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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-181: Proton Therapy Tissue-Equivalence of 3D Printed Materials

Purpose: This work investigated the proton tissue-equivalence of various 3D printed materials. Methods: Three 3D printers were used to create 5 cm cubic phantoms made of different plastics with varying percentages of infill. White resin, polylactic acid (PLA), and NinjaFlex plastics were used. The infills ranged from 15% to 100%. Each phantom was scanned with a CT scanner to obtain the HU value. The relative linear stopping power (RLSP) was then determined using a multi-layer ion chamber in a 200 MeV proton beam. The RLSP was measured both parallel and perpendicular to the print direction for each material. Results: The HU values of the materials ranged from lung-equivalent (−820 HU σ160) when using a low infill, to soft-tissue-equivalent 159 (σ12). The RLSP of the materials depended on the orientation of the beam relative to the print direction. When the proton beam was parallel to the print direction, the RLSP was generally higher than the RLSP in the perpendicular orientation, by up to 45%. This difference was smaller (less than 6%) for the materials with 100% infill. For low infill cubes irradiated parallel to the print direction, the SOBP curve showed extreme degradation of the beam in the distal region. The materials with 15–25% infill had wide-ranging agreement with a clinical HU-RLSP conversion curve, with some measurements falling within 1% of the curve and others deviating up to 45%. The materials with 100% infill all fell within 7% of the curve. Conclusion: While some materials tested fall within 1% of a clinical HU-RLSP curve, caution should be taken when using 3D printed materials with proton therapy, as the orientation of the beam relative to the print direction can result in a large change in RLSP. Further investigation is needed to measure how the infill pattern affects the material RLSP. This work was supported by PHS grant CA180803.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Preliminary results on the feasibility of using ultrasound to monitor intrafractional motion during radiation therapy for pancreatic cancer

Purpose: Substantial intrafraction organ motion during radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor for accurate delivery of RT. The aim of this work is to determine the feasibility of monitoring the intrafractional motion of the pancreas or surrounding structures using ultrasound for RT delivery. Methods: Transabdominal ultrasound (TAUS) and 4DCT data were acquired on ten pancreatic cancer patients during radiation therapy process in a prospective study. In addition, TAUS and MRI were collected for five healthy volunteers. The portal vein (PV) and the head of the pancreas (HP) along with other structures were contoured on these images. Volume changes, distance between the HP and PV, and motion difference between the HP and PV were measured to examine whether PV can be used as a motion surrogate for HP. TAUS images were acquired and processed using a research version of the Clarity autoscan ultrasound system (CAUS). Motion monitoring was performed with the ultrasound probe mounted on an arm fixed to the couch. Video segments of the monitoring sessions were captured. Results: On TAUS, PV is better visualized than HP. The measured mean volume deviation for all patients for the HP and PV was 1.4 and 0.6 ml, respectively. The distance between the HP and PV was close to a constant with 0.22 mm mean deviation throughout the ten breathing phases. The mean of the absolute motion difference for all patients was 1.7 ± 0.8 mm in LR, 1.5 ± 0.5 mm in AP, and 2.3 ± 0.7 mm in SI, suggesting that the PV is a good surrogate for HP motion estimation. By using this surrogate, the HP motion tracking using TAUS was demonstrated. Conclusions: Large intrafractional organ motion due to respiratory and/or bowel motion is a limiting factor in administering curative radiation doses to pancreatic tumors. The authors investigate the use of real-time ultrasound to track pancreas motion. Due to the poor visibility of the pancreas head on an ultrasound image, the portal vein is identified as a surrogate. The authors have demonstrated the feasibility of tracking HP motion through the localization of the PV using TAUS. This will potentially allow real-time tracking of intrafractional motion to justify small PTV-margins and to account for unusual motions, thus, improving normal tissue sparing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Multi-channel search for squarks and gluinos in $\sqrt{s}=7\mbox{ TeV}$ pp collisions with the ATLAS detector at the LHC

A search for supersymmetric particles in final states with zero, one, and two leptons, with and without jets identified as originating from b-quarks, in 4.7 fb -1 of √s=7 TeV pp collisions produced by the Large Hadron Collider and recorded by the ATLAS detector is presented. The search uses a set of variables carrying information on the event kinematics transverse and parallel to the beam line that are sensitive to several topologies expected in supersymmetry. Mutually exclusive final states are defined, allowing a combination of all channels to increase the search sensitivity. No deviation from the Standard Model expectation is observed. Upper limits at 95 % confidence level on visible cross-sections for the production of new particles are extracted. Results are interpreted in the context of the constrained minimal supersymmetric extension to the Standard Model and in supersymmetry-inspired models with diverse, high-multiplicity final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

