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At least 793 records · Page 44

Formation of functionally graded steel by laser powder bed fusion via in-situ carbon doping

Additive Manufacturing (AM) enables functional integration by combining multiple components into a single part to shorten assembly time, reduce weight, and improve performance. Laser Powder Bed Fusion (LPBF) is an important AM method due to excellent spatial resolution, surface finish, and material properties without the need for extensive post-processing. Functional integration could be enhanced by spatial tuning of properties, but LPBF cannot readily vary material composition. Here, this paper addresses a method to add spatial composition control by printing small quantities of dopants via liquid carrier prior to laser fusion. The impact of carbon black suspension added to select regions of a Stainless Steel 316 L powder bed on melt pool dimension, hardness, and porosity is reported. The distribution of the carbon between the doped and plain layers and the resulting spatial variation in hardness is measured. Optical microscopy and composition analysis show that the carbon dispersed uniformly within the layer of deposition and diffused as little as 50 μm in the build direction. Keyhole conditions dramatically increase the inter-layer transport of the dopant. The added carbon increased hardness by >50 %. Porosity increased in doped regions but remained below 1.5 % for the best processing parameters. These results demonstrate that the composition of LPBF parts could be controlled in 3-dimensions using a dopant that is soluble in the melt pool. Additional work will be required to evaluate different dopant materials and optimize processing conditions for full density, but microalloying with soluble dopants appears to be a plausible solution to enhance functional integration with LPBF.

36 MATERIALS SCIENCE↗

Effect of threshold parameters on infrared segmentation methods for porosity detection in electron beam powder bed fusion

In-situ process monitoring has seen significant interest in additive manufacturing to address qualification and certification goals. This is especially prevalent in metal powder bed fusion processes such as electron beam powder bed fusion (PBF-EB), with layer-wise infrared imaging being commonly used to detect defects. Here, this work compares two different segmentation methods (static thresholding and statistical thresholding) used for detecting porosity from in-situ infrared imaging data for PBF-EB. Samples were manufactured at a variety of focus offset values to induce porosity. Then, the segmented infrared images were compared to ex-situ X-ray computed tomography scans, which served as a ground-truth reference for objective evaluation. Through this analysis framework, the influential parameters, static threshold and N-value (number of standard deviations above the mean pixel value), respectively, for both image segmentation methods were analyzed and compared for their effects on porosity detection. With optimal parameter settings, the two methods had similar porosity detection performance, but the statistical method performed better under a larger variety of parameter settings.

Infrared imaging↗

FLiBe compatibility of fusion-relevant materials

There is current interest in a 2LiF-BeF2 (FLiBe) molten salt blanket for fusion applications, however, very little compatibility data are available for fusion relevant materials. Initial static capsule testing results for 500 h at 550°-750 °C are presented for V-4Cr-4Ti, Fe-8Cr-2W (alloy F82H) compared to type 316H stainless steel and monolithic SiC as a surrogate for SiC/SiC composites. In addition, sintered Be12Ti specimens with varying additions of Be (0–20%) and a Be2C specimen were exposed with F82H coupons at 650 °C in individual Mo capsules. The V-4Cr-4Ti and SiC specimens exposed at 650 °C had small mass changes. Steel specimens showed increasing mass losses with increasing exposure temperature. However, when Be12Ti-Be specimens were included in a capsule with an F82H coupon, increasing F82H mass gains were observed with increasing Be content due to the formation of a Fe-Be surface layer. No layer and no mass gain were observed for the F82H specimen tested with Be2C.

Pint, Bruce [Oak Ridge National Laboratory (ORNL) ↗

Microstructural evolution, defect mitigation, and precipitation behavior in AA6061 via laser powder bed fusion with high-temperature substrate heating

