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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Residual loss due to magnetic flux trapping in niobium superconducting microwave cavities

One of the significant source of radio frequency loss in superconducting microwave cavities is the trapped residual magnetic field during the cooldown due to the incomplete Messier effect. The sensitivity of flux trapping depends on the distribution of impurities, network of dislocations and defects which pin vortices. Recent advancement in cavity processing techniques resulted in very high quality factors with impurity doping, however the rf loss related to the flux trapping increases. High quality factor in SRF cavities is not only limited to particle accelerators but also emerging as an application to quantum computing and quantum information science. In this presentation, we present the results of measurements of flux trapping sensitivity on several 1.3 GHz elliptical accelerating cavities with different grain size, impurity content and surface preparations.

Dhakal, P.↗
DOE OSTI2014

Pressure solution creep of random packs of spheres

Abstract We performed numerical calculations of compaction in aggregates of spherical grains, using Lehner and Leroy's (2004, hereinafter LL) constitutive model of pressure solution at grain contacts. That model is founded on a local definition of the thermodynamic driving force and leads to a fully coupled formulation of elastic deformation, dissolution, and diffusive transport along the grain boundaries. The initial geometry of the aggregate was generated by random packing of spheres with a small standard deviation of the diameters. During the simulations, isostatic loading was applied. The elastic displacements at the contacts were calculated according to Digby's (1981) nonlinear contact force model, and deformation by dissolution was evaluated using the LL formulation. The aggregate strain and porosity were tracked as a function of time for fixed temperature, applied effective pressure, and grain size. We also monitored values of the average and standard deviation of total load at each contact, the coordination number for packing, and the statistics of the contact dimensions. Because the simulations explicitly exclude processes such as fracturing, plastic flow, and transport owing to surface curvature, they can be used to test the influence of relative changes in the kinetics of dissolution and diffusion processes caused by contact growth and packing rearrangements. We found that the simulated strain data could be empirically fitted by two successive power laws of the form, ε x ∝ t ξ , where ξ was equal to 1 at very early times, but dropped to as low as 0.3 at longer times. The apparent sensitivity of strain rate to stress found in the simulations was much lower than predicted from constitutive laws that assume a single dominant process driven by average macroscopic loads. Likewise, the apparent activation enthalpy obtained from the simulated data was intermediate between that assumed for dissolution and diffusion, and, further, tended to decrease with time. These results are similar to the experimental observations of Visser et al.'s (2012), who used an aggregate geometry and physical conditions closely resembling the present numerical simulations.

Bernabé, Y.↗
DOE OSTI2019

Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT

Purpose: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses. Methods: With institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution’s pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes. Results: We analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8–14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0–13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%. Conclusions: The best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A structural map of oncomiR-1 at single-nucleotide resolution

The miR-17–92a cluster, also known as ‘oncomiR-1’, is an RNA transcript that plays a pivotal regulatory role in cellular processes, including the cell cycle, proliferation and apoptosis. Its dysregulation underlies the development of several cancers. Oncomir-1 comprises six constituent miRNAs, each processed with different efficiencies as a function of both developmental time and tissue type. The structural mechanisms that regulate such differential processing are unknown, and this has impeded our understanding of the dysregulation of oncomiR-1 in pathophysiology. By probing the sensitivity of each nucleotide in oncomiR-1 to reactive small molecules, we present a secondary structural map of this RNA at single-nucleotide resolution. The secondary structure and solvent accessible regions of oncomiR-1 reveal that most of its primary microRNA domains are suboptimal substrates for Drosha-DGCR8, and therefore resistant to microprocessing. The structure indicates that the binding of trans-acting factors is required to remodel the tertiary organization and unmask cryptic primary microRNA domains to facilitate their processing into pre-microRNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Preliminary Cryogenic Cold Test Results of the First 9-Cell LSF Shape Cavity

Following successful prototyping and testing of single- & 5-cell LSF shape cavities *, **, the first 9-cell LSF shape cavity LSF9-1 was successfully constructed using an innovative process at JLab with the in-house facilities. The cavity was then shipped to KEK for post-fabrication mechanical adjustment and ILC TDR style treatment and surface processing. Cold testing was carried out at the JLab VTA facility, instrumented with a suite of Kyoto instruments. Favorable values for the bath pressure detuning sensitivity and Lorentz force detuning coefficient were experimentally measured, validating the design improvement in cell stiffeners. Pass-band measurements indicate 4 out of 9 cells reaching gradient capability of > 45 MV/m, including 2 cells reaching 51 MV/m. Cornell OST detectors identified the cell and location responsible for the current hard quench limit. Multipacting-like barriers observed in end cells are investigated both analytically and numerically. The cavity was shipped to FNAL and received a light EP at the joint ANL/FNAL facility for further cold testing at Jlab. Two new 9-cell LSF cavities are being constructed including one made of large-grain niobium material.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Analysis of Radioactive Waste and Contamination using 3D Position-Sensitive CdZnTe Detectors

