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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

A cross-correlation study of the Fermi -LAT γ-ray diffuse extragalactic signal

In this work, starting from 21 months of data from the Fermi Large Area Telescope (LAT), we derive maps of the residual isotropic γ-ray emission, a relevant fraction of which is expected to be contributed by the extragalactic diffuse γ-ray background (EGB). We search for the auto-correlation signals in the above γ-ray maps and for the cross-correlation signal with the angular distribution of different classes of objects that trace the large-scale structure of the Universe. We compute the angular two-point auto-correlation function of the residual Fermi -LAT maps at energies E > 1 GeV, E > 3 GeV and E > 30 GeV well above the Galactic plane and find no significant correlation signal. This is, indeed, what is expected if the EGB were contributed by BL Lacertae (BLLacs), Flat Spectrum Radio Quasars (FSRQs) or star-forming galaxies, since, in this case, the predicted signal is very weak. Then, we search for the Integrated Sachs–Wolfe (ISW) signature by cross-correlating the Fermi-LAT maps with the 7-year Wilkinson Microwave Anisotropy Probe ( WMAP7 ) cosmic microwave background map. We find a cross-correlation consistent with zero, even though the expected signal is larger than that of the EGB auto-correlation. Lastly, in an attempt to constrain the nature of the γ-ray background, we cross-correlate the Fermi -LAT maps with the angular distributions of objects that may contribute to the EGB: quasi-stellar objects (QSOs) in the Sloan Digital Sky Survey Data Release 6 (SDSS-DR6) catalogue, NRAO VLA Sky Survey (NVSS) galaxies, Two Micron All Sky Survey (2MASS) galaxies and Luminous Red Galaxies (LRGs) in the SDSS catalogue. The cross-correlation is always consistent with zero, in agreement with theoretical expectations, but we find (with low statistical significance) some interesting features that may indicate that some specific classes of objects contribute to the EGB. A χ 2 analysis confirms that the correlation properties of the 21-month data do not provide strong constraints of the EGB origin. However, the results suggest that the situation will significantly improve with the 5- and 10-yr Fermi -LAT data. In future, the EGB analysis will then allow placing significant constraints on the nature of the EGB and might provide, in addition, a detection of the ISW signal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Discovery of False Data Injection Attacks on Power Grid Frequency Controllers with Reinforcement Learning [Poster]

While inverter-based DER (distributed energy resources) are instrumental to integrating renewable energy into the power grid, they reduce the grid's mechanical inertia, thereby increasing the risk of frequency instabilities. To compensate for frequency instability risks, the grid must also undergo a transformation to include digital technologies that allow for two-way communication between the utility and customers. The current and future state of the power grid allows for building a cleaner energy landscape. However, the grid may also become vulnerable to novel cyber threats. To preemptively protect the power grid against elaborate cyber-attacks, we propose to discover potential threats via reinforcement learning. In this work, the focus is on studying false data injection attacks that target the control logic of frequency controllers. We show that a reinforcement learning agent can successfully discover how to best inject false data into linear droop controllers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

A platform for effective requirements management and collaboration in nuclear compliance and licensing

Buoyed by its promise as a cost effective and low-carbon-footprint source of electricity, the nuclear industry is in the midst of a world-wide renaissance. However, significant challenges, including responding to increased safety and regulatory mandates, making a smooth transition to next-generation reactor technology, and dealing with the adoption of digital instrumentation and control (I and C) systems that rely heavily on software must be effectively addressed to ensure the momentum continues. New technology solutions, such as those developed by IBM's Rational business unit, coupled with well codified processes, policies and best practices leveraged across the nuclear ecosystem's participants have been shown to aid in overcoming these obstacles. This paper will highlight some of the compliance and collaboration challenges facing the extended nuclear ecosystem, describe a potential solution that can aid in addressing the challenges, and present several examples of where the solution has been implemented in the nuclear space. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Evaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis

Analyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Radiologist Digital Workspace Use and Preference: a Survey-Based Study

