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DOE OSTI2021

Estimating the Acute Health Impacts of Fire-Originated PM 2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM 2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM 2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM 2.5 . Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

58 GEOSCIENCES↗

DOE OSTI2024

Structural Uncertainty in the Sensitivity of Urban Temperatures to Anthropogenic Heat Flux

One key source of uncertainty for weather and climate models is structural uncertainty arising from the fact that these models must simplify or approximate complex physical, chemical, and biological processes that occur in the real world. However, structural uncertainty is rarely examined in the context of simulated effects of anthropogenic heat flux in cities. Using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model, it is found that the sensitivity of urban canopy air temperature to anthropogenic heat flux can differ by an order of magnitude depending on how anthropogenic heat flux is released to the urban environment. Moreover, varying model structures through changing the treatment of roof-air interaction and the parameterization of convective heat transfer between the canopy air and the atmosphere can affect the sensitivity of urban canopy air temperature by a factor of 4. Urban surface temperature and 2-m air temperature are less sensitive to the methods of anthropogenic heat flux release and the examined model structural variants than urban canopy air temperature, but their sensitivities to anthropogenic heat flux can still vary by as much as a factor of 4 for surface temperature and 2 for 2-m air temperature. Our study recommends using temperature sensitivity instead of temperature response to understand how various physical processes (and their representations in numerical models) modulate the simulated effects of anthropogenic heat flux.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Mind the gap – Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars

Abstract. Ground-based radar observations show that, over the eastern North Atlantic, 50 % of warm marine boundary layer (WMBL) hydrometeors occur below 1.2 km and have reflectivities of <-17 dBZ, thus making their detection from space susceptible to the extent of surface clutter and radar sensitivity. Surface clutter limits the ability of the CloudSat cloud profiling radar (CPR) to observe the true cloud base in ~52 % of the cloudy columns it detects and true virga base in ~80 %, meaning the CloudSat CPR often provides an incomplete view of even the clouds it does detect. Using forward simulations, we determine that a 250 m resolution radar would most accurately capture the boundaries of WMBL clouds and precipitation; that being said, because of sensitivity limitations, such a radar would suffer from cloud cover biases similar to those of the CloudSat CPR. Observations and forward simulations indicate that the CloudSat CPR fails to detect 29 %–43 % of the cloudy columns detected by ground-based sensors. Out of all configurations tested, the 7 dB more sensitive EarthCARE CPR performs best (only missing 9.0 % of cloudy columns) indicating that improving radar sensitivity is more important than decreasing the vertical extent of surface clutter for measuring cloud cover. However, because 50 % of WMBL systems are thinner than 400 m, they tend to be artificially stretched by long sensitive radar pulses, hence the EarthCARE CPR overestimation of cloud top height and hydrometeor fraction. Thus, it is recommended that the next generation of space-borne radars targeting WMBL science should operate interlaced pulse modes including both a highly sensitive long-pulse mode and a less sensitive but clutter-limiting short-pulse mode.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Atomistic modeling of tensile deformation and fracture of carbon fibers: Nanoscale stress redistribution, effect of local structural characteristics and nanovoids

The mechanisms of tensile deformation and fracture of carbon fibers are investigated in large-scale molecular dynamics simulations. The simulations performed for computational samples with different structural characteristics enable analysis of the structural sensitivity of the mechanical properties. It is found that the carbon fiber nanostructure can be represented by a fine (nanoscale) mixture of stiff and soft regions. Despite the nanoscale structural heterogeneity of the computational fibers, their fracture strain and tensile strength exceed the experimental values by almost an order of magnitude. Here, this observation is explained by the ability of the carbon fiber nanostructure, largely consisting of curved and folded layers of turbostratic carbon, to exhibit continuous nanoscale load redistribution during the deformation. The transient, fluid nature of a percolating cluster of stress-holding structural elements prevents stress localization at the early stage of the deformation and enables the fiber nanostructure to adapt to the increasing load. Overall, the results of the simulations suggest that the design of advanced carbon fiber manufacturing and post-processing methods focused on the elimination of critical mesoscopic structural defects (internal voids, foreign inclusions, and surface flaws) can yield a substantial increase in the strength and fracture strain of carbon fibers.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simulated impact of fill tube geometry on recent high-yield implosions at the National Ignition Facility