INTRODUCTION The US has surplus plutonium. This material will be diluted in gloveboxes at SRS [Ref 1 and 2]. This process will create holdup. Holdup is material in an unexpected or unwanted location. Because this holdup material is primarily PuO2, it must be accounted for (measured). This measurement is typically done using a liquid-nitrogen cooled, HPGe detector. To enable more rapid processing, advanced holdup technologies are being explored [Ref 3 and 4]. METHODS For the surplus plutonium dilute and dispose program, the traditional detector system could slow down the optimal operational tempo of the program. A multiple-detector system, providing complete glovebox coverage, based on CdZnTe crystals, 3D-positioning electronics, and a coded aperture mask, is in the process of being developed by ORNL and SRNL [Ref 4].

Whiteside, Tad [Savannah River National Laboratory↗
DOE OSTI2025

Signal processing and spectral modeling for the BeEST experiment

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of 7 Be by precisely measuring the recoil energy of the 7 Li daughter. In Phase III, the BeEST experiment has been scaled from a singl superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. Here, we have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large datasets. Furthermore, this article presents the optimized procedures before unblinding the majority of the Phase III dataset to search for physics beyond the standard model.

6 ≤ A ≤ 19↗
DOE OSTI2015

Numerical Simulation of Big Area Additive Manufacturing (3D Printing) of a Full Size Car

Distortion and buildup of residual stresses are common design problems in structures manufactured using additive manufacturing techniques, popularly known as 3D printing. These problems lead to poor product quality, which often is improved by trial and error, where the sensitivity of different manufacturing configurations to product quality are experimentally determined. With the introduction of Big Area Additive Manufacturing (BAAM), where significant amount of material is deposited per unit time, trial and error philosophy reduces the economical efficiency of the process. In this work, a numerical simulation methodology based on Finite Element Method (FEM), multi-scale damage mechanics and fracture mechanics is introduced to simulate the BAAM process for determining product quality in terms of distortions, material damage and interface fracture due to manufacturing. In addition, this tool can be used to obtain the sensitivities of the manufacturing configurations with respect to product quality in an economically efficient manner compared to the trial and error philosophy. Computational tools providing a fully coupled thermo-mechanical solution of polymer additive manufacturing with chopped fiber reinforced plastics are presented.

42 ENGINEERING↗
DOE OSTI2015

Plastic Scintillators Light Yield Energy Calibration.

Currently we are investigating the inclusion of organotin compounds in polystyrene material to improve plastic scintillators full gamma-ray energy sensitivity with the ultimate goal of achieving spectroscopy. Accurate evaluation of light yield from the newly developed scintillators is crucial to assess merits of compounds and chemical process used in the scintillators development. Full gamma-ray energy peak in measured gammaray spectrum, resulting from total absorption of gamma-ray energy, would be ideal in evaluating the light yield from the new scintillators. However, full energy sensitivity achieved thus far is not statistically viable for fast and accurate light yield energy calibration from the new scintillators. The Compton edge in measured gamma-ray spectrum has been found as an alternate gamma-ray spectrum feature that can be exploited for characterizing the light yield energy from the newly developed plastic scintillators. In this study we present technique implemented for accurate light yield energy calibration using the Compton edge. Results obtained were very encouraging and promise the possibility of using the Compton edge for energy calibration in detectors with poor energy resolution such as plastic and liquid scintillators.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Drop size distribution broadening mechanisms in a bin microphysics Eulerian model

