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At least 865 records · Page 48

Characterization of boundary precipitation in a heavy ion irradiated tungsten heavy alloy under the simulated fusion environment

In the concerted effort to identify materials capable of surviving the adverse environment of a fusion reactor interior, tungsten heavy alloys have been put forth as leading candidates. Experimental trials and behavioral studies have yielded positive results for their adoption by taking advantage of the alloy’s unique balance of inherently high fracture toughness and low sputter yields; yet due to their relative novelty in the fusion community, there remains a lack of understanding on the response of these materials to the extended high temperature irradiation environment of the reactor interior. Further, to alleviate this issue and provide the necessary data on the behavior of tungsten heavy alloys to the simulated fusion environment, a 90W-7Ni-3Fe alloy has been subjected to elevated temperature sequential Ni + and He + ion irradiations to mimic the expected displacement damage and gas production expected after five years of service as a plasma facing material component. Atomic-scale structural analyses and nanoscale chemical mapping have identified the formation of two distinct precipitation structures, a surface localized η-carbide and an a-W 2 C type tungsten carbide, both of which appear to originate at the bi-phase interface between W and the ductile phase. This irradiation assisted and induced precipitate formation respectively is anticipated to adversely affect these materials by selective embrittlement at bi-phase interfaces leading to a reduction in the material’s overall fracture toughness during prolonged high temperature irradiation. It is asserted that any potential exposure to C during fusion reactor operational service should be minimized as to prevent the formation of these phases.

36 MATERIALS SCIENCE↗

Crystal plasticity model of BCC metals from large-scale MD simulations

Accurate crystal plasticity models that faithfully capture the behavior of single crystals under a wide range of loading conditions, such as loading direction, strain rate, and temperature, are still lacking. Here we introduce a novel approach in which a crystal plasticity (CP) model is informed directly from and calibrated to large-scale quantum-accurate MD simulations in which single crystal BCC Ta serves as a testbed material. By analyzing our large set of MD simulations several key insights are obtained leading us to modify constitutive assumptions in order to address deficiencies of existing CP models. Importantly, we observe that the standard notion of fixed slip systems – pairs of slip directions and slip planes – is inadequate for describing high-rate plasticity in BCC tantalum at room temperature. Instead, pencil glide defined as dislocation motion in the maximum resolved shear stress planes (MRSSP) of each Burgers vector is fully consistent with our MD simulation data while providing significant simplifications of the constitutive relations. Herein, our resulting new CP model closely matches the behavior of single crystals observed in high-rate MD simulations while being fully consistent with lower rate experimental results.

36 MATERIALS SCIENCE↗

Enhanced mobility of dislocation network nodes and its effect on dislocation multiplication and strain hardening

Understanding plastic deformation of crystals in terms of the fundamental physics of dislocations has remained a grand challenge in materials science for decades. To overcome this, the Discrete Dislocation Dynamics (DDD) method has been developed, but its lack of atomistic resolution leaves open the possibility that certain key mechanisms may be overlooked. Here, by comparing large-scale Molecular Dynamics (MD) with DDD simulations performed under identical conditions we uncover significant discrepancies in the predicted strength and microstructure evolution in BCC crystals under high-strain rate conditions. These are traced to unexpected behaviors of dislocation network nodes forming at dislocation intersections, that can move in ways not previously anticipated as revealed by MD. Once these newfound freedoms of nodal motion are incorporated, DDD simulations begin to closely match plastic evolution observed in MD. This additional mechanism of motion whereby non-screw dislocations can change their glide plane profoundly affects fundamental processes of dislocation multiplication, recovery and storage that define strength of metals.

36 MATERIALS SCIENCE↗

Ultimate compressive strength and severe plastic deformation of equilibrated single-crystalline copper nanoparticles

Mechanical properties and deformation mechanisms of defect-free copper nanoparticles are investigated by combining experiments with atomistic simulations. The compressive strength of the particles increases with decreasing size and tends to saturate near the theoretical strength in the small-size limit. In this limit, the intrinsic size dependence of the strength is governed by the stochastic nature of dislocation nucleation near the particle surface. The particle deformation process evolves from the initial strain softening to strain hardening as the particle accumulates residual damage. The normalized strength-size relation for Cu is compared with those for Au, Ni, and Pt. The lack of universal behavior among the four FCC metals is discussed. Heavily deformed Cu nanoparticles develop polycrystalline structures and change the lattice orientation from [111] to [110]. The experiments and simulations reveal the twinning mechanism of the lattice rotation leading to the new grain formation.