Inertial confinement fusion capsules fielded at the National Ignition Facility are filled with deuterium and tritium fuel by means of a fill tube. The fill tube introduces a low-density pathway into the fuel region of the capsule that allows high Z contaminant to invade the hot spot during the course of the implosion. A recent series of nominally identical high-yield implosions on the NIF has exhibited significant variability in performance. We evaluate the impact of the fill tube in these implosions computationally to determine whether variations in fill tube geometry could have contributed to this variability. The main contrast between the fill tube geometry in the six shots was the outer diameter of the capsule bore hole, a conical hole into which the fill tube is inserted. In our simulations, the geometry of the bore hole can play a significant role in the development of nonlinear flows seeded by the fill tube. Additionally, we find that the amount of space between the bore hole and the fill tube is the primary factor that determines the amount of contaminant jetted into the hot spot by the fill tube and, in turn, the level of yield reduction due to the fill tube in our simulations. As a consequence, some capsules with 5 μm fill tubes are predicted to outperform capsules with 2 μm fill tubes. We also find that micrometer-scale changes to bore hole size can impact fusion yields by up to four times near the ignition threshold. Nevertheless, simulation trends do not reproduce experimental yield trends, suggesting that the fill tube geometry was not the primary factor contributing to the observed variability in performance and that the fill tube could be masking sensitivity to other asymmetries such as other micrometer-scale capsule defects like voids that were not included in our simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Challenges and Practical Solutions for Conducting Structural MARSSIM Surveys in Elevated Radon Environments - 20413

The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) [1] provides comprehensive guidance for the development and implementation of radiological surveys conducted to demonstrate compliance with a dose- or risk-based cleanup goal during final status survey. The MARSSIM methodology follows an integrated strategy combining direct measurements and sampling to assess uniform residual contamination, and scanning surveys to identify localized areas of elevated activity. Building surveys assessing residual surface contamination present unique challenges from reliance on field measurements that may be subject to less than ideal environmental conditions. Additionally, limited characterization and excessive conservatism incorporated into the conceptual site model may result in derived concentration guideline levels (DCGL) and, as a consequence of relatively inefficient field instrumentation, corresponding attributable count rates generally comparable to background. The presence of elevated ambient radon concentrations and associated progeny deposition both exacerbate these intrinsic survey challenges and introduce a series of technical, logistic, and administrative obstacles that can wreak havoc on the statistical legitimacy of each component of the MARSSIM process. Short-lived radon progeny including polonium-218, lead-214, bismuth-214, and polonium-214 produce excessive alpha and beta radiation that may decrease instrument sensitivity through an increase in background count rates, and, at worst, may result in incorrect survey unit failure through the simulation of residual surface activity. Aside from the obvious solution of exhaustive radon mitigation, the primary objectives are to distinguish between radon progeny deposition and actual surface activity, and collect sufficient defensible data. The following is a technical discussion of the consequences of performing building MARSSIM surveys in the presence of elevated ambient radon atmospheres, conceptual examples, and an overview of practical strategies to minimize the effects of radon interference while collecting sufficient defensible data to complete the survey. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

An atomistic survey of shear coupling in asymmetric tilt grain boundaries and interpretation using the disconnections framework

Grain Boundaries (GB) play an important role in determining the behavior of polycrystalline materials. While the mechanisms of motion and associated shear response for symmetric tilt grain boundaries (STGBs) are well studied, the same is not true for asymmetric tilt grain boundaries (ATGBs) despite their greater prevalence in polycrystals. Here, this study aims to investigate the shear response of a large collection of asymmetric tilt grain boundaries (ATGBs) using molecular dynamics (MD) simulations and interpret the data using a discrete disconnections model that works remarkably well for STGBs. MD simulations of shear-driven ATGBs show that the plastic shear (shear coupling factor) in the region swept by a GB exhibits a complex dependence on the inclination angle, and this dependence changes with the misorientation of the GB. In addition, the shear response was observed to be highly sensitive to the applied shear rate and temperature. Recognizing the spatial and temporal scale limitations of MD simulations, we extended the discrete disconnections mesoscale model of Khateret al. (2012) to calculate the nucleation barriers of disconnection modes and predict the effective shear coupling of an ATGB. We observed that the mesoscale model’s predictions of the shear coupling factor of ATGBs do not agree with those observed in MD simulations. Finally, we examine the hypotheses of our mesoscale model that contribute to disagreements between MD simulations and the mesoscale model and propose improvements to the mesoscale model for future work.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Predicted Melt Curve and Liquid Shear Viscosity of RDX up to 30 GPa

