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DOE OSTI2026

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

A non‐intrusive domain‐decomposition model reduction method for linear steady‐state partial differential equations with random coefficients

Abstract Domain decomposition methods have been proved to be an effective strategy to reduce the dimension of parametric partial differential equations (PDEs). However, existing domain decomposition methods for parametric PDEs are usually intrusive, which means domain decomposition based solvers need to be implemented from scratch for each target parametric PDE. To address this issue, we develop a new non‐intrusive domain‐decomposition model reduction method for linear steady‐state PDEs with random‐field coefficients. As a variant of our previous work by Mu and Zhang, the new method only needs access to the final linear system, that is, the global stiffness matrix and the right hand side, of a deterministic PDE solver, in order to build a domain‐decomposition‐based reduced model without intrusive implementation from scratch. The key idea is to remove the interface condition between sub‐domains and rely on the correlation between columns of the linear system to couple the sub‐domains. The non‐intrusive feature enables the applicability of the proposed method to a broader class of uncertainty quantification problems, where many legacy codes/solvers can be fully reused by our method. Two numerical examples including diffusion equations with random diffusivity and convection‐dominated transport with random velocity, are provided to demonstrate the effectiveness and efficiency of our method.

Zhang, Guannan↗

DOE OSTI2026

Healable Coatings as a Mechanism to Repair Leading Edge Erosion in Wind Energy

Wind turbine blades are highly engineered structures designed to face temperature extremes and high winds. However, erosion of the blade's leading edge and subsequent repair remains a significant and costly challenge for the wind energy industry. Repair of these leading edges can lead to large amounts of downtime for the turbine and significant operational inefficiencies. In this work, the strength of adhesion and healing ability of a commercially available vitrimer (Mallinda's VITRIMAX) was compared to that of a thermoplastic resin, which has previously been demonstrated in wind energy applications (Arkema's Elium) to evaluate their efficacy as surface coatings for wind turbine blades, particularly their leading edges. Vitrimers are a class of inherently reprocessable thermosets, and it was theorized that vitrimer-based leading edge coatings could enable more robust and efficient wind turbine blades with decreased operational downtime and safer maintenance practices. It was found that the VITRIMAX adhered better to the wind blades' surfaces than both the manufacturer's paint and Elium, with increases in pull-off strength of adhesion ranging from 24% to 83% above that of the original paint. Furthermore, the VITRIMAX adhered strongly to the underlying composite of each blade with strength of adhesion values increasing in ranges from 42% to 97% above that of the original paint. Finally, the vitrimer coating showed an 88% decrease in surface roughness compared to end-of-life blade materials, and initial healing demonstrations in which coatings were manually scratched and subsequently healed exhibited an ~84.5% decrease in scratch depths.

Hubbard, Amber [ORNL]↗

DOE OSTI2019

Manufacturing of a Metal Matrix Composite Coating on a Polymer Matrix Composite Through Cold Gas Dynamic Spray Technique

In this work, the manufacturing through cold gas dynamic spray (cold spray or CS) of metallic composite coatings of Al-Al{sub 2}O{sub 3} on organic composite substrates with thermoplastic PLA matrix and hemp fibers was studied. Alumina powders, with a mean diameter of 50 μm, were used blended with aluminum powders in three different weight concentration percentages (0, 15, 20, and 45%) as feedstock material in order to highlight and discuss the variations of the coating surface properties depending on the alumina percentage. The coatings were produced by using a low-pressure cold spray equipment. A detailed experimental campaign, including microstructural observations and confocal microscopy, was carried out to study the structure of the coatings. Moreover, the tribological behavior of the coatings was studied through both scratch test and pin-on-disk test. The experiments showed that a small addition of alumina improves the compactness of the coating and its resistance to scratch and wear behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Wear and Corrosion Resistances of Active Screen Plasma-Nitrided Duplex Stainless Steels

Two grades of duplex stainless steel, SAF 2205 and SAF 2507, were nitrided using an active screen plasma process carried out at 380 °C for 10 h and were characterized in terms of microstructure and hardness. Wear resistance was assessed by means of linear scratch tests, using loads below and above the critical load. Potentiodynamic polarization was used to analyze corrosion behavior in 0.6 M NaCl solution. X-ray diffractometry showed expanded austenite formation in all nitrided samples. The super duplex steel SAF 2507 showed much better scratch resistance, with low friction coefficient and greater toughness, as judged by the pattern of superficial cracks when it was tested above the critical load. The corrosion behavior of steels was also different, mainly in the active region, and nitriding had a more beneficial effect upon SAF 2507. The potential relative to the transpassive region was practically unaffected by the nitriding.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A comparative study of mechanical and chemical durability of non-wetting superhydrophobic and lubricant-infused surfaces

