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All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

SORS: A New Software for the Simulation of Radiotherapy Schedule

We present a software for choosing the best radiotherapy treatment schedule for head and neck cancers as a beginning radiotherapy plan or a temporarily interrupted plan. Its application occurs according to two modalities: the first adopts the best estimates for model parameters; the second takes into account the parameters' uncertainty too. In both cases, the choice becomes the schedule with the highest uncomplicated tumor control probability (UTCP). In the UTCP valuation, the normal tissue complication probability (NTCP) of each organ is related to the gravity of its possible late injury. For NTCP calculation, it has been adopted the empirical LKB (Lyman-Kutcher-Burman) model corrected for dose/fraction via linear-quadratic model and the incomplete repair effect. The tumor control probability (TCP) model is Poisson based and contains corrections for dose/fraction and regrowth effect; optionally, it can be accounted for the incomplete repair effect as well. At the end of processing, a detailed file with all informations about UTCP, TCP and single organ NTCP is furnished for every examined schedule. Moreover, a useful 3-D graphic representation of the schedule's UTCP is available, allowing the physician to easily understand the schedules with the highest radiotherapeutic efficacy. The open source characteristic allows the program to adapt to the individual clinical case as well as to be a valid support in radiobiological research.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

PetroFit: A Python Package for Computing Petrosian Radii and Fitting Galaxy Light Profiles

PetroFit is an open-source Python package based on Astropy and Photutils that can calculate Petrosian profiles and fit galaxy images. It offers end-to-end tools for making accurate photometric measurements, estimating morphological properties, and fitting 2D models to galaxy images. Petrosian metric radii can be used for model parameter estimation and aperture photometry to provide accurate total fluxes. Correction tools are provided for improving Petrosian radii estimates affected by galaxy morphology. PetroFit also provides tools for sampling Astropy-based models (including custom profiles and multicomponent models) onto image grids and enables point-spread function convolution to account for the effects of seeing. These capabilities provide a robust means of modeling and fitting galaxy light profiles. We have made the PetroFit package publicly available on GitHub (PetroFit/petrofit) and PyPi (pip install petrofit).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Development of an Enhanced Radiation Physics Toolset for Modeling Spectral and Imaging Signatures in the Warm Dense Matter Experiments

Radiative and atomic processes in plasmas play a critical role in a wide variety of high energy density laboratory plasma (HEDLP) experiments. The emission, absorption, and transport of radiation can strongly affect the overall energetics and evolution of such plasmas. In addition, radiation-based diagnostics – including imaging, spectroscopy, and absolute flux measurements – are widely used to determine key features of HEDLPs. To advance our understanding of HEDLP science, it is vital to have high-fidelity computational physics tools that have well-tested radiation physics modeling, and that are readily accessible to researchers in the HEDLP community. Simulations play an extremely important role for planning and designing the experiments, as well as for post-experiment data analysis. Prism Computational Sciences develops software that is used by National Laboratories and universities (including five members of LaserNetUS network). Prominent examples of such research efforts include z-pinch and short-pulse laser experiments designed to study the basic physics of photoionized plasmas and photoionization fronts, as well as their application to astrophysical plasmas. The main effort was dedicated to the development of non-equilibrium equation-of-state (EOS) models within the HELIOS-CR code, a hydrodynamics code with inline collisional-radiative atomic kinetics. Gas cell experiments on Z and Omega demonstrated the importance of non-equilibrium effects on atomic kinetics in photoionized plasmas. Recent proof-of-principle experiments on Omega EP confirmed the advantages of using a short-pulse laser to create an intense radiation drive, leading to additional experiments being proposed. Photoionization front experiments at LLE also emphasizes the importance of radiation and atomic physics. In both studies, HELIOS-CR simulations played a crucial role in computing non-equilibrium opacities and ionization distributions. A newly developed non-LTE EOS model will help addressing possible non-equilibrium effects, on for example specific heat, and their influence in plasma evolution. Prism also implemented support for open-source atomic data generated by the Flexible Atomic Code. This allows researchers to generate custom atomic tables and use them within the complex framework of simulation tools developed by Prism. The ability to use open-source atomic data would be extremely valuable for hydrodynamics and spectroscopic simulations that include high-Z materials, e.g., picosecond x-ray pulse generation experiments. Support for new atomic structures was fully implemented, and the data can be used by all simulation tools developed at Prism: radiation-hydrodynamics, imaging and spectroscopy, EOS and opacity. The development resulted in a significant fidelity enhancement to the simulations tools developed by Prism that are currently used in other cutting-edge experiments including: opacity measurement experiments performed to both understand the basic radiative and atomic properties of plasmas as well as provide data for more accurately modeling the internal structure of the Sun and other stars, high-intensity short-pulse laser experiments performed to develop short-wavelength light sources for use as backlighters and to investigate fast ignition concepts for inertial fusion energy; capsule implosion experiments designed to develop inertial fusion as an energy source, etc.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