Recent grain-scale simulations of HMX and TATB have shown that predictions for hot spot formation in high explosives are particularly sensitive to accurate determinations of the pressure-dependent melt curve and the shear viscosity of the liquid phase. These physics terms are poorly constrained beyond ambient pressure for the explosive RDX. Here we adopt an all-atom modeling approach using molecular dynamics (MD) simulations to predict the melt curve of RDX near to detonation conditions (30 GPa) and determine the shear viscosity of the liquid as a function of temperature and pressure above the melt curve. Phase-coexistence simulations were used to determine the melt curve, which is predicted to vary by almost 1100 K as the pressure increases from 0 GPa to 30 GPa. Equilibrium MD simulations and the Green-Kubo formalism were used to obtain the pressure-temperature-dependent shear viscosity. The shear viscosity of RDX is predicted to be of similar magnitude to the viscosity of TATB at low GPa-range pressures, and to be roughly an order of magnitude lower than the viscosity of HMX. The temperature dependence of the shear viscosity is Arrhenius at a given pressure, and the exponential pre-factor and activation term exhibit a strong, yet complicated, pressure dependence. An empirical pressure-temperature dependent function for RDX shear viscosity is developed that simultaneously captures a wide range of MD predictions while taking an analytic form that extrapolates smoothly beyond the fitted regime. The relative strength of the pressure and temperature dependencies of these two physics terms is found to be of similar magnitude for RDX, HMX, and TATB, which motivates incorporating these results in future RDX grain-scale modeling.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Sensitivity of Chemical Kinetic Models on Flame Transfer Functions in Acoustic Fluctuation Environments with Varying Equivalence Ratios

Various factors affect the heat release response of flames – thermodynamics, hydrodynamics, acoustics, etc. The coupling of heat release rate and acoustics, in particular, is essential to the design of combustion devices so as to avoid adverse effects during their operation. Modeling flames in acoustic environments requires an accurate understanding of the fundamental physics that occurs when flames interact with a fluctuating pressure field. Over the past couple of decades, researchers have been quantifying the impact of this fluctuating pressure field on the unsteady heat release rate. The flame transfer functions computed have also been shown to depend on the level of detail in the chemical kinetic model. This paper attempts to bridge the gap between these studies to understand how sensitive the flame transfer function is to various kinetic models. The problem is studied by performing multiple one-dimensional simulations using the low-Mach solver NGA. The detailed GRI-Mech 3.0 will be used for comparison. Also, the pressure amplitude and reactant equivalence ratio are varied to understand how the environment affects this sensitivity.

Girdhar, Anant↗

DOE OSTI2021

SANDD: A directional antineutrino detector with segmented 6 Li-doped pulse-shape-sensitive plastic scintillator

We present a characterization of a small (9-liter) and mobile 0.1% 6 Li-doped pulse-shape-sensitive plastic scintillator antineutrino detector called SANDD (Segmented AntiNeutrino Directional Detector), constructed for the purpose of near-field reactor monitoring with sensitivity to antineutrino direction. SANDD comprises three different types of module. A detailed Monte Carlo simulation code was developed to match and validate the performance of each of the three modules. The combined model was then used to produce a prediction of the performance of the entire detector. Analysis cuts were established to isolate antineutrino inverse beta decay events while rejecting large fraction of backgrounds. The neutron and positron detection efficiencies are estimated to be 34.8% and 80.2%, respectively, while the coincidence detection efficiency is estimated to be 71.7%, resulting in inverse beta decay detection efficiency of 20.0% ± 0.2%(stat.) ± 2.1%(syst.). Finally, the predicted directional sensitivity of SANDD produces an uncertainty of 20° in the azimuthal direction per 100 detected antineutrino events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

A wide range experimental and kinetic modeling study of the oxidation of 2,3-dimethyl-2-butene: Part 1

2,3-Dimethyl-2-butene (TME) is a potential fuel additive with high research octane number (RON) and octane sensitivity (S), which can improve internal combustion engine performance and efficiency. However, the combustion characteristics of TME have not been comprehensively investigated. Thus, it is essential to study the combustion characteristics of TME and construct a detailed chemical kinetic model to describe its combustion. In this paper, two high-pressure shock tubes and a constant-volume reactor are used to measure ignition delay times and laminar flame speeds of TME oxidation. Further, the ignition delay times were measured at equivalence ratios of 0.5, 1.0, and 2.0 in “air”, at pressures of 5 and 10 bar, in the temperature range of 950 – 1500 K. Flame speeds of the TME/ “air” mixtures were measured at atmospheric pressure, at a temperature of 325 K, for equivalence ratios ranging from 0.78 to 1.31. Two detailed kinetic mechanisms were constructed independently using different methodologies; the KAUST TME mechanism was constructed based on NUIGMech1.1, and the MIT TME mechanism was built using the Reaction Mechanism Generator (RMG). Both mechanisms were used to simulate the experimental results using Chemkin Pro. In the present work, reaction flux and sensitivity analyses were performed using the KAUST mechanism to determine the critical reactions controlling TME oxidation at the conditions studied.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Tardigrade, Version 1.1x

Tardigrade is a collection of functions, libraries, and stand-alone code which enables the simulation of materials using the higher-order micromorphic framework. The tools present are the interface to INL's MOOSE code which is used as the underlying FEA solver, several constitutive equations (linear elasticity, a pressure-sensitive elasto-plastic model, crystal plasticity, and additional models for geo-materials) useful for demonstration purposes and the simulation of some materials, the micromorphic filter which converts DNS information to micromorphic stress-deformation quantities, and the overlap coupling framework which enables multi-scale simulations of a coupled higher-order macroscale and a classically defined microscale.

