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A global coupled ensemble data assimilation system using the Community Earth System Model and the Data Assimilation Research Testbed

In this paper, we present a description of the CESM/DART ensemble coupled data assimilation (DA) system based on the Community Earth System Model (CESM) and the Data Assimilation Research Testbed (DART) assimilation software. The CESM/DART should be viewed as a flexible system to support the DA needs of the CESM research community and not as a static reanalysis product. In this implementation of the CESM/DART, conventional insitu observations of the ocean and atmosphere are assimilated into the respective component models of the CESM using a 30-member ensemble adjustment Kalman filter (EAKF). CESM/DART is run in a “weakly coupled” configuration wherein observations native to each climate system component only directly impact the state vector for that component. Information is passed between components indirectly through the short-term coupled model forecasts that provide the EAKF background ensemble. This system leverages previous ensemble DA development for the Community Atmosphere Model and Parallel Ocean Program models using the DART EAKF. The CESM/DART project is a step towards providing increasingly useful DA capabilities for the CESM research community. Results are presented for our prototype 12-year reanalysis, run from 1970 to mid 1982. Multiple lines of evidence demonstrate that the system is capable of constraining the CESM coupled model to simulate the historical variability of the climate system in the well-observed Northern Hemisphere. A collection of monthly average variables, climate mode indices, observation diagnostics and snapshots of synoptic weather in the ocean and atmosphere are compared to established datasets, showing especially good agreement in the Northern Hemisphere. A discussion of the CESM/DART as a modular, community facility and the benefits and challenges associated with this vision is also included.

54 ENVIRONMENTAL SCIENCES↗

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pathfinding quantum simulations of neutrinoless double- β decay

We present results from co-designed quantum simulations of the neutrinoless double- β decay of a simple nucleus in 1+1D quantum chromodynamics using IonQ’s Forte-generation trapped-ion quantum computers. Electrons, neutrinos, and up and down quarks are distributed across two lattice sites and mapped to 32 qubits, with an additional 4 qubits used for flag-based error mitigation. A four-fermion interaction is used to implement weak interactions, and lepton-number violation is induced by a neutrino Majorana mass. Quantum circuits that prepare the initial nucleus and time evolve with the Hamiltonian containing the strong and weak interactions are executed on IonQ Forte Enterprise. Enabled by tuned model parameters, lepton-number violation is observed in real time, providing a clear signal of neutrinoless double- β decay. This was made possible by co-designing the simulation to maximally utilize the all-to-all connectivity and native gate-set available on IonQ’s quantum computers. Quantum circuit compilation techniques and co-designed error-mitigation methods, informed from executing benchmarking circuits with up to 2,356 two-qubit gates, enabled observables to be extracted with high precision. We discuss the potential of future quantum simulations to provide yocto-second resolution of the reaction pathways in these, and other, nuclear processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Biophysical model of eelgrass and water quality in Coos Bay, OR shows greater mitigation potential for ocean acidification than hypoxia

Seagrass beds provide important ecosystem services and are valued, in part, for their potential to mediate stressors such as ocean acidification and hypoxia (OAH) for sensitive species. However, the susceptibility of seagrasses to anthropogenic impacts and recent declines motivate the need to better understand the drivers of seagrass and the water quality consequences that occur with variation in seagrass abundance. To meet this need, we leveraged existing monitoring data (water quality and seagrass), hydrodynamic circulation model, and biogeochemical model framework with seagrass submodel, to produce a biophysical model of Coos Bay estuary, Oregon, U.S. The model includes biogeochemical processes involving water quality, plankton, seagrass, and sediment-water interactions. Ecosystem models like this are useful for evaluating complex estuarine systems because they allow us to extend our understanding of system dynamics beyond existing observations and perform experiments to identify the processes driving observed patterns. We used the biophysical model of Coos Bay to evaluate the dynamics of water quality and native eelgrass (Zostera marina) under three eelgrass abundance scenarios (zero eelgrass, current extent, and maximum observed extent) to elucidate the relationship between eelgrass and OAH. Including eelgrass in the Coos Bay model produced results that more closely resembled water quality observations - dissolved oxygen (DO) and pH were more dynamic in simulations with eelgrass, often having both higher highs and lower lows. While there were some areas of the estuary where DO improved with the addition of eelgrass to the model there was overall a small net increase in harmful DO conditions (based on a salmon physiological threshold). In contrast, ocean acidification conditions, pH and calcium carbonate saturation state for aragonite (Ω), were improved (based on oyster requirements) with the addition of eelgrass - although the magnitude of improvement differed seasonally and spatially. Our new model represents a useful tool - one which accounts for and controls the relevant physical and biogeochemical processes - to evaluate conditions that confer resilience or enhance vulnerability to OAH in an important Pacific Northwest coastal estuary and results can inform the OAH-related dynamics occurring in other eastern boundary current estuaries.