Award ER25844: Minimizing System Noise Effects for Extreme-Scale Scientific Simulation Through Function Delegation

In software running on distributed computing clusters, time spent on communication between nodes in the cluster can be a significant portion of the overall computation time; background operating system tasks and other computational noise on the nodes of the system can have a significant impact on the amount of time this communication takes, especially on large systems. The research completed in this period has improved understanding of when such noise will have a significant impact. Specifically, it was demonstrated that not just noise on the nodes, but also noise on the network between nodes can have a significant impact on computation time. It was also demonstrated that noise patterns matter more than noise intensity: very regular noise can cause less disruption than lighter (on average) but less regular noise. It was also demonstrated that the effect of noise is more prominent as the speed of the network between nodes is increased. Furthermore, a tracing tool, Netgauge, was improved via our work, and a system simulator, LogGOPSim, was developed; they can be used by application developers to improve performance of their program and by system designers to mitigate the effects of noise by adjusting the noise characteristics of the operating system. Both have been made freely available as open source programs. In the course of developing these tools, we demonstrated weaknesses in existing methodologies for modeling communication, and we introduced a more detailed model, LogGOPS, for simulating systems. Not only were the deleterious effects of noise explored but we have also offered solutions. Our studies of simulations of system noise have led to specific recommendations on tuning systems to mitigate noise. We have also improved existing approaches to mitigating noise. Non-blocking collective communication avoids the effects of noise by letting communication continue simultaneously with computation (thus being non-blocking), so that the delays in communication introduced by noise have a smaller impact on overall computation time. Potentially, noise can be reduced much further by offloading communication tasks to a separate processing element than the operating system is using. We have improved our library LibNBC, which provides an implementation of non-blocking collectives, via this work. During this research, our proposal to include non-blocking collectives (which used LibNBC as a reference implementation) in the upcoming MPI-3 standard was accepted. As MPI is a ubiquitous and important standard for communication in parallel computing, this demonstrates a certain acceptance of the practicality and desirability of non-blocking collectives. Now that non-blocking collectives are a part of the standard we can expect to see optimized platform-specific implementations of non-blocking collectives. Also as part of this work we have also developed a language GOAL (Global Operation Assembly Language) that can be used as a starting point for defining languages to express optimized communication algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TH-CD-201-10: Highly Efficient Synchronized High-Speed Scintillation Camera System for Measuring Proton Range, SOBP and Dose Distributions in a 2D-Plane

Purpose: Proton therapy (PT) delivery is complex and extremely dynamic. Therefore, quality assurance testing is vital, but highly time-consuming. We have developed a High-Speed Scintillation-Camera-System (HS-SCS) for simultaneously measuring multiple beam characteristics. Methods: High-speed camera was placed in a light-tight housing and dual-layer neutron shield. HS-SCS is synchronized with a synchrocyclotron to capture individual proton-beam-pulses (PBPs) at ∼504 frames/sec. The PBPs from synchrocyclotron trigger the HS-SCS to open its shutter for programmed exposure-time. Light emissions within 30×30×5cm3 plastic-scintillator (BC-408) were captured by a CCD-camera as individual images revealing dose-deposition in a 2D-plane with a resolution of 0.7mm for range and SOBP measurements and 1.67mm for profiles. The CCD response as well as signal to noise ratio (SNR) was characterized for varying exposure times, gains for different light intensities using a TV-Optoliner system. Software tools were developed to analyze ∼5000 images to extract different beam parameters. Quenching correction-factors were established by comparing scintillation Bragg-Peaks with water scanned ionization-chamber measurements. Quenching corrected Bragg-peaks were integrated to ascertain proton-beam range (PBR), width of Spared-Out-Bragg-Peak (MOD) and distal.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

