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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗
DOE OSTI2015

Simplified predictive models for CO 2 sequestration performance assessment

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Application of LES-CFD for predicting pulverized-coal working conditions after installation of NOx control system

The upcoming environmental requirements outlined at the 2017 European Commission Integrated Pollution Prevention and Control (IPPC) are becoming more and more strict in comparison to the existing standards – IED 2010/75/EU. Questions arise about changes in boiler operating conditions after the adoption of the regulations to fulfill specified emission limits. Of initial concern is the question of which technology to pursue in order to reach the specified level of NOx emissions at 150 mg/Nm 3 @6%O 2 . By introducing an air staging technique the NOx limit can be partially achieved; however these changes affect the boiler operation in a detrimental way. In order to investigate impact of de-NOx installation on the temperature and heat flux distribution, numerical techniques can be used. In order to determine the impact of the changes in the boiler operation, here this paper presents the application of an advanced, multiphase open-source code Arches, developed at the University of Utah for modeling pulverized-coal combustion using Large-Eddy Simulation (LES). Numerical simulations showed the effect on the boiler's working parameters e.g., heat-transfer rate, temperature distribution, species concentration, and NOx emission before and after proposed modifications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

Beam-driven plasma wakefield acceleration (PWFA) achieves the same energy gain in a single meter, for which conventional accelerators require several kilometers, however much work is still required to match the beam quality of conventional accelerators. The PWFA processes to be studied at the FACET-II facility will utilize extremely short (down to a few fs) high energy (10 GeV), high charge (few nC) electron and eventually positron bunches. The PWFA process is extremely sensitive to the detailed longitudinal current profiles of these bunches and it would be of great benefit to have precise measurement and control of these profiles. We present an adaptive model tuning technique for FACET-II to adaptively tune online models based on real time accelerator and beam data to continuously provide a non-invasive diagnostic which predicts the longitudinal phase space (LPS) of extremely short and highly compressed electron beams, which otherwise require destructive X-band transverse deflecting cavity (XTCAV)-based measurements. Based on simulation studies, our method has the potential for: (1). The development of a non-invasive longitudinal phase space diagnostic by adaptively tuning models based on non-invasive measurements such as energy spread spectra which could be recorded at all of the bunch compressors in the facility. (2). Utilize these diagnostic to perform model-independent feedback-based to achieve desired longitudinal phase space distributions. (3). Utilize the model-independent feedback approach to maximize energy gain while minimizing emittance growth and energy gain variance of the PWFA process by tuning accelerator parameters, while monitoring what longitudinal phase space the algorithm has found, information that will be useful for further analytical and simulation studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow

This work presents a new engineering analytical model that predicts the effect of both the turbine yaw misalignment and the inflow wind veer on the wake flow distribution downwind of a wind turbine. To consider the veered inflow, two methods were examined. In the first method, the curled shape of the wake due to the yaw offset is initially modelled. The wake shape is then laterally skewed at each height due to the wind veer based on the assumption that the turbine wake is transported downstream by the incoming flow. The second method is a more realistic approach that accounts for the effect of wind veer on the wind velocity direction and the yaw angle seen by the wind turbine. This models the wake region in a local coordinate system defined based on the wind direction at each height. A coordinate transformation is then performed to represent the wake flow distribution in the global coordinate system attached to the ground. The results show that while the two methods provide similar outputs for small variations in the wind direction across the rotor, the difference becomes more evident with an increase in wind veer. High-fidelity simulations for a turbine subject to a neutral atmospheric boundary layer were employed to validate model predictions for different operating conditions.

17 WIND ENERGY↗
DOE OSTI2023

Characterization of the In Vivo Deuteration of Native Phospholipids by Mass Spectrometry Yields Guidelines for Their Regiospecific Customization