Defects, particularly solidification cracking, remain persistent challenges in the laser powder bed fusion (LPBF) processing of AA6061 aluminum alloy. This study systematically investigates defect mitigation, microstructural evolution, and mechanical properties associated with high-temperature substrate preheating at 500 °C. Comprehensive microstructural analyses, including characterization of defects, grain structures, and precipitation behavior, were performed on samples in both as-built and T6 heat-treated states. Elevated preheating substantially reduced solidification cracking across a wide processing window, while demonstrating decreased crack sensitivity to laser parameters. Columnar cracks along the build direction were observed despite substrate preheating. Lack-of-fusion and keyhole porosity were effectively eliminated, though gas-induced microporosity persisted at higher powers. In-depth characterization of two distinct laser power and speed conditions confirmed the formation of micron-sized, non-coherent Mg 2 Si precipitates under heated substrate conditions, alongside α-AlFeCrMnSi intermetallic phases indicative of in-situ thermal effects during fabrication. Subsequent T6 heat treatment revealed the formation of fine, coherent needle-shaped β″ strengthening precipitates. Despite substantial differences in processing parameters, comparable mechanical properties were measured in the as-built samples (∼52 MPa yield strength, ∼130 MPa tensile strength), primarily due to reduced strain hardening effects and consistent precipitation characteristics. Meanwhile, the T6 heat treatment led to significant improvement in properties, enhancing yield strength by over 400%, aligning closely with the performance of conventional wrought AA6061-T6. These findings underscore that high-temperature substrate preheating offers an effective means to suppress cracks, control precipitation, and enhance mechanical performance in LPBF-processed AA6061.

36 MATERIALS SCIENCE↗

Neutron calorimeter development at fission and fusion pulsed neutron sources

A neutron calorimeter fielded in pulsed neutron irradiation experiments at the National Ignition Facility (NIF) and White Sands Missile Range Fast Burst Reactor (WSMR FBR) is described, and results are provided and discussed. The calorimeter is modular in design to allow fielding of various neutron absorber materials and thicknesses, as well as use at both fission and fusion sources, all of which has been done. Neutron calorimeters designed for fission sources have been fielded at fusion sources as well, but these instances are not documented in available literature—making this work novel. The functional calorimeter consists of a neutron absorber and two sheathed, grounded thermocouples secured within a subassembly made of thermally insulating materials. This subassembly is placed into a sealed vessel for material and facility safety considerations. The device was fielded at NIF in four polar-direct-drive exploding pusher shots and eleven WSMR FBR pulses. Calorimeter data from NIF experiments show a discernable thermal response accredited to neutron heating within the first 10 s, but the data are dominated by noise from ambient X-ray heating after time = 10 s post-pulse. This response is highly consistent between shots and linearly related to incident neutron fluence and neutron absorber thickness. A temperature rise of 1.1E-2 K/(10 13 neutrons/cm 2 ) per millimeter of absorber thickness was determined for both 0.4 mm and 1 mm thick depleted uranium absorbers with linear best fit R 2 of 0.97 and 0.98 for each thickness and y-axis offsets of 8.8E-3 and 1.3E-2, respectively. WSMR FBR experiment data show a temperature rise of 6.2E-2 K/(10 13 neutrons/cm 2 ) with linear best fit R 2 of 0.14 and y-axis offset of 7.6E-3 for a calorimeter with a 1 mm thick enriched boron carbide ( 10 B 4 C) absorber, though it must be noted that device-to-device variability is significant at both facilities. So these data are also affected by noise on a similar timescale as at NIF, though the noise is significantly lesser in magnitude but oscillatory.

42 ENGINEERING↗

Overview of advanced plasma-facing materials testing for Fusion Pilot Plants at DIII-D

Characterization and testing of advanced plasma-facing materials (PFMs) for Fusion Pilot Plants (FPP) is being conducted at the DIII-D National Fusion Facility through the ongoing two-year FPP Candidate Materials Thrust. Year one tested 17 novel materials utilizing the Divertor Materials Evaluation System (DiMES), with samples analyzed pre- and post-experiment via SEM, EDS, and confocal microscopy. Repeatable reference discharges were developed to ensure uniformity between experiments, including a new strike-point rastering scenario to provide more uniform heat/particle flux across DiMES during ELMing H-mode discharges. Various sample geometries and temperatures were used to achieve FPP-relevant conditions, including samples angled 10° towards the incident plasma flux and pre-heating up to 500 °C. The first exposure of liquid lithium (Li) capillary porous structures in a tokamak demonstrated uniform emission of Li vapor and suppression of Li droplets in H-mode when preheated to 350 °C. Dispersoid-strengthened W with 1 wt% TaC, TiC, and ZrC exposed to H-mode showed cracking and dispersoid ejection for all varieties except TiC, providing a clear down-selection. Ultra-high temperature ceramic materials TiB 2 and ZrB 2 showed minimal degradation under L-mode exposure. Silicon carbide (SiC) fiber composites showed arcing along edges, while CVD SiC remained pristine. Atmospheric plasma-sprayed W and SiC coatings endured H-mode exposure without macroscopic delamination; SiC exhibited granular ejection, while W showed increased outgassing. Additional W-based alloys were stress tested in H-mode, including Ni-based W heavy alloys, W f SiC f /W composites, W multi-principle element alloys, and functionally-graded W/SiC, to varying degrees of success.