FVCOM-ICM↗

Unavoidable multilevel biaxial symmetry breaking in chiral hybrid liquid crystals

Chiral nematic or cholesteric liquid crystals (LCs) are fluid mesophases with long-ranged orientational order featuring a quasilayered periodicity imparted by a helical director configuration but lacking long-range positional order. Doping molecular cholesteric LCs with strongly anisotropic uniaxial colloidal particles adds another level of complexity because of the interplay between weak surface-anchoring boundary conditions and bulk-based elastic distortions near the particle-LC interface. Using cylindrical colloidal disks and rods with different geometric shapes and surface conditions, we demonstrate that these colloidal inclusions generically exhibit biaxial orientational probability distributions which may impart anomalously strong local biaxiality onto the hybrid cholesteric LC structure. Unlike nonchiral hybrid molecular-colloidal LCs, where biaxial order emerges only at critical colloid volume fractions exceeding some uniaxial-biaxial transition value, the orientational probability of the colloidal inclusions immersed in chiral nematic hosts is unambiguously biaxial even at infinite dilution. We demonstrate that the colloids induce local biaxial perturbations within the molecular orientational order of the LC host medium which strongly enhances the weak but native biaxial order of chiral nematic LC induced by the chiral symmetry breaking of the director field. With the help of analytical modeling and computer simulations based on the Landau–de Gennes free energy of the host LC around the colloids, we rationalize the observed multilevel biaxial order and conclude that it is not only unavoidable but also strongly enhanced compared to both achiral hybrid LCs and purely molecular cholesteric LCs.

biaxial liquid crystals↗

infrastore [SWR-26-077]

Infrastore is time-series storage for energy-systems simulations, backed by HDF5 + SQLite, with Rust, Python, Julia, gRPC, and CLI bindings. It is a Rust library for managing time-series data in power-systems and energy simulations. Numerical arrays are persisted in HDF5, and the metadata associating each array with its owning component lives in SQLite. Identical arrays are stored once and shared through content addressing. It ships native Rust, Python (PyO3), and Julia (C ABI) interfaces, the infrastore command-line tool, and a read-only gRPC server with a Rust client. Documentation: https://natlabrockies.github.io/infrastore/latest/ — start with the Quick Start or the Architecture.

Thom, Daniel [National Laboratory of the Rockies (↗

Non-linear enhancement of ultrafast X-ray diffraction through transient resonances

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.

47 OTHER INSTRUMENTATION↗

Necessary Experimental Conditions for Single-Shot Diffraction Imaging of DNA-Based Structures with X-ray Free-Electron Lasers

It has been proposed that the radiation damage to biological particles and soft condensed matter can be overcome by ultrafast and ultraintense X-ray free-electron lasers (FELs) with short pulse durations. The successful demonstration of the “diffraction-before-destruction” concept has made single-shot diffraction imaging a promising tool to achieve high resolutions under the native states of samples. However, the resolution is still limited because of the low signal-to-noise ratio, especially for biological specimens such as cells, viruses, and macromolecular particles. Here, we present a demonstration single-shot diffraction imaging experiment of DNA-based structures at SPring-8 Angstrom Compact Free Electron Laser (SACLA), Japan. Through quantitative analysis of the reconstructed images, the scattering abilities of gold and DNA were demonstrated. Suggestions for extracting valid DNA signals from noisy diffraction patterns were also explained and outlined. To sketch out the necessary experimental conditions for the 3D imaging of DNA origami or DNA macromolecular particles, we carried out numerical simulations with practical detector noise and experimental geometry using the Linac Coherent Light Source (LCLS) at the SLAC National Accelerator Laboratory, USA. In conclusion, the simulated results demonstrate that it is possible to capture images of DNA-based structures at high resolutions with the technique development of current and next-generation X-ray FEL facilities.