Customization of deuterated biomolecules is vital for many advanced biological experiments including neutron scattering. However, because it is challenging to control the proportion and regiospecificity of deuterium incorporation in live systems, often only two or three synthetic lipids are mixed together to form simplistic model membranes. This limits the applicability and biological accuracy of the results generated with these synthetic membranes. Despite some limited prior examination of deuterating Escherichia coli lipids in vivo, this approach has not been widely implemented. In this report an extensive mass spectrometry-based profiling of E. coli phospholipid deuteration states with several different growth media was performed, and a computational method to describe deuterium distributions with a one-number summary is introduced. The deuteration states of 36 lipid species were quantitatively profiled in 15 different growth conditions, and tandem mass spectrometry was used to reveal deuterium localization. Regressions were employed to enable the prediction of lipid deuteration for untested conditions. Small-angle neutron scattering was performed on select deuterated lipid samples, which validated the deuteration states calculated from the mass spectral data. Based on these experiments, guidelines for the design of specifically deuterated phospholipids are described. This unlocks even greater capabilities from neutron-based techniques, enabling experiments that were formerly impossible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational studies of impurity migration during induction stirring of molten uranium

Understanding and controlling impurity behavior in actinide metal casting processes are foundational for efficient part production yet remain major challenges for researchers and industry. To help provide insight regarding impurity distribution during actinide metal casting, we have developed computational fluid dynamics (CFD) models for a laboratory-scale system using commercial and open-source code. Multiple simulation frameworks allow for improved confidence in the resulting outputs, while taking advantage of the maturity and convenience offered by commercial platforms and simultaneously maintaining the transparency and flexibility often provided by open-source software. Here, we describe multiple experiment-informed models designed to simulate a specific laboratory system in which uranium melt, containing a known starting concentration of carbon impurity, is electromagnetically stirred in an induction furnace. Here, the goal of the simulations is to predict the motion of uranium carbide microparticles in the velocity field of the melt. Prior to simulating the uranium-carbon system, numerical models were validated using a previously published nonradioactive experimental system. Effects of the size and shape of impurity particles in the models were investigated and agree with experimental findings. Simulation of smaller particles (< 50 µm) shows more homogenous distribution throughout the stirred melt. With increased particle size (100 µm), the body forces, which include the buoyancy force, dominate over the drag force, causing larger particles to move toward the crucible walls and upward in the system.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Effects of the distribution and evolution of the coefficient of friction along a fault on the assessment of the seismic activity associated with a hypothetical industrial-scale geologic CO 2 sequestration operation

Carbon capture and storage (CCS) in geological formations is considered as a promising option that could limit CO 2 emissions from human activities into the atmosphere. However, there is a risk that pressure buildup inside the storage formation can induce slip along preexisting faults and create seismic event felt by the population. To prevent this to happen a geomechanical fault stability analysis should be performed, considering uncertainties of input parameters. In this paper, we investigate how the distribution of the coefficient of friction and the applied frictional law could influence the assessment of fault stability and the characteristics of potential injection-induced seismic events. Our modelling study is based on a hypothetical industrial-scale carbon sequestration project located in the Southern San Joaquin Basin in California, USA, where the stability on a major (25 km long) fault that bounds the sequestration site is assessed during 50 years of CO 2 injection. We conduct nine simulations in which the distributions of the coefficients of static and dynamic friction are changed to simulate a hardening and softening phase before and during rupture. Here, our main findings are: (i) variations in friction along the fault have an important effect on the predicted seismic activity, with maximum magnitude ranging from 1.88 to 5.88 and number of seismic events ranging from 338 to 3272; (ii) the extreme values of the coefficient of friction (lowest and highest) present along the rupture area control how much stress is accumulated before rupture; and (iii) an argillaceous caprock can prevent the development of large magnitude seismic events but favor the occurrence of a large number of smaller events.

58 GEOSCIENCES↗
DOE OSTI2012

Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

New Architectures for Designed Catalysts: Selective Oxidation using AgAu Nanoparticles on Colloid-Templated Silica