In this study, processes that broaden drop size distributions (DSDs) in Eulerian models with two-moment bin microphysics are analyzed. Numerous tests are performed to isolate the effects of different physical mechanisms that broaden DSDs in two- and three-dimensional Weather Research and Forecasting model simulations of an idealized ice-free cumulus cloud. Additionally, sensitivity of these effects to modifying horizontal and vertical model grid spacings is also examined. As expected, collision-coalescence is a key process broadening the modeled DSDs. In-cloud droplet activation also contributes substantially to DSD broadening, whereas evaporation has only a minor effect and sedimentation has little effect. Cloud dilution (mixing of cloud-free and cloudy air) also broadens the DSDs considerably, whether or not it is accompanied by evaporation. This mechanism involves the reduction of droplet concentration from dilution along the cloud’s lateral edges, leading to locally high supersaturation and enhanced drop growth when this air is subsequently lifted in the updraft. DSD broadening ensues when the DSDs are mixed with those from the cloud core. Decreasing the horizontal and vertical model grid spacings from 100 m to 30 m has limited impact on the DSDs. However, when these physical broadening mechanisms (in-cloud activation, collision-coalescence, dilution, etc.) are turned off, there is a reduction of DSD width by up to ~20-50% when the vertical grid spacing is decreased from 100 m to 30 m, consistent with effects of artificial broadening from vertical numerical diffusion. Nonetheless, this artificial numerical broadening appears to be relatively unimportant overall for DSD broadening when physically based broadening mechanisms in the model are included for this cumulus case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Toward a sustainable circular economy of multilayer plastic films: Life cycle and techno-economic assessment with a focus on end-of-life treatment and multiple recovery cycles

This study presents a life cycle assessment (LCA) and techno-economic analysis (TEA) of end-of-life technologies for treating polyethylene–polyamide barrier film waste, focusing on quality degradation across recovery cycles. Novel treatment methods are experimentally validated, while others are drawn from literature and industry consultations. A displacement approach, assuming no quality loss, is first applied. Results show that solvent-based recycling via the solvent-targeted recovery and precipitation (STRAP) process outperforms alternatives across environmental indicators, reducing global warming potential (GWP) by 40% compared to landfilling. Incineration performs worst in most categories, particularly eutrophication (80% higher than landfilling), due to nitrogen emissions. Experimentally validated downcycling (pelletizing) proves more economically viable. The assumption of infinite recoverability is overly optimistic. To address this, we propose a mathematical framework accounting for a finite number of recovery cycles. This refined model shows reduced GWP and cost savings for solvent recovery, making its benefits less pronounced than initially estimated. Sensitivity and uncertainty analyses reveal strong dependence on recovered material quality and solvent recovery efficiency, underscoring the need for optimized process design. Finally, hotspot analysis identifies greenhouse gas emissions from the polyamide supply chain as the dominant GWP contributor. In conclusion, the results underscore potential trade-offs across pathways and show that solvent-based recovery’s sustainability depends heavily on process conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

WIPP PA Sensitivity Studies in Support of CRA-2014 Completeness Determination and Compliance Decision - 18209