Fabrication of bioinspired non-wetting superhydrophobic surfaces (SHS) and lubricant-infused surfaces (LIS) has been studied extensively on a variety of materials. In contrast, durability of the surfaces exposed to harsh mechanical and chemical environments has been the subject of little attention. This study considers the mechanical and chemical durability of SHS and LIS copper surfaces fabricated via facile electrodeposition and chemical etching methods. The as-fabricated surfaces demonstrate excellent non-wetting characteristics with water contact angle of 160° and sliding angle below 5°. The surfaces are subject to mechanical wear through scratch test and water jet impingement at 15 psi and 20 psi as well as accelerated corrosion following the ASTM-E407 standard. The performance of the electrodeposited and etched non-wetting surfaces is systematically assessed in terms of contact and sliding angles and corrosion rate in a simulated marine environment. All surfaces are shown to be robust to mechanical wear after scratch test, with excellent stability of contact and sliding angles, and up to two orders of magnitude reduced corrosion rate compared to bare copper surface. SHS retained steadfast non-wetting characteristics under high-pressure water jet tests compared to the other surfaces while LIS, regardless of texturing method, showed one to two orders of magnitude reduced corrosion rate compared to bare copper surface throughout water jet impingement and chemical durability tests. The study presents for the first time a systematic comparison of durability of SHS and LIS through a common set of fabrication and testing protocol and helps identify appropriate non-wetting surfaces and fabrication methods based on the use environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Efficient distributed continual learning for steering experiments in real-time

Deep learning has emerged as a powerful method for extracting valuable information from large volumes of data. However, when new training data arrives continuously (i.e., is not fully available from the beginning), incremental training suffers from catastrophic forgetting (i.e., new patterns are reinforced at the expense of previously acquired knowledge). Training from scratch each time new training data becomes available would result in extremely long training times and massive data accumulation. Rehearsal-based continual learning has shown promise for addressing the catastrophic forgetting challenge, but research to date has not addressed performance and scalability. To fill this gap, we propose an approach based on a distributed rehearsal buffer that efficiently complements data-parallel training on multiple GPUs to achieve high accuracy, short runtime, and scalability. It leverages a set of buffers (local to each GPU) and uses several asynchronous techniques for updating these local buffers in an embarrassingly parallel fashion, all while handling the communication overheads necessary to augment input minibatches using unbiased, global sampling. We further propose a generalization of rehearsal buffers to support both classification and generative learning tasks, as well as more advanced rehearsal strategies (notably Dark Experience Replay, leveraging knowledge distillation). We illustrate this approach with a real-life HPC streaming application from the domain of ptychographic image reconstruction. Furthermore, we run extensive experiments on up to 128 GPUs of the ThetaGPU supercomputer to compare our approach with baselines representative of training-from-scratch (the upper bound in terms of accuracy) and incremental training (the lower bound). Results show that rehearsal-based continual learning achieves a top-5 validation accuracy close to the upper bound, while simultaneously exhibiting a runtime close to the lower bound.

Asynchronous data management↗

DOE OSTI2019

Characterization of PVD Cr, CrN, and TiN coatings on SiC

SiC ceramic matrix composites are a potential replacement for current light water nuclear reactor fuel cladding material. However, loss of fission gas via micro-cracks and corrosion remain an issue. Cathodic arc Cr, CrN, and TiN coatings were deposited on SiC tubes and plates to provide hermeticity and corrosion resistance. These coatings were characterized to determine as-deposited quality. Cross-sectional microscopy, X-ray diffraction, glow discharge optical emission spectroscopy, and scratch tests were performed to evaluate the purity, structure, and mechanical performance of the coatings. Nitride coatings had stable interfaces, but larger defects in the coatings as compared to the Cr coatings which showed cracking at the interface, but less deposition-induced defects. Despite the local state of the interface, the mechanical properties of the metallic coatings versus ceramic coatings enabled the Cr coatings to resist loads three times that of the nitride coatings during scratch tests. Finally, glow-discharge optical emission spectroscopy showed that improvement in elemental purity is needed for future coatings.