36 MATERIALS SCIENCE↗

Exploring the relationship between deposition method, microstructure, and performance of Nb/Si-based superconducting coplanar waveguide resonators

Superconducting quantum circuits (SQC) are one of the most promising hardware platforms for quantum computing, yet their performance is currently limited by the presence of various structural defects inside the circuit's structure. Despite impressive progress in the past decade, a precise understanding of the origin of these defects from various fabrication processes and their impact on coherence is still lacking. Here, in this study, we performed a comprehensive investigation on the microstructure, superconductivity, and resonator quality factor of Nb films deposited by high-power impulse magnetron sputtering (HiPIMS) and direct current (DC) magnetron sputtering. A suite of characterization techniques, including electron microscopy with spectroscopy, secondary ion mass spectrometry, magneto-optical microscopy, and pump-probe reflectivity spectroscopy is used. We reveal that niobium (Nb) resonators fabricated using HiPIMS exhibit a smaller average grain size, thicker surface oxide with larger thickness variations (rougher surface), and a thicker amorphous Nb/Si interface layer compared to samples deposited by DC sputtering. We identified that the amorphous Nb oxides (mainly located at the Nb surface and along the grain boundaries) and Nb-Si amorphous layers (at the Nb/Si interface) are major and potential sources of two-level system (TLS), while off-stochiometric oxides and suboxides of Nb close to the surface, crystalline defects (i.e., dislocations at grain boundary, point defects introduced during deposition) are main contributors of non-TLS sources. Our findings clarify the relationship between different defects and coherence loss mechanisms, highlighting the importance of material microstructure control on performance optimization in SQC.

36 MATERIALS SCIENCE↗

In-situ ETEM study of plasma-facing tungsten nanofuzz oxidation at atmospheric pressure: Microstructure evolution and substrate-free oxidation kinetics

To enable sustainable carbon-free fusion energy, managing reactor structural material degradation during normal operation as well as accident scenarios is vital. Tungsten (W) plasma-facing materials (PFMs) are susceptible to aggressive high-temperature oxidation during air-ingress fusion reactor accidents, yet there's a lack of oxidation kinetic data for irradiated tungsten. Here, in this study, we utilize atmospheric environmental transmission electron microscopy (ETEM) to present the first kinetic data for substrate-free W nanofuzz oxidation at 400 ºC and 500 ºC in 1 bar dry air. Comparison with pristine bulk W during the early parabolic stage suggests an irradiationdecelerated oxidation for W nanofuzz. Our time-resolved in-situ characterization reveals a durable amorphous surface oxide, likely promoted by high-flux He + irradiation-induced surface defects, serving as an effective passivating layer that impedes nanofuzz oxidation onset. This surface oxide layer also interfaces well with newly formed orthorhombic WO 3 , facilitated by stress relief through He bubble shrinkage, providing lasting passivating protection throughout the nanofuzz parabolic oxidation. This new finding challenges conventional notions of irradiation's negative impact on metal oxidation, and calls for advanced characterization to enhance our understanding of fusion energy materials degradation, informed by further accident modeling.

36 MATERIALS SCIENCE↗

A model for oblique impacts on material surfaces

Many practical situations of material damage, wear, and erosion involve collisions between small particles and surfaces at inclined angles. While there are many well-validated models of normal incidence impact situations, elastic-plastic models for oblique incidence impact events are lacking. Here the finite element method is used to predict the normal and tangential coefficient of restitution in oblique impacts for hard, elastic spheres impacting an elastic-perfectly plastic material surface. The proposed model covers various impact angles ranging from 0° to 45°, within a limiting impact velocity below which the effects of heating are negligible. The normal coefficient of restitution follows power-laws with respect to normalized values of the impact velocity. Interestingly, the tangential coefficient of restitution follows a linear relationship with impact velocity. Together, these results provide a semi-empirical set of equations predicting oblique impact rebounds (both velocity and trajectory) for a wide range of conditions and material properties, with which experimental results can be rapidly interpreted. As a result, Laser-Induced Particle Impact Test (LIPIT) data are also presented for aluminum particles impacting aluminum substrates, at impact angles of 25° and 40°; the results compare favorably with the model and validate the general use of such models for the analysis of experimental data.