TU-F-CAMPUS-J-04: Setup Uncertainties in the Mediastinum Area for IMRT Treatment of Lymphoma Patients

Purpose: Despite daily image guidance setup uncertainties can be high when treating large areas of the body. The aim of this study was to measure local uncertainties inside the PTV for patients receiving IMRT to the mediastinum region. Methods: Eleven lymphoma patients that received radiotherapy (breath-hold) to the mediastinum were included in this study. The treated region could range all the way from the neck to the diaphragm. Each patient had a CT scan with a CT-on-rails system prior to every treatment. The entire PTV region was matched to the planning CT using automatic rigid registration. The PTV was then split into 5 regions: neck, supraclavicular, superior mediastinum, upper heart, lower heart. Additional auto-registrations for each of the 5 local PTV regions were performed. The residual local setup errors were calculated as the difference between the final global PTV position and the individual final local PTV positions for the AP, SI and RL directions. For each patient 4 CT scans were analyzed (1 per week of treatment). Results: The residual mean group error (M) and standard deviation of the inter-patient (or systematic) error (Σ) were lowest in the RL direction of the superior mediastinum (0.0mm and 0.5mm) and highest in the RL direction of the lower heart (3.5mm and 2.9mm). The standard deviation of the inter-fraction (or random) error (σ) was lowest in the RL direction of the superior mediastinum (0.5mm) and highest in the SI direction of the lower heart (3.9mm) The directionality of local uncertainties is important; a superior residual error in the lower heart for example keeps it in the global PTV. Conclusion: There is a complex relationship between breath-holding and positioning uncertainties that needs further investigation. Residual setup uncertainties can be significant even under daily CT image guidance when treating large regions of the body.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Influence of regional nighttime atmospheric regimes on canopy turbulence and gradients at a closed and open forest in mountain-valley terrain

Stable stratification of the nocturnal lower boundary layer inhibits convective turbulence, such that turbulent vertical transfer of ecosystem carbon dioxide (CO 2 ), water vapor (H 2 O) and energy is driven by mechanically forced turbulence, either from frictional forces near the ground or top of a plant canopy, or from shear generated aloft. The significance of this last source of turbulence on canopy flow characteristics in a closed and open forest canopy is addressed in this paper. We present micrometeorological observations of the lower boundary layer and canopy air space collected on nearly 200 nights using a combination of atmospheric laser detection and ranging (lidar), eddy covariance (EC), and tower profiling instrumentation. Two AmeriFlux/Fluxnet sites in mountain-valley terrain in the Western U.S. are investigated: Wind River, a tall, dense conifer canopy, and Tonzi Ranch, a short, open oak canopy. On roughly 40% of nights lidar detected down-valley or downslope flows above the canopy at both sites. Nights with intermittent strong bursts of “top-down” forced turbulence were also observed above both canopies. The strongest of these bursts increased sub-canopy turbulence and reduced canopy virtual potential temperature (θv) gradient at Tonzi, but did not appear to change the flow characteristics within the dense Wind River canopy. At Tonzi we observed other times when high turbulence (via friction velocity, u*) was found just above the trees, yet CO2 and θv gradients remained large and suggested flow decoupling. These events were triggered by regional downslope flow. Lastly, a set of turbulence parameters is evaluated for estimating canopy turbulence mixing strength. The relationship between turbulence parameters and canopy θv gradients was found to be complex, although better agreement between the canopy θv gradient and turbulence was found for parameters based on the standard deviation of vertical velocity, or ratios of 3-D turbulence to mean flow, than for u*. These findings add evidence that the relationship between canopy turbulence, static stability, and canopy mixing is far from straightforward even within an open canopy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Electrical anisotropy and coexistence of structural transitions and superconductivity in IrT e 2

In this work, we report experimental investigations of the electrical transport, magnetic, and thermodynamic properties of IrTe 2 single crystals. The resistivity, magnetization, and specific heat display anomalies at T S1 ≈ 283K,T S2 ≈ 167K, and T c ≈2.5K, corresponding to two structural and one superconducting phase transitions, respectively, demonstrating the coexistence of all of these transitions in high-quality stoichiometric samples. While there is little magnetic anisotropy, a large ab-plane (ρab) and c-axis (ρc) electrical resistivity ratio (ρ c /ρ ab ≈730 at T=4K) is observed. This two-dimensional (2D) electronic character is further reflected in the disparate temperature dependences of ρ ab and ρ c , with ρab exhibiting a Fermi-liquid-like T 2 dependence below ~25K, while ρc deviates significantly from this standard metallic behavior. In contrast, the magnetization is almost isotropic and negative over a wide temperature range. Furthermore, this can be explained by larger diamagnetism induced by electronic structure reconstruction as probed by the Hall effect and smaller positive contribution from itinerant electrons due to a low density of states (DOS) at the Fermi level. A small electronic specific heat coefficient with γ ≈ 1.8mJ/molK 2 confirms this assertion. This implies that IrTe 2 is a weakly coupled superconductor. The connection between the superconductivity and the two structural transitions is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-T-427: Cell Surviving Fractions Derived From Tumor-Volume Variation During Radiotherapy for Non-Small Cell Lung Cancer: Comparison with Predictive Assays