36 MATERIALS SCIENCE↗

DOE OSTI2021

High-temperature oxidation and quenching of chromium-coated zirconium alloy ATF cladding tubes with and w/o pre-damage

Chromium-coated zirconium alloys are one of the promising candidates for accident-tolerant fuel cladding (ATF) tubes for light water reactors (LWRs). In this study, the high temperature oxidation and degradation of two types of Cr coatings (cold spray and physical vapor deposition) with and without pre-damage by scratches were investigated on prototype rod segment samples filled with ZrO 2 pellets and tightly sealed with welded end caps. Isothermal tests at 1100 and 1200 °C were terminated by quenching with water; transient tests were performed up to 1500–1600 °C until complete coating failure. The positive effect of both types of Cr coatings was observed in all tests. Pre-damaged specimens showed only locally increased oxidation of the scratched zone, but no negative effects on the adjacent Cr coating. Finally, the behavior of the two types of coatings is compared and the degradation mechanisms are discussed based on hydrogen release data, extensive metallographic post-test examinations, and the current state of global research.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Porous but Mechanically Robust All-Inorganic Antireflective Coatings Synthesized using Polymers of Intrinsic Microporosity

Herein, we introduce polymer of intrinsic microporosity 1 (PIM-1) to design single-layer and multilayered all-inorganic antireflective coatings (ARCs) with excellent mechanical properties. Using PIM-1 as a template in sequential infiltration synthesis (SIS), we can fabricate highly uniform, mechanically stable conformal coatings of AlO x with porosities of ~50% and a refractive index of 1.41 compared to 1.76 for nonporous AlO x that is perfectly suited for substrates commonly used in high-end optical systems or touch screens (e.g., sapphire, conductive glass, bendable glass, etc.). We show that such films can be used as a single-layer ARC capable of reduction of the Fresnel reflections of sapphire to as low as 0.1% at 500 nm being deposited only on one side of the substrate. We also demonstrate that deposition of the second layer with higher porosity using block copolymers enables the design of graded-index double-layered coatings. AlO x structures with just two layers and a total thickness of less than 200 nm are capable of reduction of Fresnel reflections under normal illumination to below 0.5% in a broad spectral range with 0.1% reflection at 700 nm. Additionally, and most importantly, we show that highly porous single-layer and graded-index double-layered ARCs are characterized by high hardness and scratch resistivity. The hardness and the maximum reached load were 7.5 GPa and 13 mN with a scratch depth of about 130 nm, respectively, that is very promising for the structures consisting of two porous AlO x layers with 50% and 85% porosities, correspondingly. Such mechanical properties of coatings can also allow their application as protective layers for other optical coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders

We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the model on a large full simulation dataset from one detector design, and subsequently fine-tune the model on a sample with a different collider and detector design. Specifically, we use the Compact Linear Collider detector (CLICdet) model for the initial training set and demonstrate successful knowledge transfer to the CLIC-like detector (CLD) proposed for the Future Circular Collider in electron-positron mode. We show that with an order of magnitude less samples from the second dataset, we can achieve the same performance as a costly training from scratch, across particle-level and event-level performance metrics, including jet and missing transverse momentum resolution. Furthermore, we find that the fine-tuned model achieves comparable performance to the traditional rule-based particle-flow approach on event-level metrics after training on 100,000 CLD events, whereas a model trained from scratch requires at least 1 million CLD events to achieve similar reconstruction performance. To our knowledge, this represents the first full-simulation cross-detector transfer learning study for particle-flow reconstruction. These findings offer valuable insights towards building large foundation models that can be fine-tuned across different detector designs and geometries, helping to accelerate the development cycle for new detectors and opening the door to rapid detector design and optimization using machine learning.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

The Abrasion of Photovoltaic Glass: A Comparison of the Effects of Natural and Artificial Aging

Natural soiling and the subsequent requisite cleaning of photovoltaic (PV) modules result in abrasion damage to the cover glass. The durability of the front glass has important economic consequences, including determining the use of antireflective and/or antisoiling coatings as well as the method and frequency of operating maintenance (cleaning). The abrasion of coatings and glass has been explored in a field study, including the soiling-prone locations of Dubai (United Arab Emirates), Kuwait City (Kuwait), Mesa (Arizona), Mumbai (India), and Sacramento (California). Dry-brush-cleaned specimens will be compared to those subjected to artificial-brush testing. The characteristics of material integrity, surface energy, optical transmittance, surface roughness, and scratch size were examined using an optical microscope, contact goniometer (for water), spectrophotometer, interferometer, and atomic force microscope (AFM), respectively. The findings of this study will be used to provide feedback regarding the cleaning equipment, cleaning methods, and coatings used in the PV industry. The study here will also be used to aid in developing an abrasion standard for the PV industry.