Literature regarding the heterogeneity of and preferences for radiology workstation design—and, in particular, the digital workspace of the radiology workstation—is scant. The purpose of this study was to determine the nature of the digital environments across the specialty and the degree of satisfaction users associated with the particular facets of those environments. A survey was sent to the membership of the Association of University Radiologists in February 2015. The survey comprised 10 questions establishing demographics, current typical workstation setup, perceived satisfaction with that setup, and preferences for potential altered setups. A total of 336 radiologists responded, with a cross-section similar to that described in the 2015 ACR annual workforce survey (1). Although there was a rough split in the number of radiologists using one or two non-diagnostic monitors (46 vs. 51%, respectively), the strong majority (75%) of radiologists use two diagnostic monitors. Users of two non-diagnostic monitors were more likely to keep open the case info (87 vs. 68%) and EMR (84 vs 68%). More senior radiologists tended to find the current setup easy more frequent than younger radiologists, and the latter group was more likely to believe additional monitors would be helpful. Although many radiologists are comfortable with their computing workflows, a significant number indicate dissatisfaction and may be interested in being able to specify the amount of monitor space with which they can work. Additional monitors may promote improved quality in addition to any potential productivity gains.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

SPIDERS: overview of the X-ray galaxy cluster follow-up and the final spectroscopic data release

ABSTRACT SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a large spectroscopic programme for X-ray selected galaxy clusters as part of the Sloan Digital Sky Survey-IV (SDSS-IV). We describe the final data set in the context of SDSS Data Release 16 (DR16): the survey overall characteristics, final targeting strategies, achieved completeness, and spectral quality, with special emphasis on its use as a galaxy cluster sample for cosmology applications. SPIDERS now consists of about 27 000 new optical spectra of galaxies selected within 4000 photometric red sequences, each associated with an X-ray source. The excellent spectrograph efficiency and a robust analysis pipeline yield a spectroscopic redshift measurement success rate exceeding 98 per cent, with a median velocity accuracy of 20 km s−1 (at z = 0.2). Using the catalogue of 2740 X-ray galaxy clusters confirmed with DR16 spectroscopy, we reveal the 3D map of the galaxy cluster distribution in the observable Universe up to z ∼ 0.6. We highlight the homogeneity of the member galaxy spectra among distinct regions of the galaxy cluster phase space. Aided by accurate spectroscopic redshifts and by a model of the sample selection effects, we compute the galaxy cluster X-ray luminosity function and we present its lack of evolution up to z = 0.6. Finally we discuss the prospects of forthcoming large multiplexed spectroscopic programmes dedicated to follow up the next generation of all-sky X-ray source catalogues.

Clerc, N.↗
DOE OSTI2025

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗
DOE OSTI2016

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinct from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Developmental study of advanced HIS design method for digital I and C+HMIT of PWR plant - 277

A new conceptual frame of how to design and validate a digital HIS (human interface system) on an innovative numerical simulation basis is proposed for the support of plant operators' supervisory control of various types of automated complex NPPs (nuclear power plants). The proposed conceptual framework utilizes the object-oriented software for plant DiD (defense-in depth) risk monitor with the combination of nuclear reactor accident simulation by an advanced nuclear safety analysis code RELAP5/MOD4. The conceptual frame proposed in this paper will be applied for an example practice for the SBLOCA (small break loss of coolant accident) case of passive safety PWR (pressurized water reactor) AP1000. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Enhanced resistance to decay of imprinted nanopatterns in thin films by bare nanoparticles compared to polymer-grafted nanoparticles

We extend a previous study on the influence of nanoparticles on the decay of nanoimprinted polymer film patterns to compare the effects of “bare” silica (SiO 2 ) nanoparticles and SiO 2 nanoparticles with grafted polymer layers having the same chemical composition as the polymer matrix. This method involves nanoimprinting substrate-supported polymer films using a pattern replicated from a digital versatile disc (DVD), and then annealing the patterned polymer nanocomposite films at elevated temperatures to follow the decay of the topographic surface pattern with time by atomic force microscopy imaging after quenching. We quantified the relaxation of the pattern height (“slumping”) and determined the relaxation time τ for this pattern decay process as a function of nanoparticle filler type and concentration to determine how nanoparticle additives influence relative film stability. Attractive interactions between the bare nanoparticles and the polymer matrix significantly enhance the thermal resilience of the nanopatterns to decay, compared to those of the particle brushes, wherein the particle core interactions are screened from the matrix via the brush layer. A novel aspect of this method is that it readily lends itself to in situ film relaxation measurements in a manufacturing context. We observe that the relaxation time of the pattern relaxation exhibits entropy–enthalpy compensation in the free energy parameters governing the pattern relaxation process as a function of temperature, irrespective of the NP system used, consistent with our previous experimental and computational studies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A symbolic framework to obtain mid-fidelity models of flexible multibody systems with application to horizontal-axis wind turbines