Purpose: To show that a distribution of cell surviving fractions S{sub 2} in a heterogeneous group of patients can be derived from tumor-volume variation curves during radiotherapy for non-small cell lung cancer. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage (MV) computed tomography (CT). Statistical distributions of cell surviving fractions S{sup 2} and cell clearance half-lives of lethally damaged cells T1/2 have been reconstructed in each patient group by using a version of the two-level cell population tumor response model and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Non-small cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S{sub 2} for non-small cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S{sup 2} reconstructed from tumor volume variation agree with the PDF measured in vitro. Comparison of the reconstructed cell surviving fractions with patient survival data shows that the patient survival time decreases as the cell surviving fraction increases. Conclusion: The data obtained in this work suggests that the cell surviving fractions S{sub 2} can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. This means that the majority of our estimates are within 6.5 minutes of the actual wait time. Conclusion: The goal of this project was to define an appropriate machine learning algorithm to estimate waiting times based on the collective knowledge and experience learned from previous patients. Our results offer an opportunity to improve the information that is provided to patients and family members regarding the amount of time they can expect to wait for radiotherapy treatment at our centre. AJ acknowledges support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and from the 2014 Q+ Initiative of the McGill University Health Centre.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗
DOE OSTI2016

Speeding up equation of motion coupled cluster theory with the chain of spheres approximation

In the present paper, the chain of spheres exchange (COSX) approximation is applied to the highest scaling terms in the equation of motion (EOM) coupled cluster equations with single and double excitations, in particular, the terms involving integrals with four virtual labels. It is found that even the acceleration of this single term yields significant computational gains without compromising the desired accuracy of the method. For an excitation energy calculation on a cluster of five water molecules using 585 basis functions, the four virtual term is 9.4 times faster using COSX with a loose grid than using the canonical implementation, which yields a 2.6 fold acceleration for the whole of the EOM calculation. For electron attachment calculations, the four virtual term is 15 times and the total EOM calculation is 10 times faster than the canonical calculation for the same system. The accuracy of the new method was tested using Thiel’s test set for excited states using the same settings and the maximum absolute deviation over the whole test set was found to be 12.945 cm{sup −1} (59 μHartree) for excitation energies and 6.799 cm{sup −1} (31 μHartree) for electron attachments. Using MP2 amplitudes for the ground state in combination with the parallel evaluation of the full EOM equations in the manner discussed in this paper enabled us to perform calculations for large systems. Electron affinity values for the two lowest states of a Zn protoporphyrine model compound (224 correlated electrons and 1120 basis functions) were obtained in 3 days 19 h using 4 cores of a Xeon E5-2670 processor allocating 10 GB memory per core. Calculating the lowest two excitation energies for trans-retinal (114 correlated electrons and 539 basis functions) took 1 day 21 h using eight cores of the same processor and identical memory allocation per core.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Impurity induced confinement effects in size-separated Mn-doped CsPbCl 3 nanocrystals

Beyond quantum confinement, impurity doping of semiconductor nanocrystals (NCs) offers a degree of control over their optical and electronic properties, which are of interest for potential applications. Manganese (Mn)-doped CsPbCl 3 NCs, for example, show synergistic effects in the visible, with large enhancements in both blue (exciton) and red (dopant) emission over a narrow range of dopant concentration. Although Mn concentration is the primary parameter, NC size offers an additional degree of control over the number of dopants per NC. Size-resolved CsPbCl 3 NCs prepared in the limit of strong Mn doping highlight the emergence of defective NCs with deviations from anticipated confinement trends. In conclusion, the transition correlates with a redshift and increase in the amplitude of dopant emission, and we discuss these observations in the context of atomistic simulations of Ruddlesden-Popper defects in CsPbCl 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2016

WE-DE-207B-10: Library-Based X-Ray Scatter Correction for Dedicated Cone-Beam Breast CT: Clinical Validation