IGRINS RV: A Precision Radial Velocity Pipeline for IGRINS Using Modified Forward Modeling in the Near-infrared

Application of the radial velocity (RV) technique in the near-infrared is valuable because of the diminished impact of stellar activity at longer wavelengths, making it particularly advantageous for the study of late-type stars but also for solar-type objects. In this paper, we present the IGRINS RV open-source python pipeline for computing infrared RV measurements from reduced spectra taken with IGRINS, an R ≡ λ/Δλ ∼ 45,000 spectrograph with simultaneous coverage of the H band (1.49–1.80 μm) and K band (1.96–2.46 μm). Using a modified forward-modeling technique, we construct high-resolution telluric templates from A0 standard observations on a nightly basis to provide a source of common-path wavelength calibration while mitigating the need to mask or correct for telluric absorption. Telluric standard observations are also used to model the variations in instrumental resolution across the detector, including a yearlong period when the K band was defocused. Without any additional instrument hardware, such as a gas cell or laser frequency comb, we are able to achieve precisions of 26.8 m s{sup −1} in the K band and 31.1 m s{sup −1} in the H band for narrow-line hosts. These precisions are empirically determined by a monitoring campaign of two RV standard stars, as well as the successful retrieval of planet-induced RV signals for both HD 189733 and τ Boo A; furthermore, our results affirm the presence of the Rossiter–McLaughlin effect for HD 189733. The IGRINS RV pipeline extends another important science capability to IGRINS, with publicly available software designed for widespread use.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|SpeedShop

In this project we created a community tool infrastructure for program development tools targeting Petascale class machines and beyond. This includes tools for performance analysis, debugging, and correctness tools, as well as tuning and optimization frameworks. The developed infrastructure provides a comprehensive and extensible set of individual tool building components. We started with the basic elements necessary across all tools in such an infrastructure followed by a set of generic core modules that allow a comprehensive performance analysis at scale. Further, we developed a methodology and workflow that allows others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In order to form the core modules, we built on the existing Open|SpeedShop infrastructure and decomposed it into individual modules that match the necessary tool components. At the same time, we addressed the challenges found in performance tools for petascale systems in each module. When assembled, this instantiation of community tool infrastructure provides an enhanced version of Open|SpeedShop, which, while completely different in its architecture, provides scalable performance analysis for petascale applications through a familiar interface. This project also built upon and enhances capabilities and reusability of project partner components as specified in the original project proposal. The overall project team’s work over the project funding cycle was focused on several areas of research, which are described in the following sections. The reminder of this report also highlights related work as well as preliminary work that supported the project. In addition to the project partners funded by the Office of Science under this grant, the project team included several collaborators who contribute to the overall design of the envisioned tool infrastructure. In particular, the project team worked closely with the other two DOE NNSA laboratories Los Alamos and Sandia leveraging co-funding for Krell by ASC’s Common Computing Environment (CCE) program as laid out in the original proposal. The ASC CCE co-funding, coordinated through LLNL, was for 50% of the total project funding, with the ASC CCE portion of the funding going entirely to Krell, while the ASCR funding itself was split between Krell and the funded partners. This report covers the entire project from both funding sources. Additionally, the team leveraged the expertise of software engineering researchers from Carnegie Mellon University, who specialize in software framework design, in order to achieve a broadly acceptable component framework. The Component Based Tool Framework (CBTF) software has been released to the community. Information related to the project and the released software can be found on the CBTF wiki page at: http://sourceforge.net/p/cbtf/wiki/Home.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluation of DUSTRAN Software System for Modeling Chloride Deposition on Steel Canisters