DIII-D↗

Search for pair production of boosted Higgs bosons via vector-boson fusion in the $b$$\overline{b}$$b$$\overline{b}$ final state using $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for Higgs boson pair production via vector-boson fusion is performed in the Lorentz-boosted regime, where a Higgs boson candidate is reconstructed as a single large-radius jet, using 140 fb−1 of proton–proton collision data at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. Only Higgs boson decays into bottom quark pairs are considered. The search is particularly sensitive to the quartic coupling between two vector bosons and two Higgs bosons relative to its Standard Model prediction, K 2V . This study constrains K 2V to 0.55 < K 2V < 1.49 at the 95% confidence level. The value K 2V = 0 is excluded with a significance of 3.8 standard deviations with other Higgs boson couplings fixed to their Standard Model values. A search for new heavy spin-0 resonances that would mediate Higgs boson pair production via vector-boson fusion is carried out in the mass range of 1–5 TeV for the first time under several model and decay-width assumptions. No significant deviation from the Standard Model hypothesis is observed and exclusion limits at the 95% confidence level are derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Thermochemical Data Fusion Using Graph Representation Learning

Large databases are required for “Big Data” applications in catalysis and materials science. Thermochemical databases can be created by combining data from various sources and by correcting low-fidelity datasets to higher accuracy with minimal computation. To achieve this “data fusion”, thermochemical quantities of interest, calculated at various levels of density functional theory (DFT), need to be mapped to the same, high levels of theory. In this work, a graph theoretical, statistical framework is proposed for such tasks. Subgraph frequencies are shown to provide a natural representation for learning these fusion maps. The maps are linear and are learnt with automated descriptor selection. Using a dataset of as few as ~1% from the QM9 database of 133,885 molecules, these models can predict multiple thermochemical quantities at a higher level of theory with an accuracy of 1 kcal/mol. Here, the method is explainable, generalizable, and provides a diagnostic tool for outlier identification

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning

Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Environmental Sciences & Ecology↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Integrated linker-regulation and ring-fusion engineering for efficient additive-free non-fullerene organic solar cells

The rational molecular design and structural modification of quasi-two-dimensional fused perylene diimide (quasi-2D FPDI) acceptors have received growing attention for application in non-fullerene organic solar cells (NF-OSCs). Herein, we designed and synthesized two pairs of FPDI acceptors, one in the form of FPDI–π-bridge–FPDI with the π-bridge being either an axisymmetric thiophene (T) or a centrosymmetric thienothiophene (TT) unit, and the other being the corresponding ring-fusion counterpart. Additionally, four small molecule acceptors, namely T-FPDI, TT-FPDI, FT-FPDI and FTT-FPDI, were paired with a common PTB7-Th polymeric electron donor as active materials for a comparative study of the effects of linkers and ring fusion on their photovoltaic performances. The T-FPDI-based NF-OSC exhibited a decent power conversion efficiency (PCE) of 5.50%, while a higher PCE of 7.17% with a simultaneous enhancement in the open circuit voltage ( V oc ), the short-circuit current density ( J sc ) and the fill factor (FF) was achieved for the TT-FPDI-based solar cells. The solar cells based on the ring-fused FT-FPDI and FTT-FPDI acceptors displayed PCEs of 6.75% and 7.66%, respectively, both higher than those of the corresponding non-fused counterparts. Notably, the trade-off between the J sc and V oc , commonly observed in fullerene OSCs, is alleviated in these systems. It is also worth noting that the NF-OSCs based on these FPDI acceptors do not need any solvent additives. Overall, this successful molecular engineering based on novel quasi-2D FPDI building blocks may inspire the development of emergent electron acceptors for high performance additive-free NF-OSCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Siderocalin fusion proteins enable a new 86 Y/ 90 Y theranostic approach