59 BASIC BIOLOGICAL SCIENCES↗

A Distributed Control System Prototyping Environment to Support Control Room Modernization

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, however the set of tools for developing and designing HMIs is still in its infancy. Here we propose a rapid prototyping approach for integrating proposed HMIs into their native environments before a design is finalized. This approach allows researchers and developers to test design ideas and eliminate design flaws prior to fully developing the new system. We illustrate this approach with four prototype designs developed using Microsoft’s Windows Presentation Foundation (WPF). One example is integrated into a microworld environment to test the functionality of the design and identify the optimal level of automation for a new system in a nuclear power plant. The other three examples are integrated into a full-scale, glasstop digital simulator of a nuclear power plant. One example demonstrates the capabilities of next generation control concepts; another aims to expand the current state of the art; lastly, an HMI prototype was developed as a test platform for a new control system currently in development at U.S. nuclear power plants. WPF possesses several characteristics that make it well suited to HMI design. It provides a tremendous amount of flexibility, agility, robustness, and extensibility. Distributed control system (DCS) specific environments tend to focus on the safety and reliability requirements for real-world interfaces and consequently have less emphasis on providing functionality to support novel interaction paradigms. Because of WPF’s large user-base, Microsoft can provide an extremely mature tool. Within process control applications,WPF is platform independent and can communicate with popular full-scope process control simulator vendor plant models and DCS platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MicroBooNE Public Data Sets: a Collaborative Tool for LArTPC Software Development

Among liquid argon time projection chamber (LArTPC) experiments MicroBooNE is the one that continually took physics data for the longest time (2015-2021), and represents the state of the art for reconstruction and analysis with this detector. Recently published analyses include oscillation physics results, searches for anomalies and other BSM signatures, and cross section measurements. LArTPC detectors are being used in current experiments such as ICARUS and SBND, and being planned for future experiments such as DUNE. MicroBooNE has recently released to the public two of its data sets, with the goal of enabling collaborative software developments with other LArTPC experiments and with AI or computing experts. These data sets simulate neutrino interactions on top of off-beam data, which include cosmic ray background and noise. The data sets are released in two formats: the native art/ROOT format used internally by the collaboration and familiar to other LArTPC experts, and the HDF5 format which contains reduced and simplified content and is suitable for usage by the broader community. This contribution presents the open data sets, discusses their motivation, the technical implementation, and the extensive documentation -- all inspired by FAIR principles. Finally, opportunities for collaborations are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Structure-Based Exciton Hamiltonian and Dynamics for the Reconstituted Wild-type CP29 Protein Antenna Complex of the Photosystem II

Here we provide an analysis of the pigment composition of reconstituted wild type CP29 complexes. The obtained stoichiometry of 9 ± 0.6 Chls a and 3 ± 0.6 Chls b per complex, with some possible heterogeneity in the carotenoid binding, is in agreement with 9 Chls a and 3.5 Chls b revealed by the modeling of low-temperature optical spectra. We find that ~50% of Chl b614 is lost during the reconstitution/purification procedure, while Chls a are almost fully retained. The excitonic structure and the nature of the low-energy (low-E) state(s) are addressed via simulations (using Redfield theory) of 5 K absorption and fluorescence/nonresonant hole-burned (NRHB) spectra obtained at different excitation/burning conditions. We show that, depending on laser excitation frequency, reconstituted complexes display two (independent) low-E states (i.e., the A and B traps) with different NRHB and emission spectra. The red-shifted state A near 682.4 nm is assigned to a minor (~10%) subpopulation (Sub. II) that most likely originates from an imperfect local folding occurring during protein reconstitution. Its lowest energy state A (localized on Chl a604) is easily burned with λ B = 488.0 nm and has a red-shifted florescence origin band near 683.7 nm that is not observed in native (isolated) complexes. Prolonged burning by 488.0 nm light reveals a second low-E trap at 680.2 nm (state B) with a fluorescence origin-band ~681 nm which is also observed when using a direct lowfluence excitation near 650 nm. The latter state is mostly delocalized over the a611, a612, a615 Chl trimer, and corresponds to the lowest energy state of the major (~90%) subpopulation (Sub. I) which exhibits a lower hole-burning quantum yield. Thus, we suggest that major Sub. I correspond to the native folding of CP29, whereas the red-shift of the Chl a604 site energy observed in the minor Sub. II occurs only in reconstituted complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multitarget Rydberg gates via spatial blockade engineering