The Waste Isolation Pilot Plant (WIPP) has been developed by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. Containment of TRU waste at the WIPP is regulated by the U.S. Environmental Protection Agency (EPA). The DOE demonstrates compliance with the containment requirements by means of performance assessment (PA) calculations. WIPP PA calculations estimate the probability and consequence of potential radionuclide releases from the repository to the accessible environment for a regulatory period of 10,000 years after facility closure. Since TRU waste was first received at the WIPP in 1999, compliance recertification applications (CRAs) have been required by the EPA on five-year cycle. The latest CRA (CRA-2014) was submitted by the DOE to the EPA in 2014. As part of the application, a formal set of PA calculations (CRA-2014 PA) was performed and results were documented in detail. The CRA-2014 PA incorporated several parameter updates based on new data, as well as the implementation of a different model for panel closures, barriers planned for the opening of each waste panel. The results presented as part of the CRA-2014 showed via the required complementary cumulative distribution function (CCDF) release curves that the estimated releases were within compliance limits. As part of their process for reviewing the completeness of the CRA-2014 [1], the EPA formally requested that the DOE perform sensitivity studies based on EPA-requested changes to model parameters. The DOE performed and documented the results of three sensitivity studies described below: CRA14-SEN2 [2], CRA14-SEN3 [3], and CRA14-SEN4 [4]. In each case, the new analysis results were compared to CRA- 2014 PA (CRA14) results to determine the impact of the EPA-requested changes. CRA14-SEN2: the application of EPA-requested modified parameters in the operations and experimental (non-waste) areas of the repository to simulate an accelerated (instantaneous) creep closure, the inclusion of capillary pressure effects on relative permeability, and an increase in initial/residual brine saturation and residual gas saturation. The modifications to the repository model resulted in increased pressures and decreased brine saturations in waste areas and increased pressures and brine saturations in the operations and experimental areas. However, the overall effects on total high-probability mean releases from the repository were entirely insignificant. It was concluded that the modeling assumptions associated with the operations and experimental areas of the repository have an insignificant effect on the prediction of total releases from the repository and/or adequacy of the current (CRA14) model to demonstrate compliance with the regulatory limits. CRA14-SEN3: the application of EPA-requested modified parameters in the panel closure areas and operations and experimental (non-waste) areas of the repository to simulate an accelerated (instantaneous) creep closure, the inclusion of capillary pressure effects on relative permeability, and an increase in initial/residual brine saturation and residual gas saturation. The modifications to the repository model predominantly result in increased pressures and decreased brine saturations in waste areas, increased pressures and brine saturations in the operations and experimental areas, and decreased brine and gas flows across all panel closures. The pressure increases in repository waste regions yielded slightly decreased brine saturations (on average) in those areas. However, the overall effects on total high-probability mean releases from the repository are entirely insignificant. It was concluded that the modeling assumptions made for this sensitivity study which were associated with the panel closures and north end areas of the repository have only a small effect on the prediction of total releases from the repository and/or adequacy of the current (CRA14) model to demonstrate compliance with the regulatory limits. CRA14-SEN4: the application of several changes to the current WIPP PA model (CRA14), including: parameter changes, use of an updated code, and a revised computational grid for the BRAGFLO code. The modifications to the repository model resulted in increased releases in all primary release mechanisms. The impacts of each EPA-requested change to CRA14 were analyzed with respect to each release mechanism in the CRA14-SEN4 study. Overall, total high-probability predicted mean releases from the repository were increased by about 15%. Total low-probability predicted mean releases were increased by about 107%. It was concluded that the EPA-requested changes to the CRA14 result in increases to the predicted total releases from the repository. However, releases calculated in the CRA14-SEN4 analysis remained below regulatory limits, demonstrating continued compliance of the WIPP. In January 2017, the EPA determined that CRA-2014 was complete and then began a technical evaluation of CRA-2014 to determine whether the WIPP continued to comply with the radiation protection standards for disposal. During their evaluation, the EPA utilized the sensitivity study results to inform their ultimate determination in July 2017 that the WIPP continues to comply with regulatory standards. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

A Charge Sensitive Pre-Amplifier for Smart Point-of-Care Devices Employing Polymer Based Lab-on-a-Chip

With increasing emphasis on implantable and portable medical devices, low-power, small-chip-area sensor readout system realized in lab-on-a-chip (LOC) platform is gaining more and more importance these days. The main building blocks of the LOC system include a front-end transducer that generates an electrical signal in response to the presence of an analyte of interest, signal processing electronics to process the signal to comply with a specific transmission protocol and a low-power transmitter, all realized in a single integrated circuit platform. Low power consumption and compactness of the components are essential requirements of the LOC system. This paper presents a novel charge sensitive pre-amplifier developed in a standard 180-nm CMOS process suitable for implementing in an LOC platform. The pre-amplifier converts the charge generated by a pyroelectric transducer into a voltage signal, which provides a measurement of the temperature variation in biological fluids. The proposed design is capable of providing 0.8-mV/pC gain while consuming only 2.1 μW of power. Finally, the pre-amplifier composed of integrated components occupies an area of 0.038 mm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2019

High spatial resolution imaging of biological tissues using nanospray desorption electrospray ionization mass spectrometry

Mass spectrometry imaging (MSI) enables label-free spatial mapping of hundreds of biomolecules in tissue sections. This capability provides valuable information on tissue heterogeneity that is difficult to obtain using population-averaged assays. Despite substantial developments in both instrumentation and methodology, MSI of tissue samples at single-cell resolution remains challenging. In our research, we describe a protocol for robust imaging of tissue sections with a high (better than 10-μm) spatial resolution using nanospray desorption electrospray ionization (nano-DESI) mass spectrometry, an ambient ionization technique that does not require sample pretreatment before analysis. In this protocol, mouse uterine tissue is used as a model system to illustrate both the workflow and data obtained in these experiments. We provide a detailed description of the nano-DESI MSI platform, fabrication of the nano-DESI and shear force probes, shear force microscopy experiments, spectral acquisition, and data processing. A properly trained researcher (e.g., technician, graduate student, or postdoc) can complete all the steps from probe fabrication to data acquisition and processing within a single day. We further describe a new strategy for acquiring both positive- and negative-mode imaging data in the same experiment. This is achieved by alternating between positive and negative data acquisition modes during consecutive line scans. Using our imaging approach, hundreds of high-quality ion images were obtained from a single uterine section. This protocol enables sensitive and quantitative imaging of lipids and metabolites in heterogeneous tissue sections with high spatial resolution, which is critical to understanding biochemical processes occurring in biological tissues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Singlet fission