A highly modular synthesis of designed catalysts with controlled bimetallic nanoparticle size and composition and a well-defined structural hierarchy is shown. Exemplary catalysts—bimetallic dilute Ag-in-Au nanoparticles partially embedded in a porous SiO 2 matrix (SiO 2 –Ag x Au y )—were synthesized by the decoration of polymeric colloids with the bimetallic nanoparticles followed by assembly into a colloidal crystal backfilled with the matrix precursor and subsequent removal of the polymeric template. This work reports that these new catalyst architectures are significantly better than nanoporous dilute AgAu alloy catalysts (nanoporous Ag 3 Au 97 ) while retaining a clear predictive relationship between their surface reactivity with that of single-crystal Au surfaces. This paves the way for broadening the range of new catalyst architectures required for translating the designed principles developed under controlled conditions to designed catalysts under operating conditions for highly selective coupling of alcohols to form esters. Excellent catalytic performance of the porous SiO 2 –Ag x Au y structure for selective oxidation of both methanol and ethanol to produce esters with high conversion efficiency, selectivity, and stability was demonstrated, illustrating the ability to translate design principles developed for support-free materials to the colloid-templated structures. The synthetic methodology reported is customizable for the design of a wide range of robust catalytic systems inspired by design principles derived from model studies. Fine control over the composition, morphology, size, distribution, and availability of the supported nanoparticles was discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Precipitation in pores: A geochemical frontier

This article's purpose is to review some of the recent research in which geochemists have examined precipitation of solid phases in porous media, particularly in pores a few nanometers in diameter (nanopores). While this is a “review,” it is actually more forward-looking in that the list of things about this phenomenon that we do not know or cannot control at this time is likely longer than what we do know and can control. For example, there are three directly contradictory theories on how to predict how precipitation proceeds in a medium of varying pore size, as will be discussed below. The confusion on this subject likely stems from the complexity of the phenomenon itself: One can easily clog a porous medium by inducing a rapid, homogeneous precipitation directly from solution, or have limited precipitation occur that does not affect permeability or even porosity substantially. It is more difficult to engineer mineral precipitation in order to obtain a specific outcome, such as filling all available pore space over a targeted area for the purposes of contaminant sequestration. However, breakthrough discoveries could occur in the next five to ten years that enhance our ability to predict robustly and finely control precipitation in porous media by understanding how porosity and permeability evolve in response to system perturbations. These discoveries will likely stem (at least in part) from advances in our ability to 1) perform and interpret X-ray/neutron scattering experiments that reveal the extent of precipitation and its locales within porous media (Anovitz and Cole 2015, this volume), and 2) utilize increasingly powerful simulations to test concepts and models about the evolution of porosity and permeability as precipitation occurs (Steefel et al. 2015, this volume). A further important technique to isolate specific phenomena and understand reactivity is also microfluidics cell experiments that allow specific control of flow paths and fluid velocities (Yoon et al. 2012). An improved ability to synthesize idealized porous media will allow for tailored control of pore distributions, mineralogy and will allow more reproducible results. This in turn may allow us to isolate specific processes without the competing and obfuscatory effects that hinder generalization of observations when working with solely natural samples. It is likely that no one single experiment, or simulation technique will provide the key discoveries: to make substantive progress will require a collaborative effort to understand the interplay between fluid transport and geochemistry. Finally, where rock fracturing and elevated pressures are of concern, an understanding and capability to model geomechanical properties are necessary (Scherer 1999).

58 GEOSCIENCES↗
DOE OSTI2013

Tumor response parameters for head and neck cancer derived from tumor-volume variation during radiation therapy

Purpose: The main goal of this paper is to reconstruct a distribution of cell survival fractions from tumor-volume variation for a heterogeneous group of head and neck cancer patients and compare this distribution to the data from predictive assays. Methods: To characterize the tumor-volume variation during radiation therapy treatment, the authors use a two-level tumor-volume model of cell population that separates the entire tumor cell population into two subpopulations of viable cells and lethally damaged cells. This parameterized radiobiological model is integrated with a least squares objective function and a simulated annealing optimization algorithm to describe time-dependent tumor-volume variation rates in individual patients. Several constraints have been used in the optimization problem because tumor-volume variation during radiotherapy is described by a sum of exponentials; therefore, the problem of accurately fitting a model to measured data is ill-posed. The model was applied to measured tumor-volume variation curves from a clinical study on tumor-volume variation during radiotherapy for 14 head and neck cancer patients in which an integrated CT/linear particle accelerator (LINAC) system was used for tumor-volume measurements. Results: The two-level cell population tumor-volume modeling is capable of describing tumor-volume variation throughout the entire treatment for 11 of the 14 patients. For three patients, the tumor-volume variation was described only during the initial part of treatment, a fact that may be related to the neglected hypoxia in the two-level approximation. The predicted probability density distribution for the survival fractions agrees with the data obtained using in vitro studies with predictive assays. The mean value 0.35 of survival fraction obtained in this study is larger than the value 0.32 from in vitro studies, which could be expected because of greater repair in vivo. The mean half-life obtained in this study for the head-and-neck squamous cell carcinoma (SCC) is equal to 3.8 mean potential doubling times, which agrees with 4.0 mean potential doubling times obtained previously for lung SCC. Conclusions: The distribution of cell survival fractions obtained in this study support the hypothesis that the tumor-volume variation during radiotherapy treatment for head and neck cancer can be described by the two-level cell population tumor-volume model. This model can be used for in vivo evaluation of patient-specific radiobiological parameters that are needed for tumor-control probability evaluation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Model predictive control system and method for integrated gasification combined cycle power generation