Abstract. The article presents a symbolic framework (also called computer algebra program) that is used to obtain, in symbolic mathematical form, the linear and nonlinear equations of motion of a mid-fidelity multibody system including rigid and flexible bodies. Our approach is based on Kane's method and a nonlinear shape function representation for flexible bodies. The shape function approach does not represent the state of the art for flexible multibody dynamics but is an effective trade-off to obtain mid-fidelity models with few degrees of freedom, taking advantage of the separation of space and time. The method yields compact symbolic equations of motion with implicit account of the constraints. The general and automatic framework facilitates the creation and manipulation of models with various levels of complexity by adding or removing degrees of freedom. The symbolic treatment allows for analytical gradients and linearized equations of motion. The linear and nonlinear equations can be exported to Python code or dedicated software. There are multiple applications, such as time domain simulation, stability analyses, frequency domain analyses, advanced controller design, state observers, and digital twins. In this article, we describe the method we used to systematically generate the equations of motion of multibody systems and present the implementation of the framework using the Python package SymPy. We apply the framework to generate illustrative land-based and offshore wind turbine models. We compare our results with OpenFAST simulations and discuss the advantages and limitations of the method. The Python implementation is provided as an open-source project.

Branlard, Emmanuel (ORCID:0000000277506128)↗
DOE OSTI2013

Sost and its paralog Sostdc1 coordinate digit number in a Gli3-dependent manner

WNT signaling is critical in most aspects of skeletal development and homeostasis, and antagonists of WNT signaling are emerging as key regulatory proteins with great promise as therapeutic agents for bone disorders. Here we show that Sost and its paralog Sostdc1 emerged through ancestral genome duplication and their expression patterns have diverged to delineate nonoverlapping domains in most organ systems including musculoskeletal, cardiovascular, nervous, digestive, reproductive and respiratory. In the developing limb, Sost and Sostdc1 display dynamic expression patterns with Sost being restricted to the distal ectoderm and Sostdc1 to the proximal ectoderm and the mesenchyme. While Sostdc1 –/– mice lack any obvious limb or skeletal defects, Sost –/– mice recapitulate the hand defects described for Sclerosteosis patients. However, elevated WNT signaling in Sost –/–; Sostdc1 –/– mice causes misregulation of SHH signaling, ectopic activation of Sox9 in the digit 1 field and preaxial polydactyly in a Gli1- and Gli3-dependent manner. In addition, we show that the syndactyly documented in Sclerosteosis is present in both Sost –/– and Sost –/–; Sostdc1 –/– mice, and is driven by misregulation of Fgf8 in the AER, a region lacking Sost and Sostdc1 expression. This study highlights the complexity of WNT signaling in skeletal biology and disease and emphasizes how redundant mechanism and non-cell autonomous effects can synergize to unveil new intricate phenotypes caused by elevated WNT signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Network Slicing for Federated Learning in Operational Technology Environment

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) environments are essential to modern infrastructure, facing challenges in ensuring low-latency, high-throughput communication while mitigating cyber threats. This paper presents a framework integrating Federated Learning (FL) and network slicing with Quality of Service (QoS) to enable real-time monitoring without disrupting OT operations. Leveraging digital twin technology and Network Function Virtualization (NFV), the architecture supports predictive analytics and Industry 4.0 requirements. FL facilitates decentralized model training, preserving data privacy and scalability, though it introduces potential throughput constraints. Network slicing addresses this by creating dedicated virtualized segments optimized for performance and security. Advanced fault tolerance at the container and instance levels enhances system reliability. The proposed architecture ensures high throughput, low latency, and secure orchestration for real-time anomaly detection in OT networks. Performance evaluations validate its efficiency in throughput, deployment, and learning accuracy, providing a robust foundation for future ICS automation and data-driven decision-making.