Singlet fission (SF) is a process whereby a photo-excited singlet exciton spontaneously splits into lower energy triplet excitons. This process has been known to occur in select organic materials for over 50 years but in the past was viewed as a curiosity and not as a problem worthy of focused attention. Over the past decade, this viewpoint has changed as the promising use of SF to improve photovoltaic efficiency has spurred vast activity, which has revealed the richness of the phenomenon. Currently, our understanding of the role played by various bright and dark states and their couplings to vibrations and to each other and by chemical composition and packing, among other factors, has enabled a large increase in the number of viable SF systems as well as a far deeper understanding of the process itself. These advances have allowed for the demonstration of proof-of-concept increases in the solar cell efficiency via the use of SF materials in simple tandem cells and as sensitizers in conjunction with conventional photovoltaics. Indeed, concepts surrounding the field have now invaded other fields, with a prominent example being the use of photon upconversion associated with triplet–triplet fusion (the inverse process to SF) in organic chemistry and photocatalysis. The 23 research articles in this special topic showcase recent cutting-edge advances in the field and highlight the diverse new directions being explored in the field of SF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Qudit Dynamical Decoupling on a Superconducting Quantum Processor

Multilevel qudit systems are increasingly being explored as alternatives to traditional qubit systems due to their denser information storage and processing potential. However, qudits are more susceptible to decoherence than qubits due to increased loss channels, noise sensitivity, and crosstalk. To address these challenges, we develop protocols for dynamical decoupling (DD) of qudit systems based on the Heisenberg-Weyl group. We implement and experimentally verify these DD protocols on a superconducting transmon processor that supports qudit operation based on qutrits (d = 3) and ququarts (d = 4). Specifically, we demonstrate single-qudit DD sequences to decouple qutrits and ququarts from system-bath-induced decoherence. Here we also introduce two-qudit DD sequences designed to suppress the detrimental cross-Kerr couplings between coupled qudits. This allows us to demonstrate a significant improvement in the fidelity of time-evolved qutrit Bell states. Our results highlight the utility of leveraging DD to enable scalable qudit-based quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures

In material science microfocus X-ray computed tomography (micro-CT) is one of the most popular non-destructive techniques to visualise and quantify the internal structure of materials in 3D. Despite constant system improvements, state-of-the-art micro-CT images can still hold several artefacts typical for X-ray CT imaging that hinder further image-based processing, structural and quantitative analysis. For example spatial resolution is crucial for an appropriate characterisation as the voxel size essentially influences the partial volume effect. However, defining the adequate image resolution is not a trivial aspect and understanding the correlation between scan parameters like voxel size and the structural properties is crucial for comprehensive material characterisation using micro-CT. Therefore, the objective of this study was to evaluate the influence of the spatial image resolution on the micro-CT based morphological analysis of three-dimensional (3D) open porous structures with a high surface complexity. In particular the correlation between the local surface properties and the accuracy of the micro-CT-based macro-morphology of 3D open porous Ti6Al4V structures produced by selective laser melting (SLM) was targeted and revealed for rough surfaces a strong dependence of the resulting structure characteristics on the scan resolution. Reducing the surface complexity by chemical etching decreased the sensitivity of the overall morphological analysis to the spatial image resolution and increased the detection limit. This study showed that scan settings and image processing parameters need to be customized to the material properties, morphological parameters under investigation and the desired final characteristics (in relation to the intended functional use). Customization of the scan resolution can increase the reliability of the micro-CT based analysis and at the same time reduce its operating costs. - Highlights: • We examine influence of the image resolution on μCT-based morphological analysis. • Surface properties influence accuracy of μCT-based morphology of porous structures. • Total porosity was the least sensitive to surface complexity and scan voxel size. • The beam thickness analysis was overestimated by the surface roughness. • Voxel size customization can significantly reduce a cost of the μCT-based analysis.

36 MATERIALS SCIENCE↗