas (GHG) emissions of the CAP and HTL options for the three scenarios just described. Water use is also reported. Water use during algal biofuel production comes from evaporation during cultivation, discharge to bleed streams to control pond salinity (“blowdown”), and from use during preprocessing and upgrading. For scenarios considered to date, most water use was from evaporation and, secondarily, from bleed streams. Other use was relatively small at the level of fidelity being modeled now.

54 ENVIRONMENTAL SCIENCES↗

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗

Applications Of The Advanced Simulation Capability For Environmental Management (ASCEM) - 17253

Three applications were completed using the Advanced Simulation Capability for Environmental Management (ASCEM), supported by the U.S. Department of Energy's Office of Environmental Management. These analyses were performed for the Savannah River Site (SRS) F-Area, the Los Alamos National Laboratory (LANL) Site, and the Nevada National Security Site (NNSS). At the SRS F-Area, ASCEM simulations were used to help develop cost-effective, long-term monitoring approaches for science-based site closure and management. The simulation results were used to develop a mechanistic understanding of correlations between contaminant concentrations and master variables that can be used for monitoring. At LANL, the ASCEM simulator Amanzi was integrated with a LANL-based decision support tool for the LANL onsite program. A saturated-zone site model focused on a key area of interest was developed and calibrated to measured data. This model was applied to quantify uncertainty and provide decision support to inform chromium remediation efforts. To support assessment of groundwater contamination at NNSS, ASCEM was used to calibrate hydrologic properties and flow directions using water levels observed under steady-state conditions and during four different pump tests on Pahute Mesa. The flow fields generated from these pump tests will be used to simulate transport pathways from underground nuclear tests to compare with field observations and to test alternative conceptual models of transport, which will ultimately facilitate better placement of monitoring wells. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Impact of weightlessness on muscle function

The most studied skeletal muscles which depend on gravity, "antigravity" muscles, are located in the posterior portion of the legs. Antigravity muscles are characterized generally by a different fiber type composition than those which are considered nonpostural. The gravity-dependent function of the antigravity muscles makes them particularly sensitive to weightlessness (unweighting) resulting in a substantial loss of muscle protein, with a relatively greater loss of myofibrillar (structural) proteins. Accordingly alpha-actin mRNA decreases in muscle of rats exposed to microgravity. In the legs, the soleus seems particularly responsive to the lack of weight-bearing associated with space flight. The loss of muscle protein leads to a decreased cross-sectional area of muscle fibers, particularly of the slow-twitch, oxidative (SO) ones compared to fast-twitch glycolytic (FG) or oxidative-glycolytic (FOG) fibers. In some muscles, a shift in fiber composition from SO to FOG has been reported in the adaptation to spaceflight. Changes in muscle composition with spaceflight have been associated with decreased maximal isometric tension (Po) and increased maximal shortening velocity. In terms of fuel metabolism, results varied depending on the pathway considered. Glucose uptake, in the presence of insulin, and activities of glycolytic enzymes are increased by space flight. In contrast, oxidation of fatty acids may be diminished. Oxidation of pyruvate, activity of the citric acid cycle, and ketone metabolism in muscle seem to be unaffected by microgravity.

NASA Discipline Number 00-00↗

Micro X-ray computed tomography examination of mini plate fuel with hot isostatic pressed aluminum cladding

In order to minimize proliferation risks and improve security of nuclear material, the United States high performance research and test reactors (USHPRR) program is tasked with converting nuclear reactors that are fueled with highly enriched uranium (HEU) fuels to operate with low-enriched uranium (LEU) nuclear fuels. One favorable LEU fuel configuration is plate fuel with a metallic uranium-molybdenum foil clad within an aluminum alloy (AA 6061). In this fuel, the aluminum cladding is bonded with a hot isostatic pressing (HIP) method to seal the cladding around the fuel meat. However, the HIP process parameters influence the cladding performance, as a defective or incomplete bond can cause a pathway for corrosion. Micro X-ray computed tomography (XCT), a nondestructive technique that provides volumetric imaging, can be applied to inspect fuel plate cladding at the engineering scale. In this work, XCT methodology was developed and successfully utilized to not only observe the bond line of unirradiated mini fuel plates, but to also identify subsurface abnormalities in the plates’ cladding. Importantly, in future work, this technique could be applied to fuel plates, pre- and post-irradiation, to quantify irradiation effects on cladding defects and bond line integrity.