The mammalian protein siderocalin binds bacterial siderophores and their iron complexes through cation-π and electrostatic interactions, but also displays high affinity for hydroxypyridinone complexes of trivalent lanthanides and actinides. In order to circumvent synthetic challenges, the use of siderocalin-antibody fusion proteins is explored herein as an alternative targeting approach for precision delivery of trivalent radiometals. We demonstrate the viability of this approach in vivo, using the theranostic pair 90 Y (β − , t 1/2 = 64 h)/ 86 Y (β + , t 1/2 = 14.7 h) in a SKOV-3 xenograft mouse model. Ligand radiolabeling with octadentate hydroxypyridinonate 3,4,3-LI(1,2-HOPO) and subsequent protein binding were achieved at room temperature. The results reported here suggest that the rapid non-covalent binding interaction between siderocalin fusion proteins and the negatively charged Y(III)-3,4,3-LI(1,2-HOPO) complexes could enable purification-free, cold-kit labeling strategies for the application of therapeutically relevant radiometals in the clinic.

Cosby, Alexia G.↗

A simple vacuum suitcase for enabling plasma facing component characterization in fusion devices

We have demonstrated a vacuum suitcase to transport samples in vacuo to a surface analysis station for characterization of tokamak plasma facing components (PFCs). This technique enables surface analysis at powerful, dedicated stations that are not encumbered by design constraints imposed on them by a tokamak. The vacuum suitcase is an alternative solution to characterizing PFCs using diagnostics that are designed and built around a tokamak. The vacuum suitcase, called the Sample Exposure Probe (SEP), features mobile ultra-high vacuum pumping. Active pumping under high vacuum enables sample transfer between the Lithium Tokamak eXperiment-β (LTX-β) and a high resolution X-ray Photoelectron Spectroscopy (XPS) system that is situated close by. A thermocouple inserted in the back of the sample head measures heat flux from the plasma during exposure, and together with a button heater, allows the sample to match the LTX-β PFCs in high temperature operations. As vacuum conditions are better during transfer and analysis than in the tokamak, less contamination is introduced to the samples. XPS scans on a dedicated analysis station enable peak identification due to higher resolution and signal to noise ratio. A similar probe could be implemented for other fusion devices. As a result, the SEP is the first vacuum suitcase implementation for fusion applications that incorporates active pumping.

47 OTHER INSTRUMENTATION↗

Solid Cherenkov detector for studying nucleosynthesis in inertial confinement fusion

Measuring gamma rays emitted from nuclear reactions gives insight into their nuclear structure. Notably, there are several nuclear reactions that produce gamma rays at ~1 MeV–3 MeV energies such as T( 4 He, γ) 7 Li, 4 He( 3 He, γ) 7 Be, and 12 C(p, γ) 13 N, which may solve questions lingering about big-bang nucleosynthesis and stellar nucleosynthesis. To observe 1 MeV–3 MeV gamma rays in an inertial confinement fusion system, a new style of the Cherenkov detector was developed using aerogel and fused silica as a Cherenkov medium. Utilizing the OMEGA laser facility, both aerogel and fused silica media were compared with the existing gas-medium Cherenkov detector to validate the concept. Furthermore, gamma ray measurements from high yield inertial confinement fusion implosions (deuterium–tritium and deuterium– 3 He) demonstrated that aerogel and fused silica were viable Cherenkov media, paving the way for a potential optimized detector to make these cross section measurements on OMEGA or the National Ignition Facility.

47 OTHER INSTRUMENTATION↗

Fiber-optic silicon Fabry–Perot interferometric bolometer with improved detection limit for magnetic confinement fusion