The degradation of steel by stress corrosion cracking (SCC) when exposed to atmospheric conditions for decades is a significant challenge in the fossil fuel and nuclear industries. SCC can occur when corrosive contaminants such as chlorides are deposited on a susceptible material in a tensile stress state. The Nuclear Regulatory Commission has identified chloride-induced SCC as a potential cause for concern in stainless steel used nuclear fuel (UNF) canisters in dry storage. The modeling of contaminant deposition is the first step in predictive multiscale modeling of SCC that is essential to develop mitigation strategies, prioritize inspection, and ensure the integrity and performance of canisters, pipelines, and structural materials. A multiscale simulation approach can be developed to determine the likelihood that a canister would undergo SCC in a certain period of time. This study investigates the potential of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to model the deposition of chloride contaminants from sea salt aerosols on a steel canister. Results from DUSTRAN simulations run with historical meteorological data were compared against measured chloride data at a coastal site in Maine. DUSTRAN’s CALPUFF model tended to simulate concentrations higher than those measured; however, the closest estimations were within the same order of magnitude as the measured values. The decrease in discrepancies between measured and simulated values as the level of abstraction in wind speed decreased suggest that the model is very sensitive to wind speed. However, the influence of other parameters such as the distinction between open-ocean and surf-zone sources needs to be explored further. Deposition values predicted by the DUSTRAN system were not in agreement with concentration values and suggest that the deposition calculations may not fully represent physical processes. Overall, results indicate that with parameter refinement, DUSTRAN has the potential to simulate atmospheric chloride dispersion on steel canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

SciPy 1.0: fundamental algorithms for scientific computing in Python

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-P-59: A Graphical Interface for XCAT Phantom Configuration, Generation and Processing

Purpose: To design a comprehensive open-source, publicly available, graphical user interface (GUI) to facilitate the configuration, generation, processing and use of the 4D Extended Cardiac-Torso (XCAT) phantom. Methods: The XCAT phantom includes over 9000 anatomical objects as well as respiratory, cardiac and tumor motion. It is widely used for research studies in medical imaging and radiotherapy. The phantom generation process involves the configuration of a text script to parameterize the geometry, motion, and composition of the whole body and objects within it, and to generate simulated PET or CT images. To avoid the need for manual editing or script writing, our MATLAB-based GUI uses slider controls, drop-down lists, buttons and graphical text input to parameterize and process the phantom. Results: Our GUI can be used to: a) generate parameter files; b) generate the voxelized phantom; c) combine the phantom with a lesion; d) display the phantom; e) produce average and maximum intensity images from the phantom output files; f) incorporate irregular patient breathing patterns; and f) generate DICOM files containing phantom images. The GUI provides local help information using tool-tip strings on the currently selected phantom, minimizing the need for external documentation. The DICOM generation feature is intended to simplify the process of importing the phantom images into radiotherapy treatment planning systems or other clinical software. Conclusion: The GUI simplifies and automates the use of the XCAT phantom for imaging-based research projects in medical imaging or radiotherapy. This has the potential to accelerate research conducted with the XCAT phantom, or to ease the learning curve for new users. This tool does not include the XCAT phantom software itself. We would like to acknowledge funding from MRA, Varian Medical Systems Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. In this report, we evaluate the performance of the kernel using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board. Compared to the M506 module, the board provides more hardware resources for a larger design exploration space. The kernel performance is measured with the compute kernel throughput, an upper bound to the FPGA throughput. The report presents the experimental results in details. The Appendix lists the kernel source code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Automatic Analyte-Ion Recognition and Background Removal for Ambient Mass-Spectrometric Data Based on Cross-Correlation