Purpose: Scatter contamination is detrimental to image quality in dedicated cone-beam breast CT (CBBCT), resulting in cupping artifacts and loss of contrast in reconstructed images. Such effects impede visualization of breast lesions and the quantitative accuracy. Previously, we proposed a library-based software approach to suppress scatter on CBBCT images. In this work, we quantify the efficacy and stability of this approach using datasets from 15 human subjects. Methods: A pre-computed scatter library is generated using Monte Carlo simulations for semi-ellipsoid breast models and homogeneous fibroglandular/adipose tissue mixture encompassing the range reported in literature. Projection datasets from 15 human subjects that cover 95 percentile of breast dimensions and fibroglandular volume fraction were included in the analysis. Our investigations indicate that it is sufficient to consider the breast dimensions alone and variation in fibroglandular fraction does not significantly affect the scatter-to-primary ratio. The breast diameter is measured from a first-pass reconstruction; the appropriate scatter distribution is selected from the library; and, deformed by considering the discrepancy in total projection intensity between the clinical dataset and the simulated semi-ellipsoidal breast. The deformed scatter-distribution is subtracted from the measured projections for scatter correction. Spatial non-uniformity (SNU) and contrast-to-noise ratio (CNR) were used as quantitative metrics to evaluate the results. Results: On the 15 patient cases, our method reduced the overall image spatial non-uniformity (SNU) from 7.14%±2.94% (mean ± standard deviation) to 2.47%±0.68% in coronal view and from 10.14%±4.1% to 3.02% ±1.26% in sagittal view. The average contrast to noise ratio (CNR) improved by a factor of 1.49±0.40 in coronal view and by 2.12±1.54 in sagittal view. Conclusion: We demonstrate the robustness and effectiveness of a library-based scatter correction method using patient datasets with large variability in breast dimensions and composition. The high computational efficiency and simplicity in implementation make this attractive for clinical implementation. Supported partly by NIH R21EB019597, R21CA134128 and R01CA195512.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Analysis of Nonlinear Dynamics by Square Matrix Method

The nonlinear dynamics of a system with periodic structure can be analyzed using a square matrix. In this paper, we show that because the special property of the square matrix constructed for nonlinear dynamics, we can reduce the dimension of the matrix from the original large number for high order calculation to low dimension in the first step of the analysis. Then a stable Jordan decomposition is obtained with much lower dimension. The transformation to Jordan form provides an excellent action-angle approximation to the solution of the nonlinear dynamics, in good agreement with trajectories and tune obtained from tracking. And more importantly, the deviation from constancy of the new action-angle variable provides a measure of the stability of the phase space trajectories and their tunes. Thus the square matrix provides a novel method to optimize the nonlinear dynamic system. The method is illustrated by many examples of comparison between theory and numerical simulation. Finally, in particular, we show that the square matrix method can be used for optimization to reduce the nonlinearity of a system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Collaborative Research: Multi-scale Dynamics of Kinetic Turbulence in Weakly Collisional, High-Beta Plasmas

The transport of energy and momentum and the heating of plasma particles by waves and turbulence are key ingredients in many problems at the frontiers of heliospheric and astrophysics research. This includes the heating and acceleration of the solar wind; the observational appearance of black-hole accretion flows on event-horizon scales; and the properties of the hot, diffuse plasmas that fill dark-matter halos. This work addressed the physics of plasma waves and turbulence in weakly collisional, weakly magnetized (high-beta) plasmas. In this regime, deviations from local thermodynamic equilibrium (i.e., pressure anisotropies) and the instabilities they excite can dramatically change the properties of waves and turbulence from those predicted by fluid (i.e., magnetohydrodynamic) and linear kinetic theories. Through a combination of analytic theory and first-principles kinetic simulations, we have shown that: (1) ion-acoustic waves of sufficient amplitude drive pressure anisotropies large enough to trigger kinetic Larmor-scale instabilities, which in turn interrupt the otherwise strong collisionless damping such waves suffer; (2) pressure anisotropies generated by fluctuating magnetic fields in strong Alfvénic turbulence produce a viscous scale comparable to the driving scale and a cascade with significant non-local interactions; (3) strong Alfvénic turbulence in an expanding high-beta plasma self-organizes to maintain critical balance, even as kinetic Larmor-scale instabilities regulate the plasma viscosity and reduce the elasticity of magnetic-field lines; (4) imbalanced Alfvénic turbulence leads to a "helicity barrier" that ultimately triggers the cyclotron heating of ions, in a manner consistent with spacecraft measurements taken in the solar wind; and (5) relativistic synchrotron-radiating plasmas develop kinetically unstable pressure anisotropy, which changes the nature of their cooling in a way that can couple the thermodynamics of ions and electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Evaluation of the dosimetric properties of a synthetic single crystal diamond detector in high energy clinical proton beams