Multi-target gates offer the potential to reduce gate depth in syndrome extraction for quantum error correction. Although neutral-atom quantum computers have demonstrated native multi-qubit gates, existing approaches that avoid additional control or multiple atomic species have been limited to single-target gates. We propose single-control-multi-target CZ^n gates on a single-species neutral-atom platform that require no extra control and have gate durations comparable to standard CZ gates. Our approach leverages tailored interatomic distances to create an asymmetric blockade between the control and target atoms. Using a GPU-accelerated pulse synthesis protocol, we design smooth control pulses for CZZ and CZZZ gates, achieving fidelities of up to 99.55% and $99.24\%$, respectively, even in the presence of simulated atom placement errors and Rydberg-state decay. Our approach is most effective for N=2 (CZZ) and N=3 targets (CZZZ); for larger N, increasing spatial crowding of the targets introduces significant challenges for maintaining the required blockade asymmetry. This work presents a practical path to implementing low-overhead multi-target gates in single-species neutral-atom systems, significantly reducing the resource overhead for syndrome extraction. To motivate the impact of these gates, we apply a greedy scheduling algorithm and we demonstrate that our proposed gates can reduce the number of atom reconfiguration costs by up to 50% for color code syndrome extraction of code distances greater than 5.

Stein, Samuel A.↗

Polyphenols Weaken Pea Protein Gel by Formation of Large Aggregates with Diminished Noncovalent Interactions

Polyphenols are well-known native cross-linkers and gel strengthening agents for many animal proteins. However, their role in modifying plant protein gels remains unclear. In this study, multiple techniques were applied to unravel the influence of green tea polyphenols (GTP) on pea protein gels and the underlying mechanisms. We found that the elasticity and viscosity of pea protein gels decreased with increased GTP. The protein backbone became less rigid when GTP was present based on shortened T 1ρ H in relaxation solid-state NMR measurements. Electron microscopy and small-angle X-ray scattering showed that gels weakened by GTP possessed disrupted networks with the presence of large protein aggregates. Solvent extraction and molecular dynamic simulation revealed a reduction in hydrophobic interactions and hydrogen bonds among proteins in gels containing GTP. The current findings may be applicable to other plant proteins for greater control of gel structures in the presence of polyphenols, expanding their utilization in food and biomedical applications.

59 BASIC BIOLOGICAL SCIENCES↗

Determination of Free Fatty Acids and Triglycerides by Gas Chromatography Using Selective Esterification Reactions

A method for selectively determining both free fatty acids (FFA) and triacylglycerides (TAGs) in biological oils was investigated and optimized using gas chromatography after esterification of the target species to their corresponding fatty acid methyl esters (FAMEs). The method used acid catalyzed esterification in methanolic solutions under conditions of varying severity to achieve complete conversion of more reactive FFAs while preserving the concentration of TAGs. Complete conversion of both free acids and glycerides to corresponding FAMEs was found to require more rigorous reaction conditions involving heating to 120°C for up to 2 h. Method validation was provided using gas chromatography–flame ionization detection, gas chromatography–mass spectrometry, and liquid chromatography–mass spectrometry. The method improves on existing methods because it allows the total esterified lipid to be broken down by FAMEs contributed by FFA compared to FAMEs from both FFA and TAGs. Single and mixed-component solutions of pure fatty acids and triglycerides, as well as a sesame oil sample to simulate a complex biological oil, were used to optimize the methodologies. Key parameters that were investigated included: HCl-to-oil ratio, temperature and reaction time. Pure free fatty acids were found to esterify under reasonably mild conditions (10 min at 50°C with a 2.1:1 HCl to fatty acid ratio) with 97.6 ± 2.3% recovery as FAMEs, while triglycerides were largely unaffected under these reaction conditions. The optimized protocol demonstrated that it is possible to use esterification reactions to selectively determine the free acid content, total lipid content, and hence, glyceride content in biological oils. This protocol also allows gas chromatography analysis of FAMEs as a more ideal analyte than glyceride species in their native state.