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Gulf of Mexico miocene CO₂ site characterization mega transect

This project characterized the Miocene-age sub-seafloor stratigraphy in the near-offshore portion of the Gulf of Mexico adjacent to the Texas coast. The large number of industrial sources of carbon dioxide (CO₂) in coastal counties and the high density of onshore urbanization and environmentally sensitive areas make this offshore region extremely attractive for long-term storage of carbon dioxide emissions from industrial sources (CCS). The study leverages dense existing geologic data from decades of hydrocarbon exploration in and around the study area to characterize the regional geology for suitability and storage capacity. Primary products of the study include: regional static storage capacity estimates, sequestration “leads” and prospects with associated dynamic capacity estimates, experimental studies of CO₂-brine-rock interaction, best practices for site characterization, a large-format ‘Atlas’ of sequestration for the study area, and characterization of potential fluid migration pathways for reducing storage risks utilizing novel high-resolution 3D (HR3D) seismic surveys. In addition, three subcontracted studies address source-to-sink matching optimization, offshore well bore management and environmental aspects. The various geologic data and interpretations are integrated and summarized in a series of cross-sections and maps, which represent a primary resource for any near-term commercial deployment of CCS in the area. The regional study characterized and mapped important geologic features (e.g., Clemente-Tomas fault zone, the regionally extensive Marginulina A and Amphistegina B confining systems, etc.) that provided an important context for regional static capacity estimates and specific sequestration prospects of the study. A static capacity estimate of the majority of the Study area (14,467 mi 2 ) was estimated at 86 metric Gigatonnes. While local capacity estimates are likely to be lower due to reservoir-scale characteristics, the offshore Miocene interval is a storage resource of National interest for providing CO₂ storage as an atmospheric emissions abatement strategy. The natural petroleum system was used as an analog to infer seal quality and predict possible migration pathways of fluids in an engineered system of anthropogenic CO₂ injection and storage. The regional structural features (e.g., Clemente-Tomas fault zone) that exert primary control on the trapping and distribution of Miocene hydrocarbons are expected to perform similarly for CCS. Industrial-scale CCS will require storage capacity utilizing well-documented Miocene hydrocarbon (dominantly depleted gas) fields and their larger structural closures, as well as barren (unproductive, brine-filled) closures. No assessment was made of potential for CO₂ utilization for enhanced oil and gas recovery. The use of 3D numerical fluid flow simulations have been used in the study to greatly assist in characterizing the potential storage capacity of a specific reservoir. Due to the complexity of geologic systems (stratigraphic heterogeneity) and inherent limitations on producing a 3D geologic model, these simulations are typically simplified scenarios that explore the influence of model property variability (sensitivity study). A specific site offshore San Luis Pass (southern Galveston Island) was undertaken successfully, indicating stacked storage potential. Downscaling regional capacity estimates to the local scale (and the inverse) has proven challenging, and remains an outstanding gap in capacity assessments. In order to characterize regional seal performance and identify potential brine and CO₂ leakage pathways, results from three high-resolution 3D (HR3D) seismic datasets acquired by the study using novel HR3D (P-Cable) acquisition system showed steady and significant improvements in data quality because of improved acquisition and processing technique. Finely detailed faults and stratigraphy in the shallowest 1000 milliseconds (~800 m) of data allowed for the identification and mapping of unconformable surfaces including what is probably a surface associated with the last Pleistocene glacial lowstand. The identification of a previously unrecognized (in commercial seismic data) gas chimney that was clearly defined in the 2013 HR3D survey, indicates that HR3D surveys may be useful as both a characterization tool for the overburden of a potential carbon sequestration site and as an additional monitoring tool for future engineered injection sites. Geochemical modeling indicated that injection of CO₂ would result in minor dissolution of calcite, K-feldspar and albite. In addition, modeling of typical brines in Miocene age rocks indicate that approximately 5% of injection capacity would result from CO₂ dissolution into the brine. After extensive searches, no rock samples of the Marginulina A and Amphistegina B seals (“caprocks”) were obtained, but analyses of available core samples of other Miocene age mudrocks (seals or caprocks) indicate that they have sealing ability sufficient for potential CO 2 storage in underlying sandstone units.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