Fiber-optic bolometers (FOBs) intended for plasma radiation measurement in magnetically confined fusion have been previously developed using a silicon pillar that functions as both a Fabry–Perot interferometer (FPI) for temperature measurement and an absorber for the radiation. We report an FOB design that can significantly improve the detection sensitivity over earlier designs by engineering the absorber of the FOB. Our design uses the fact that, compared with a silicon pillar, a gold film with the same x-ray absorption thickness will show a much higher temperature rise from a given power density of the radiation. Therefore, the responsivity of an FOB can be improved by attaching a large gold disk to the silicon FPI as the absorber. We have developed a fabrication method for FOBs of such design and obtained an FOB with a 4-µm-thick, 0.6-mm-diameter gold disk attached to a 200-µm-diameter, 100-µm-thick silicon FPI. We have characterized the noise, responsivity, response time, and noise-equivalent power density (NEPD) and compared these with the earlier design where the absorber is mainly the silicon FPI itself. The experimental result suggests that the FOB with the gold disk achieves a responsivity of ∼2.8 mK/(W/m2) and a noise-equivalent-power-density of 0.13 W/m2, which are, respectively, more than nine times larger and six times smaller compared to the FOB using a previous design. Improved NEPD and good absorption over a broad frequency range will make the FOB more attractive for applications in magnetic-confinement fusion devices.

Uddin, Nezam↗

Inferring neutron yields using indium activation samples for small fractions of tritium added to deuterium fuel in inertial confinement fusion (ICF) experiments

In inertial confinement fusion experiments, the neutron yield is an important metric for thermonuclear fusion performance. Neutron activation diagnostics can be used to infer neutron yields. The material used for neutron activation diagnostic undergoes a threshold reaction so that only neutrons having energies above the threshold energy are observed. For thermonuclear experiments using deuterium (D) and tritium (T) fuel constituents, neutrons arising from D + D reactions (DD-neutrons) and neutrons resulting from D + T reactions (DT-neutrons) are of primary interest. Indium has two neutron activation reactions that can be used to infer yields of DD-neutrons and DT-neutrons. One threshold is high enough that only DT-neutrons can induce activation, the second reaction can be activated by both DD-neutrons and DT-neutrons. Thus, to obtain the DD-neutron yield, the contribution made by DT-neutrons to the total induced activity must be extracted. In DD-fuel experiments, DT-neutrons arise from secondary reactions, which are significantly lower in number than primary DD-neutrons, and their contribution to the inferred DD-neutron yield can be ignored. When the DD- and DT-neutron yields become comparable, such as when low tritium fractions are added to DD-fuel, the contribution of DT-neutrons must be extracted to obtain accurate yields. A general method is described for this correction to DD-neutron yields.

Mangan, M. A. (ORCID:000000034583700X)↗

Investigating boosted decision trees as a guide for inertial confinement fusion design

Inertial confined fusion experiments at the National Ignition Facility have recently entered a new regime approaching ignition. Improved modeling and exploration of the experimental parameter space were essential to deepening our understanding of the mechanisms that degrade and amplify the neutron yield. The growing prevalence of machine learning in fusion studies opens a new avenue for investigation. Here in this paper, we have applied the Gradient-Boosted Decision Tree machine-learning architecture to further explore the parameter space and find correlations with the neutron yield, a key performance indicator. We find reasonable agreement between the measured and predicted yield, with a mean absolute percentage error on a randomly assigned test set of 35.5%. This model finds the characteristics of the laser pulse to be the most influential in prediction, as well as the hohlraum laser entrance hole diameter and an enhanced capsule fabrication technique. We used the trained model to scan over the design space of experiments from three different campaigns to evaluate the potential of this technique to provide design changes that could improve the resulting neutron yield. While these data-driven model cannot predict ignition without examples of ignited shots in the training set, it can be used to indicate that an unseen shot design will at least be in the upper range of previously observed neutron yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Charged particle diagnostics for inertial confinement fusion and high-energy-density physics experiments

MeV-range ions generated in inertial confinement fusion (ICF) and high-energy-density physics experiments carry a wealth of information, including fusion reaction yield, rate, and spatial emission profile; implosion areal density; electron temperature and mix; and electric and magnetic fields. Here, the principles of how this information is obtained from data and the charged particle diagnostic suite currently available at the major US ICF facilities for making the measurements are reviewed. Time-integrating instruments using image plate, radiochromic film, and/or CR-39 detectors in different configurations for ion counting, spectroscopy, or emission profile measurements are described, along with time-resolving detectors using chemical vapor deposited diamonds coupled to oscilloscopes or scintillators coupled to streak cameras for measuring the timing of ion emission. A brief description of charged-particle radiography setups for probing subject plasma experiments is also given. The goal of the paper is to provide the reader with a broad overview of available capabilities, with reference to resources where more detailed information can be found.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