Delgado, Brian G. Rodiles [University of Texas at ↗
DOE OSTI2014

Semiotic indexing of digital resources

A method of classifying a plurality of documents. The method includes steps of providing a first set of classification terms and a second set of classification terms, the second set of classification terms being different from the first set of classification terms; generating a first frequency array of a number of occurrences of each term from the first set of classification terms in each document; generating a second frequency array of a number of occurrences of each term from the second set of classification terms in each document; generating a first similarity matrix from the first frequency array; generating a second similarity matrix from the second frequency array; determining an entrywise combination of the first similarity matrix and the second similarity matrix; and clustering the plurality of documents based on the result of the entrywise combination.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Optimization of energy window for {sup 90}Y bremsstrahlung SPECT imaging for detection tasks using the ideal observer with model-mismatch

Purpose: In yttrium-90 ({sup 90}Y) microsphere brachytherapy (radioembolization) of unresectable liver cancer, posttherapy {sup 90}Y bremsstrahlung single photon emission computed tomography (SPECT) has been used to document the distribution of microspheres in the patient and to help predict potential side effects. The energy window used during projection acquisition can have a significant effect on image quality. Thus, using an optimal energy window is desirable. However, there has been great variability in the choice of energy window due to the continuous and broad energy distribution of {sup 90}Y bremsstrahlung photons. The area under the receiver operating characteristic curve (AUC) for the ideal observer (IO) is a widely used figure of merit (FOM) for optimizing the imaging system for detection tasks. The IO implicitly assumes a perfect model of the image formation process. However, for {sup 90}Y bremsstrahlung SPECT there can be substantial model-mismatch (i.e., difference between the actual image formation process and the model of it assumed in reconstruction), and the amount of the model-mismatch depends on the energy window. It is thus important to account for the degradation of the observer performance due to model-mismatch in the optimization of the energy window. The purpose of this paper is to optimize the energy window for {sup 90}Y bremsstrahlung SPECT for a detection task while taking into account the effects of the model-mismatch. Methods: An observer, termed the ideal observer with model-mismatch (IO-MM), has been proposed previously to account for the effects of the model-mismatch on IO performance. In this work, the AUC for the IO-MM was used as the FOM for the optimization. To provide a clinically realistic object model and imaging simulation, the authors used a background-known-statistically and signal-known-statistically task. The background was modeled as multiple compartments in the liver with activity parameters independently following a Gaussian distribution; the signal was modeled as a tumor with a Gaussian-distributed activity parameter located randomly with equal probability at one of three positions. The IO test statistics (i.e., likelihood ratios) were estimated using Markov-chain Monte Carlo methods. The authors realistically modeled human anatomy using a digital phantom code, and realistically simulated {sup 90}Y bremsstrahlung SPECT imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo bremsstrahlung simulation method. Model-mismatch was included by modeling image formation process in the calculation of IO test statistics using an analytic modeling method previously developed for quantitative {sup 90}Y bremsstrahlung SPECT. To demonstrate the effects of the model-mismatch on the detection task, the authors optimized the energy window both with and without model-mismatch included in the IO. Results: For all the energy windows, the AUC values for the IO-MM were smaller than that for the IO. The optimal windows for the IO-MM and the IO were 80-180 and 60-400 keV, respectively. Conclusions: The authors have demonstrated the degradation of the ideal performance due to model-mismatch and optimized the energy window for {sup 90}Y bremsstrahlung SPECT for detection tasks by accounting for the effects of the model-mismatch. The obtained optimal window was much narrower when taking into account the model-mismatch and similar to that obtained previously for estimation tasks.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