Purpose: To investigate the dosimetric properties of a synthetic single crystal diamond Schottky diode for accurate relative dose measurements in large and small field high-energy clinical proton beams.Methods: The dosimetric properties of a synthetic single crystal diamond detector were assessed by comparison with a reference Markus parallel plate ionization chamber, an Exradin A16 microionization chamber, and Exradin T1a ion chamber. The diamond detector was operated at zero bias voltage at all times. Comparative dose distribution measurements were performed by means of Fractional depth dose curves and lateral beam profiles in clinical proton beams of energies 155 and 250 MeV for a 14 cm square cerrobend aperture and 126 MeV for 3, 2, and 1 cm diameter circular brass collimators. ICRU Report No. 78 recommended beam parameters were used to compare fractional depth dose curves and beam profiles obtained using the diamond detector and the reference ionization chamber. Warm-up/stability of the detector response and linearity with dose were evaluated in a 250 MeV proton beam and dose rate dependence was evaluated in a 126 MeV proton beam. Stem effect and the azimuthal angle dependence of the diode response were also evaluated.Results: A maximum deviation in diamond detector signal from the average reading of less than 0.5% was found during the warm-up irradiation procedure. The detector response showed a good linear behavior as a function of dose with observed deviations below 0.5% over a dose range from 50 to 500 cGy. The detector response was dose rate independent, with deviations below 0.5% in the investigated dose rates ranging from 85 to 300 cGy/min. Stem effect and azimuthal angle dependence of the diode signal were within 0.5%. Fractional depth dose curves and lateral beam profiles obtained with the diamond detector were in good agreement with those measured using reference dosimeters.Conclusions: The observed dosimetric properties of the synthetic single crystal diamond detector indicate that its behavior is proton energy independent and dose rate independent in the investigated energy and dose rate range and it is suitable for accurate relative dosimetric measurements in large as well as in small field high energy clinical proton beams.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Observation of VVZ production at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for the production of three massive vector bosons, VVZ(V = W, Z) , in proton-proton collisions at $\sqrt{s}$ = 13 TeV is performed using data with an integrated luminosity of 140 fb -1 recorded by the ATLAS detector at the Large Hadron Collider. Events produced in the leptonic final states WWZ → ℓvℓvℓℓ (ℓ = e,μ), WZZ → ℓvℓℓℓℓ, ZZZ → ℓℓℓℓℓ, and the semileptonic final states WWZ → qq ℓvℓℓ and WZZ → ℓv qq ℓℓ, are analysed. The measured cross section for the pp → VVZ process is 660$^{+93}_{-90}$(stat.)$^{+80}_{-81}$(syst.) fb, and the observed (expected) significance is 6.4 (4.7) standard deviations, representing the observation of VVZ production. In addition, the measured cross section for the pp → WWZ process is 442 ± 94(stat.)$^{+60}_{-52}$(syst.) fb, and the observed (expected) significance is 4.4 (3.6) standard deviations, representing evidence of WWZ production. The measured cross sections are consistent with the Standard Model predictions. Constraints on physics beyond the Standard Model are also derived in the effective field theory framework by setting limits on Wilson coefficients for dimension-8 operators describing anomalous quartic gauge boson couplings.

Aad, G. (ORCID:0000000266654934)↗
DOE OSTI2025

Data Set Analysis to Reduce Uncertainty in Formula Assignments of Ultrahigh Resolution Mass Spectra

Environmental samples contain a vast array of organic compounds with diverse elemental compositions and heteroatom content. Molecular formula assignments of ultrahigh resolution mass spectra (HRMS) hold promise for elucidating the molecular composition of these compounds. However, the need to account for an assortment of heteroatoms increases the uncertainty associated with individual assignments – and ultimately the ecological, biological, and biogeochemical insights gleaned from the assignments. To address this challenge, we introduce a formula assignment strategy that leverages HRMS data sets to improve assignment confidence, filter false assignments, and mitigate bias in assignment routines. The strategy, implemented using CoreMS, first identifies the highest confidence assignment for a recurring ion in a data set by assessing the mass accuracy and isotopologue similarity of all assignments to the ion across the data set. The second component of the strategy examines the consistency of mass errors for an assigned ion throughout a data set and flags formulas with statistically unlikely deviations in mass error. Here, we illustrate the application and utility of the strategy by comparing its results against documented misassignment patterns within a set of oceanographic samples that were measured with 21 T Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Because the efficacy of our strategy improves with data set size, it is particularly useful for enhancing assignment confidence in large HRMS data sets common in studies of environmental systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