36 MATERIALS SCIENCE↗

Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways

Gas fermentation by autotrophic bacteria, such as clostridia, offers a sustainable path to numerous bioproducts from a range of local, highly abundant, waste and low-cost feedstocks, such as industrial flue gases or syngas generated from biomass or municipal waste. Unfortunately, designing and engineering clostridia remains laborious and slow. The ability to prototype individual genetic part function, gene expression patterns, and biosynthetic pathway performance in vitro before implementing designs in cells could help address these bottlenecks by speeding up design. Unfortunately, a high-yielding cell-free gene expression (CFE) system from clostridia has yet to be developed. Here in this paper, we report the development and optimization of a high-yielding (236 ± 24 μg/mL) batch CFE platform from the industrially relevant anaerobe, Clostridium autoethanogenum. A key feature of the platform is that both circular and linear DNA templates can be applied directly to the CFE reaction to program protein synthesis. We demonstrate the ability to prototype gene expression, and quantitatively map aerobic cell-free metabolism in lysates from this system. We anticipate that the C. autoethanogenum CFE platform will not only expand the protein synthesis toolkit for synthetic biology, but also serve as a platform in expediting the screening and prototyping of gene regulatory elements in non-model, industrially relevant microbes.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of a preQ1-I riboswitch in effector-free and bound states reveals a metabolite-programmed nucleobase-stacking spine that controls gene regulation

Abstract Riboswitches are structured RNA motifs that recognize metabolites to alter the conformations of downstream sequences, leading to gene regulation. To investigate this molecular framework, we determined crystal structures of a preQ1-I riboswitch in effector-free and bound states at 2.00 Å and 2.65 Å-resolution. Both pseudoknots exhibited the elusive L2 loop, which displayed distinct conformations. Conversely, the Shine-Dalgarno sequence (SDS) in the S2 helix of each structure remained unbroken. The expectation that the effector-free state should expose the SDS prompted us to conduct solution experiments to delineate environmental changes to specific nucleobases in response to preQ1. We then used nudged elastic band computational methods to derive conformational-change pathways linking the crystallographically-determined effector-free and bound-state structures. Pathways featured: (i) unstacking and unpairing of L2 and S2 nucleobases without preQ1—exposing the SDS for translation and (ii) stacking and pairing L2 and S2 nucleobases with preQ1—sequestering the SDS. Our results reveal how preQ1 binding reorganizes L2 into a nucleobase-stacking spine that sequesters the SDS, linking effector recognition to biological function. The generality of stacking spines as conduits for effector-dependent, interdomain communication is discussed in light of their existence in adenine riboswitches, as well as the turnip yellow mosaic virus ribosome sensor.

59 BASIC BIOLOGICAL SCIENCES↗

LLNL SFA OBER–SBR FY19 Program Management and Performance Report: Biogeochemistry of Actinides

Over 2,600 metric tons of plutonium (Pu) are estimated to have been produced worldwide, with approximately 70-90 metric tons added to this inventory each year from spent nuclear fuel. A subset of this Pu inventory has been released into the environment as a result of nuclear weapons production, weapons testing, poor waste management practices, and nuclear accidents. The migration of low levels of Pu released in the environment has been documented on the scale of kilometers. Due to its long half-life, toxicity, and its ability to migrate, Pu represents a potentially significant risk to humankind and the environment. Their fate depends on the nature of the release, the biogeochemical processes controlling mobilization, and the eventual exposure pathways. Understanding their behavior in the environment is critical for managing environmental contamination and planning for the safe, long-term isolation of nuclear waste from the biosphere.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Role of Surface Hydroxyls and Lattice Oxygen in Governing Selectivity and Restructuring During Acetic Acid Conversion on Fe 3 O 4 (001)

Understanding the reactivity of carboxylic acids on metal oxide surfaces is critical for elucidating ketonization mechanisms relevant to biomass upgrading. Here, we investigate the adsorption and thermal decomposition of acetic acid (CH 3 COOH) on Fe 3 O 4 (001) using scanning tunneling microscopy (STM), temperature-programmed reaction spectroscopy (TPRS), and X-ray photoelectron spectroscopy (XPS). At room temperature, acetic acid adsorbs dissociatively to form ordered bidentate acetate (CH 3 COO) overlayer that lifts the (√2 × √2)R 45° surface reconstruction. TPRS reveals ketene (CH 2 CO) as the dominant product, along with CO, CO 2 , and H 2 O, the latter evolving via a Mars–van Krevelen (MvK) mechanism. Isotopic labeling shows preferential CO 2 formation from the carboxyl carbon and a more balanced CO/CO 2 ratio from the methyl carbon, suggesting distinct oxidation pathways. STM imaging reveals embedded acetate intermediates filling surface oxygen vacancies created in MvK steps. Upon product formation completion (~700 K), extensive surface etching is observed, with pits elongated along the octahedral Fe rows. Approximately 20% of the surface oxygen is removed, consistent with vacancy formation stoichiometry inferred from product distributions. These findings demonstrate that carboxylate-induced restructuring of Fe 3 O 4 (001) involves both surface healing and reduction processes, offering mechanistic insights relevant to ketonization and broader carboxylic acid chemistry on metal oxides.

acetic acid↗