Miller, Nathan↗

DOE OSTI2021

History Matching and Performance Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope (ANS) is ongoing. After more than 2.5 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is economically attractive.

Wang, Xindan↗

DOE OSTI2022

An algorithm for detecting and quantifying disturbance and recovery in high-frequency time series

Determining when a disturbance has occurred, its severity, and when the system recovered, is important to numerous questions in the aquatic sciences. This problem can be conceptualized as the timing and degree of perturbation from a typical state, and when the system returns to that typical state. We present an algorithm for detecting disturbance and recovery designed for high-frequency time series, e.g., data produced by automated sampling devices in instrumented buoys and flux towers. The algorithm quantifies differences in the empirical cumulative distribution functions of moving windows over reference and evaluation periods, and is sensitive to changes in the mean, variance, and higher statistical moments. Tests on simulated data show it accurately identifies disturbance and recovery. Three case studies illustrate the application of our algorithm in different empirical settings. A case study on dissolved oxygen in a Florida, USA estuary following a hurricane identified the disturbance and recovery 73 d later. A case study on air temperature and net ecosystem exchange in the Florida everglades identified cold snaps coinciding with periods of reduced carbon uptake. A case study on rotifer abundance following zebra mussel invasion in the Hudson River, NY showed rotifer collapse following invasion and recovery over a decade later. Methods such as ours can improve understanding response to disturbance and facilitate comparative and synthetic study of disturbance impacts across ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Sensitivity Analysis for Solutions to Heterogeneous Nonlocal Systems. Theoretical and Numerical Studies

The paper presents a collection of results on continuous dependence for solutions to nonlocal problems under perturbations of data and system parameters. The integral operators appearing in the systems capture interactions via heterogeneous kernels that exhibit different types of weak singularities, space dependence, even regions of zero-interaction. Here, the stability results showcase explicit bounds involving the measure of the domain and of the interaction collar size, nonlocal Poincaré constant, and other parameters. In the nonlinear setting, the bounds quantify in different L p norms the sensitivity of solutions under different nonlinearity profiles. The results are validated by numerical simulations showcasing discontinuous solutions, varying horizons of interactions, and symmetric and heterogeneous kernels.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as Monte Carlo weighting. In this work we present a staged approach to the generation of expected distributions of observables in order to overcome these challenges. By combining multiple integration and smoothing techniques which address limited statistics from simulation it arrives at reliable analysis results using modest computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

The Single Residue K12 Governs the Exceptional Voltage Sensitivity of Mitochondrial Voltage-Dependent Anion Channel Gating

The voltage-dependent anion channel (VDAC) is a β-barrel channel of the mitochondrial outer membrane (MOM) that passively transports ions, metabolites, polypeptides, and single-stranded DNA. VDAC responds to a transmembrane potential by “gating,” i.e. transitioning to one of a variety of low-conducting states of unknown structure. The gated state results in nearly complete suppression of multivalent mitochondrial metabolite (such as ATP and ADP) transport, while enhancing calcium transport. Voltage gating is a universal property of β-barrel channels, but VDAC gating is anomalously sensitive to transmembrane potential. Here, we show that a single residue in the pore interior, K12, is responsible for most of VDAC’s voltage sensitivity. Using the analysis of over 40 μs of atomistic molecular dynamics (MD) simulations, we explore correlations between motions of charged residues inside the VDAC pore and geometric deformations of the β-barrel. Residue K12 is bistable; its motions between two widely separated positions along the pore axis enhance the fluctuations of the β-barrel and augment the likelihood of gating. Single channel electrophysiology of various K12 mutants reveals a dramatic reduction of the voltage-induced gating transitions. The crystal structure of the K12E mutant at a resolution of 2.6 Å indicates a similar architecture of the K12E mutant to the wild type; however, 60 μs of atomistic MD simulations using the K12E mutant show restricted motion of residue 12, due to enhanced connectivity with neighboring residues, and diminished amplitude of barrel motions. We conclude that β-barrel fluctuations, governed particularly by residue K12, drive VDAC gating transitions.

59 BASIC BIOLOGICAL SCIENCES↗