The research data alliance photon and neutron science interest group

Scientific research data provides unique challenges that are distinct from classic “Big Data” sources. One common element in research data is that the experiment, observations, or simulation were designed, and data were specifically acquired, to shed light on an open scientific question. The data and methods are usually “owned” by the researcher(s) and the data itself might not be viewed to have long-term scientific significance after the results have been published. Often, the data volume was relatively low, with data sometimes easier to reproduce than to catalog and store. Some data and meta-data were not collected in a digital form, or were stored on antiquated or obsolete media. Generally speaking, policies, tools, and management of digital research data have reflected an ad hoc approach that varies domain by domain and research group by research group. This model, which treats research data as disposable, is proving to be a serious limitation as the volume and complexity of research data explodes. Changes are required at every level of scientific research: within the individual groups, and across scientific domains and interdisciplinary collaborations. Enabling researchers to learn about available tools, processes, and procedures should encourage a spirit of cooperation and collaboration, allowing researchers to come together for the common good. In conclusion, these community-oriented efforts provide the potential for targeted projects with high impact.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-E-06: Teaching About the Gamma Camera and Ultrasound Imaging

Purpose: Instructional modules on applications of physics in medicine are being developed. The target audience consists of students who have had an introductory undergraduate physics course. This presentation will concentrate on an active learning approach to teach the principles of the gamma camera. There will also be a description of an apparatus to teach ultrasound imaging. Methods: Since a real gamma camera is not feasible in the undergraduate classroom, we have developed two types of optical apparatus that teach the main principles. To understand the collimator, LEDS mimic gamma emitters in the body, and the photons pass through an array of tubes. The distance, spacing, diameter, and length of the tubes can be varied to understand the effect upon the resolution of the image. To determine the positions of the gamma emitters, a second apparatus uses a movable green laser, fluorescent plastic in lieu of the scintillation crystal, acrylic rods that mimic the PMTs, and a photodetector to measure the intensity. The position of the laser is calculated with a centroid algorithm.To teach the principles of ultrasound imaging, we are using the sound head and pulser box of an educational product, variable gain amplifier, rotation table, digital oscilloscope, Matlab software, and phantoms. Results: Gamma camera curriculum materials have been implemented in the classroom at Loyola in 2014 and 2015. Written work shows good knowledge retention and a more complete understanding of the material. Preliminary ultrasound imaging materials were run in 2015. Conclusion: Active learning methods add another dimension to descriptions in textbooks and are effective in keeping the students engaged during class time. The teaching apparatus for the gamma camera and ultrasound imaging can be expanded to include more cases, and could potentially improve students’ understanding of artifacts and distortions in the images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Operando synchrotron X-ray analysis of melt pool dynamics in an Al-Sn immiscible alloy

The melt flow in an Al-50vol.% Sn immiscible alloy, produced by single-track laser melting of Al and Sn elemental powders, was studied in real time. High-speed synchrotron X-ray imaging was used to track Al and Sn liquids’ movements, and also to examine elemental distributions in the laser tracks, complimented by electron microscopy after solidification. Key aspects, including melt pool geometry, keyhole instability, and flow dynamics (flow pattern and velocity), were examined using digital image analysis. Relatively deeper melt pools formed at 400 W and 300 mm/s exhibited greater stability, with smooth surfaces, consistent outward flow, and minor vortices near the keyhole. In contrast, shallower pools produced at higher scanning speeds (>500 mm/s) demonstrated greater instability with increased surface waviness, and stronger velocity fluctuations, leading to numerous micro-vortices and increased Al-Sn heterogeneity. Velocity scale estimations, supported by experimental observations, examined the roles of vapour pressure, Marangoni effect, buoyancy, inertial, and surface tension forces in the flow. The results revealed that vapour pressure and mechanical waves dominated at high scanning speeds (shallow pools), while Marangoni forces were equally significant in deep pools at lower speeds (300 mm/s). Buoyancy was found to have minimal impact in both cases. Furthermore, the interaction between inertial and surface tension forces played a critical role in determining the degree of waviness of the pools’ surfaces. These findings offer valuable insights into melt pool dynamics during laser processing of immiscible alloys and other metallic systems using elemental powders, and provide guidance for developing high-fidelity computational fluid dynamics models.

immiscible alloys↗