Coefficient of restitution↗

Local chemical ordering of a neutron-irradiated CrFeMnNi compositionally complex alloy

While ion-irradiation studies are a critical first step in studying compositionally complex alloys (CCAs) for nuclear applications, they do not capture all the microstructural changes occurring under the low irradiation dose rates and different particles’ scattering patterns experienced in a nuclear reactor setting. To explore these phenomena in reactor-relevant conditions for the first time in CCA, the single-phase solid-solution Cr 10 Fe 30 Mn 30 Ni 30 was neutron irradiated up to 6.61 displacements per atom at 395 and 579 °C. Irradiation-enhanced local chemical ordering (LCO) well beyond the range of short range ordering was observed, and is predicted to be the precursor to the precipitation of a coherent Ni-Mn L1 0 phase and a Cr-rich α’ phase, though TEM analysis did not indicate the presence of either in any irradiation condition. The line density of faulted dislocation loops decreased from 6.47 to 1.69 ∙ 10 15 m -2 from 3.43 to 6.61 dpa at 579 °C despite no appreciable faulted loop content in the unirradiated material. LCO is expected to increase the complexity of the energy landscape within this alloy, restricting interstitial point defect mobility and creating local regions of greater stacking fault energy. These contribute to the negative correlation between irradiation dose and faulted dislocation loop density in this study, as well as the lack of void swelling observed.

36 MATERIALS SCIENCE↗

Grain boundary segregation in BCC vanadium-based alloys: Quantum-accurate computed segregation spectra and targeted experimental validations

Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Furthermore, using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. Furthermore, the agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.

Fusion materials↗

The structure and migration of twin boundaries in tetragonal β -Sn: An application of machine learning based interatomic potentials

Although atomistic simulations have contributed significantly to our understanding of twin boundary structure and migration in metals and alloys with hexagonal close packed (HCP) crystal structures, few direct atomistic studies of twinning have been conducted for other types of low symmetry materials, in large part due to a lack of reliable interatomic potentials. In this work, we examine twin boundary structure and migration in a tetragonal material, β-Sn, comparing high resolution Transmission Electron Microscopy (TEM) images of deformation twins in β-Sn to the results of direct atomistic simulations using multiple interatomic potentials. ML-based potentials developed in this work are found to give results consistent with our experimental data, revealing faceted twin boundary structures formed by the nucleation and motion of twinning disconnections. We use bicrystallographic methods in combination with atomistic simulations to analyze the structure, energy and shear coupled migration of observed twin facets in β-Sn. In analogy to Prismatic-Basal (PB/BP) interfaces in HCP metals, we discover low energy asymmetric Prismatic-A-plane (PA/AP) interfaces important to twin growth in β-Sn. Finally, a Moment Tensor Potential (MTP) and Rapid Artificial Neural Network (RANN) interatomic potential suitable for studying twinning and phase transformations in Sn are made publicly available as part of this work.

36 MATERIALS SCIENCE↗

Formation of carbon homonuclear bonds in β-SiC under neutron irradiation at various temperatures and neutron doses

To elucidate radiation defect processes in SiC, Raman spectroscopy was systematically applied to high-purity, polycrystalline β-SiC that was neutron irradiated at a range of temperature and dose conditions. The analysis specifically focused on formation of carbon homonuclear bonds by irradiation; these bonds were indicated by D and G bands and amorphous carbon peaks. Intensity of the carbon peaks relative to SiC peaks significantly decreased in the case of high temperature and/or high neutron dose of 500 °C to 29 displacements per atom (dpa) and about 800 °C to 1.38 and 29 dpa. The absence of carbon bond peaks under those conditions was explained by growth of stoichiometric defect clusters, consistent with previous atomistic simulations on SiC defect stability. The lack of Raman bands associated with carbon clusters under high-temperature and high-dose radiation conditions accounts for the resistance of SiC to phase separation under irradiation. The findings further suggest that material compositions and chemical properties that are inherently resistant to chemical disordering under high-dose radiation conditions are indicative of the long-term durability of ceramic compounds in radiation environments.

36 MATERIALS SCIENCE↗

Predicting transport of intra-articularly injected growth factor fusion proteins into human knee joint cartilage

There are no drugs or treatment methods known to prevent the development of post-traumatic osteoarthritis (PTOA), a type of osteoarthritis (OA) that is triggered by traumatic joint injuries and accounts for ~12% of the nearly 600 million OA cases worldwide. Lack of effective drug delivery techniques remains a major challenge in developing clinically effective treatments, but cationic delivery carriers can help overcome this challenge. Scaling up treatments that are effective in in vitro models to achieve success in preclinical in vivo models and clinical trials is also a challenging problem in the field. Here we use a cationic green fluorescent protein (GFP) as a carrier to deliver Insulin-Like Growth Factor 1 (IGF-1), a drug considered as a potential therapeutic for PTOA. GFP-IGF-1 conjugates were first synthesized as fusion proteins with different polypeptide linkers, and their transport properties were characterized in human cartilage explants. In vitro experimental data were used to develop a predictive mathematical transport model that was validated using an independent in vitro experimental data set. In this study, the model was used to predict the transport of these fusion proteins upon intra-articular injection into human knee joints. The predictions included results for the rate and extent of fusion protein penetration into cartilage, and the maximum levels of fusion proteins that would escape into systemic circulation through the joint capsule. Together, our transport measurements and model set the stage for translation of such explant culture studies to in vivo preclinical studies and potentially clinical application.