Ambient mass spectrometry is a powerful approach for rapid, high-throughput, and direct sample analysis. Due to the open-air desorption and ionization processes, random fluctuations of ambient conditions can lead to large variances in mass-spectral signals over time. The mass-spectral data also can be further complicated due to multiple analytes present in the sample, background-ion signals stemming from the desorption/ionization source itself, and other laboratory-specific conditions (e.g., ambient laboratory air, nearby hardware). Thus, background removal and analyte-ion recognition can be quite difficult, particularly in non-targeted analyses. Here, we demonstrate the use of a cross-correlation-based approach to exploit chemical information encoded in the time domain to group/categorize mass-spectral peaks from a single analysis dataset. Ions that originate from ambient (or other) background species were readily flagged and removed from spectra; the result was a decrease in mass-spectral complexity by over 70% due to the removal of these background ions. Meanwhile, analyte ions were differentiated and categorized based on their time-domain profiles. With sufficient mass resolving-power and mass-spectral acquisition rate, isolated mass spectra containing ions from the same species in a sample could be extracted, leading to a reduction in mass-spectral complexity by more than 98% in some cases. The cross-correlation approach was tested with different ionization sources as well as reproducible and irreproducible sample introduction. Software built in-house enabled fully automated data processing, which can be performed within a few seconds. Ultimately, this approach provides an additional dimension of analyte separation in ambient mass-spectrometric analyses with information that is already recorded throughout the analysis. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Numerical simulations of vertical growth of hydraulic fractures and brine migration in geological formations above the Marcellus shale

One of the critical environmental questions about hydraulic fracturing in shales is the potential for contamination of ground and surface water. There are two specific concerns arising from hydraulic treatments: 1) whether hydraulic fractures extend upward through overlying strata to reach overlying aquifers containing drinking water, and 2) whether injected fluids push native fluids upward into these overlying aquifers. In this work, the extent of likely fracture growth through overlying layers during hydraulic treatment of the Marcellus shale was estimated using a hydraulic fracture model. A wide range of material and fluid flow properties in a multi-layered geologic model was considered. The model was based on conditions and characteristics applicable to the Marcellus shale in that part of the Appalachian basin within southwestern Pennsylvania. Predictions of vertical termination frequencies for hydraulic fractures were used in a multi-layer model of the strata and natural fractures for studying brine migration through the natural and induced fracture network. NFFLOW, the software for explicitly modeling flow within networks of fractures, was utilized to compute transient flow rates according to the schedule of injected fluid during hydraulic fracturing. To aid our analysis, the modeled sequence of geologic strata was capped with a fictitious unfractured, but moderately-permeable layer, which serves as a monitoring zone. The analysis assumes one well lateral was placed in the middle of the Marcellus shale with hydraulic fractures penetrating layers in the model. The newly-developed geomechanical module within NFFLOW was used to represent stress-sensitivity of the fractures. This allows the opening and closing of fracture apertures with changes in fluid pressures within fracture segments. Pressure increases in the formations overlying the Tully limestone, indicating fluid flow, was observed due to the hydraulic stimulation; and the impact of these increased pressures on brine migration towards the surface was considered.

03 NATURAL GAS↗
DOE OSTI2024

Improving the User Interface of the DeepLynx Data Warehouse

DeepLynx is an open-source ontology-based data warehouse created by INL to support the creation and life cycle of digital engineering projects, with a particular emphasis on digital twins [1]. Digital twins are systems that represent physical assets and process in a real-time digital environment [1]. Most well-known commercial data warehouses use Graphical User Interfaces (GUIs) for users to interact with their systems [3]. Limited publications have addressed the design of these interfaces and understanding of their target users. The current users and development team acknowledge the need to improve the current UI, not just for aesthetics but to improve functionality and workflow of DeepLynx. Traditional data warehouse users are developers, data scientists and business analysts [2]. DeepLynx users have a vast range of experience using data warehouses, and diverse roles, including engineers, scientists and management positions. Because there is a broader audience of target users for DeepLynx than a typical data warehouse, it is essential that DeepLynx has a useable and intuitive user interface. To achieve this the team performed human-computer interaction methods, including a Heuristic Evaluation of current UI using Neilsen’s Usability Heuristic, create personas based on current users by designing a user survey, data analysis and develop of personas. Followed by a redesign of the UI following using Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design in industry standard software Figma. Lastly a Heuristic Evaluation of new UI design, using Neilsen’s Usability Heuristic and User testing of redesign UI and have a group of users complete a Thinking Aloud Test of the new UI. Preliminary results of the Heuristic Evaluation of current UI arise issue with Consistency and Standards, Visibility of System Status, Match System and Real World and Recognition Rather than Recall. These issues were addressed in the proposed redesign by applying Neilsen’s Usability Heuristic and Norman’s Principles of Interactive Design. Next steps include formalized list of lessons learned and design implications for future publications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrc package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