SU-D-204-07: Retrospective Correlation of Dose Accuracy with Regions of Local Failure for Early Stage Lung Cancer Patients Treated with Stereotactic Body Radiotherapy

Purpose: To correlate dose distributions computed using six algorithms for recurrent early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT), with outcome (local failure). Methods: Of 270 NSCLC patients treated with 12Gyx4, 20 were found to have local recurrence prior to the 2-year time point. These patients were originally planned with 1-D pencil beam (1-D PB) algorithm. 4D imaging was performed to manage tumor motion. Regions of local failures were determined from follow-up PET-CT scans. Follow-up CT images were rigidly fused to the planning CT (pCT), and recurrent tumor volumes (Vrecur) were mapped to the pCT. Dose was recomputed, retrospectively, using five algorithms: 3-D PB, collapsed cone convolution (CCC), anisotropic analytical algorithm (AAA), AcurosXB, and Monte Carlo (MC). Tumor control probability (TCP) was computed using the Marsden model (1,2). Patterns of failure were classified as central, in-field, marginal, and distant for Vrecur ≥95% of prescribed dose, 95–80%, 80–20%, and ≤20%, respectively (3). Results: Average PTV D95 (dose covering 95% of the PTV) for 3-D PB, CCC, AAA, AcurosXB, and MC relative to 1-D PB were 95.3±2.1%, 84.1±7.5%, 84.9±5.7%, 86.3±6.0%, and 85.1±7.0%, respectively. TCP values for 1-D PB, 3-D PB, CCC, AAA, AcurosXB, and MC were 98.5±1.2%, 95.7±3.0, 79.6±16.1%, 79.7±16.5%, 81.1±17.5%, and 78.1±20%, respectively. Patterns of local failures were similar for 1-D and 3D PB plans, which predicted that the majority of failures occur in centraldistal regions, with only ∼15% occurring distantly. However, with convolution/superposition and MC type algorithms, the majority of failures (65%) were predicted to be distant, consistent with the literature. Conclusion: Based on MC and convolution/superposition type algorithms, average PTV D95 and TCP were ∼15% lower than the planned 1-D PB dose calculation. Patterns of failure results suggest that MC and convolution/superposition type algorithms predict different outcomes for patterns of failure relative to PB algorithms. Work supported in part by Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Tuning Optical Properties of Conjugated Molecules by Lewis Acids: Insights from Electronic Structure Modeling

Understanding and controlling the optoelectronic properties of organic semiconductors at the molecular level remains a challenge due to the complexity of chemical structures and intermolecular interactions. A common strategy to address this challenge is to utilize both experimental and computational approaches. In this contribution, we show that density functional theory (DFT) calculation is a useful tool to provide insights into the bonding, electron population distribution, and optical transitions of adducts between conjugated molecules and Lewis acids (CM-LA). Adduct formation leads to relevant modifications of key properties, including a red shift in optical transitions and an increase in charge carrier density and charge mobility, compared to the parent conjugated molecules. We show that electron density transfer from the CM to the LA, which was hypothesized to cause the experimental red shift in absorption spectra upon LA binding, can be quantified and interpreted by population analysis. Experimental red shifts in optical transitions for all molecular families can also be predicted by time dependent DFT calculations with different density functionals. Finally, these detailed insights help to optimize a priori design guidelines for future applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