14 SOLAR ENERGY↗

DOE OSTI2021

Solvent Hold Tank Sample Results for MCU-20-32-33-34 (Quarterly Report, September 2020)

In late FY13, MCU implemented the Next Generation Solvent (NGS) flow sheet. Facility personnel added a non-radioactive, NGS “cocktail” containing the new Extractant (MaxCalix) and a new Suppressor (TiDG) to the SHT heel to implement the NGS flow sheet. The resulting “blend” solvent (“NGS blend solvent”) is essentially NGS with residual amounts of calix[4]arene-bis(tert-octylbenzo-crown-6) (BOBCalixC6) and trioctylamine (TOA). For process monitoring, SHT samples are sent to Savannah River National Laboratory (SRNL) to examine solvent composition changes over time. With the exception of Isopar™ L which is regularly added to the SHT due to its high vapor pressure, this report shows the cumulative chemical composition data, including impurities like mercury, of the September 2020 (MCU-20-32-33-34) solvent SHT sample. A summary report of the September SHT solvent sample was issued earlier. This report examines the cumulative results from these and several past monthly reports. These samples are intended to verify that the solvent is within the specified composition range. A baseline “scratch” solvent - a scratch solvent is a preparation of all 6 solvent components (this includes the old extractant BoBCalix and the old suppressor TrioctylAmine that remained when solvent was converted to Next Generation Solvent [NGS]) of the composition that approximates the blend of cocktail and heel solvent - was prepared in the lab (September 2018) and used for comparison and evaluation. The results from the analyses are presented in this document. This report is the last characterization analysis of the SHT solvent. MCU entered a lay-up state and about 128 gallons of the SHT solvent were pumped into 55 gallons drums for future disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Corrosion of Zinc Cold Spray Coatings in a Wet Sweet and Sour Gas Environment

Internal corrosion is a problem for steel pipelines transporting natural gas or CO 2 containing water and partial pressures of H 2 S higher than 0.3 kPa (0.05 psi). This work aims to mitigate internal corrosion in steel pipelines transporting natural gas containing H 2 S using cold spray coatings. Two types of the cold spray binary metallic coatings (zinc chromium [ZnCr]. zinc niobium [ZnNb]) were studied using electrochemical techniques: potentiodynamic polarization, linear polarization resistance, and electrochemical impedance spectroscopy. The corrosion resistance of cold spray coatings (ZnCr, ZnNb) was evaluated in an environment containing 4 bar CO 2 pressure, simulating the partial pressures found in gas transmission lines over a solution of 3.5 wt% NaCl heated to 40°C. A concentration of 0.003 M Na 2 S 2 O 3 ·5H 2 O, corresponding to H 2 S partial pressures around 0.079 bar (1.146 psi), was used to simulate sour conditions. Postcorrosion surface characterization was performed using a scanning electron microscope (SEM) equipped with an energy-dispersive x-ray spectroscope (EDS) and x-ray diffraction analysis. The data showed that the presence of 0.003 M Na 2 S 2 O 3 ·5H 2 O shifted the corrosion potential to more anodic values and decreased the corrosion current density. Both coatings showed similar behavior after 1 h of exposure in the CO 2 /H 2 S environment, indicating that similar electrochemical reactions were occurring on ZnNb and ZnCr. SEM images and EDS surface analyses for specimens showed a significant change in the surface chemical composition of carbon steel coated with ZnNb and ZnCr after 24 h of immersion. In the presence of thiosulfate (under sour conditions), the formation of corrosion product layers (ZnCO 3 and ZnS) on top of ZnNb and ZnCr coatings increased their corrosion resistance, which helped to reduce their corrosion by a factor of 2. Under a sweet environment, the corrosion rates for steel coated with cold spray coatings after 14 d of exposure are lower than that for galvanized steel by a factor of 5 due to the ZnCO 3 layer formed on top of the coatings. The ZnCO 3 layer formed on the steel surface acts as a physical barrier against corrosion by blocking the diffusion of corrosive species to the surface. No localized attack was observed. ZnCr Cold spray coating with defect showed promising corrosion protection against CO 2 corrosion (sweet corrosion) after 14 d of exposure to a CO 2 environment. Here, the scratch on the coating simulated damage created in service, and it was deep enough to expose the substrate material (steel). The formation of zinc oxide (ZnO) and zinc carbonate (ZnCO 3 ) on the scratch confirmed the cathodic protection of the steel by ZnCr and ZnNb coatings.

36 MATERIALS SCIENCE↗

NASA NTRS1975

Evaluation of anomalies observed on film from S-190A flight system calibration test

Due to a persistent problem of scratched film from testing of the Skylab S-190A system, a series of tests were designed to identify the cause of the film scratching. The procedures followed in this test for pretest handling and packaging of the film, the makeup of the rolls for processing, and the results of the processed film evaluation are reported.

Bourque, P. F.↗

NASA NTRS1976

The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

Athale, R.↗