59 BASIC BIOLOGICAL SCIENCES↗

Discovering conformational sub-states relevant to protein function

Internal motions enable proteins to explore a range of conformations, even in the vicinity of native state. The role of conformational fluctuations in the designated function of a protein is widely debated. Emerging evidence suggests that sub-groups within the range of conformations (or sub-states) contain properties that may be functionally relevant. However, low populations in these sub-states and the transient nature of conformational transitions between these sub-states present significant challenges for their identification and characterization. To overcome these challenges we have developed a new computational technique, quasi-anharmonic analysis (QAA). QAA utilizes higher-order statistics of protein motions to identify sub-states in the conformational landscape. Further, the focus on anharmonicity allows identification of conformational fluctuations that enable transitions between sub-states. QAA applied to equilibrium simulations of human ubiquitin and T4 lysozyme reveals functionally relevant sub-states and protein motions involved in molecular recognition. In combination with a reaction pathway sampling method, QAA characterizes conformational sub-states associated with cis/trans peptidyl-prolyl isomerization catalyzed by the enzyme cyclophilin A. In these three proteins, QAA allows identification of conformational sub-states, with critical structural and dynamical features relevant to protein function. Overall, QAA provides a novel framework to intuitively understand the biophysical basis of conformational diversity and its relevance to protein function.

59 BASIC BIOLOGICAL SCIENCES↗

In situ study of the role of substrate temperature during atomic layer deposition of HfO{sub 2} on InP

The dependence of the “self cleaning” effect of the substrate oxides on substrate temperature during atomic layer deposition (ALD) of HfO{sub 2} on various chemically treated and native oxide InP (100) substrates is investigated using in situ X-ray photoelectron spectroscopy. The removal of In-oxide is found to be more efficient at higher ALD temperatures. The P oxidation states on native oxide and acid etched samples are seen to change, with the total P-oxide concentration remaining constant, after 10 cycles of ALD HfO{sub 2} at different temperatures. An (NH{sub 4}){sub 2} S treatment is seen to effectively remove native oxides and passivate the InP surfaces independent of substrate temperature studied (200 °C, 250 °C and 300 °C) before and after the ALD process. Density functional theory modeling provides insight into the mechanism of the changes in the P-oxide chemical states.

36 MATERIALS SCIENCE↗

Collidoscope: An Improved Tool for Computing Collisional Cross-Sections with the Trajectory Method

Ion mobility-mass spectrometry (IM-MS) can be a powerful tool for determining structural information about ions in the gas phase, from small covalent analytes to large, native-like or denatured proteins and complexes. For large biomolecular ions, which may have a wide variety of possible gas-phase conformations and multiple charge sites, quantitative, physically explicit modeling of collisional cross sections (CCSs) for comparison to IMS data can be challenging and time-consuming. We present a “trajectory method” (TM) based CCS calculator, named “Collidoscope,” which utilizes parallel processing and optimized trajectory sampling, and implements both He and N{sub 2} as collision gas options. Also included is a charge-placement algorithm for determining probable charge site configurations for protonated protein ions given an input geometry in pdb file format. Results from Collidoscope are compared with those from the current state-of-the-art CCS simulation suite, IMoS. Collidoscope CCSs are within 4% of IMoS values for ions with masses from ~18 Da to ~800 kDa. Collidoscope CCSs using X-ray crystal geometries are typically within a few percent of IM-MS experimental values for ions with mass up to ~3.5 kDa (melittin), and discrepancies for larger ions up to ~800 kDa (GroEL) are attributed in large part to changes in ion structure during and after the electrospray process. Due to its physically explicit modeling of scattering, computational efficiency, and accuracy, Collidoscope can be a valuable tool for IM-MS research, especially for large biomolecular ions. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Discovering Conformational Sub-States Relevant to Protein Function

Background: Internal motions enable proteins to explore a range of conformations, even in the vicinity of native state. The role of conformational fluctuations in the designated function of a protein is widely debated. Emerging evidence suggests that sub-groups within the range of conformations (or sub-states) contain properties that may be functionally relevant. However, low populations in these sub-states and the transient nature of conformational transitions between these sub-states present significant challenges for their identification and characterization. Methods and Findings: To overcome these challenges we have developed a new computational technique, quasi-anharmonic analysis (QAA). QAA utilizes higher-order statistics of protein motions to identify sub-states in the conformational landscape. Further, the focus on anharmonicity allows identification of conformational fluctuations that enable transitions between sub-states. QAA applied to equilibrium simulations of human ubiquitin and T4 lysozyme reveals functionally relevant sub-states and protein motions involved in molecular recognition. In combination with a reaction pathway sampling method, QAA characterizes conformational sub-states associated with cis/trans peptidyl-prolyl isomerization catalyzed by the enzyme cyclophilin A. In these three proteins, QAA allows identification of conformational sub-states, with critical structural and dynamical features relevant to protein function. Conclusions: Overall, QAA provides a novel framework to intuitively understand the biophysical basis of conformational diversity and its relevance to protein function.

59 BASIC BIOLOGICAL SCIENCES↗