36 MATERIALS SCIENCE↗

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗

Active and passive cooling approaches for a Southern California residential community

This study assesses cooling strategies in a low-income community in Southern California that lacks air conditioning and struggles with heat and air pollution. We used an urban building energy model and an electric distribution system model to evaluate active and passive cooling measures. The most effective space cooling measures were high-performance air-source heat pumps, cool coatings, window films, and harnessing the space cooling effect from heat pump water heaters. The results show that combining heat pump water heaters with window films and cool coatings reduces heat index hazard hours within buildings by 95 % to 99 % but increases total energy costs (equipment costs plus changes in utility bills) by 20 % to 60 % where the higher end includes building electrical upgrades. These measures also led to increased space heater use during colder months to avoid overcooling. Replacing conventional heaters with air source heat pumps eliminated unsafe indoor temperatures and reduced total energy use, but increased cost by 125 % to 150 %. In total, using heat pumps for space and water heating could reduce primary energy use by up to 57 %. The higher cost of active and passive cooling measures can be mitigated by existing and emerging incentive programs, especially those that support heat pumps. Electric distribution upgrades to support community electrification are estimated to increase utility costs by $\$$25 to $\$$40 per ratepayer per year. The results underscore the potential and challenges of adapting building infrastructure in communities at risk from climate and environmental stressors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mitigating keyhole pore formation by nanoparticles during laser powder bed fusion additive manufacturing

Keyhole pore formation is one of the most detrimental subsurface defects in the laser metal additive manufacturing process. However, effective ways to mitigate keyhole pore formation beyond tuning laser processing conditions during keyhole mode laser melting are still lacking. Here we report a novel approach to mitigate keyhole pore formation during laser powder bed fusion (LPBF) process by using stable nanoparticles. The critical keyhole depth for keyhole pore generation (i.e., the largest keyhole depth without keyhole pore formation) during LPBF of Al6061 increases from 246 µm to 454 µm (85% increase) after adding TiC nanoparticles. In-depth x-ray imaging studies and thermo-fluid dynamics simulation enable us to identify that two mechanisms work together to mitigate keyhole pore generation: (1) adding nanoparticles prevents the keyhole from collapsing by increasing the liquid viscosity to impede the protrusion development; (2) adding nanoparticles slows down the keyhole pore movement by increasing the liquid viscosity, resulting in the recapturing of the pore by the keyhole. We further demonstrate that adding TiC nanoparticles can also eliminate the keyhole fluctuation induced keyhole pore during LPBF of Al6061. Our research provides a potential way to mitigate keyhole pore formation for defect lean metal additive manufacturing.

36 MATERIALS SCIENCE↗

High-throughput surface characterization to identify porosity defects in additively manufactured 316L stainless steel

In the present study, a high throughput (HT) methodology is applied to rapidly assess the surface characteristics of 83 additively manufactured 316L stainless steel. The variation in surface roughness (S a ) showed a good correlation with a dimensionless number (π) and provided direct linkages to the internal porosity defects. Lack-of-fusion regime relates to high surface roughness (S a > 5 µm), low dimensionless number (π < 61), and the presence of cavities in between the melt pool tracks. Balling regime correlates to high surface roughness (S a > 5 µm), intermediate dimensionless number (61 < π < 146), and non-uniform melt pool track width. Keyhole regime shows low surface roughness (S a < 5 µm), high dimensionless number (π > 146), and a curved melt pool track. This approach accelerates the process parameter discovery and minimizes the porosity defects for the LPBF process. The impact of the defects on the as-processed tensile mechanical properties demonstrates that samples with porosity exhibit up to 10% less tensile strength and 30% less ductility than optimal samples.

316L stainless steel↗

A non-melting additive approach to structural repair of aluminum aircraft fastener holes

The damage to fastener holes in aerospace aluminum structures presents significant challenges for aircraft durability, and conventional bushing methods for repairing oversized holes often fall short due to the lack of metallurgical bonding and limited edge distance availability. This study investigates additive friction stir deposition, a non-melting additive process, as a viable alternative for the structural repair of aerospace fastener holes. The repair process, demonstrated on AA7050 (Al-Zn-Mg-Cu-Zr) hole structures, involves filling oversized holes with new material and machining to restore the original hole size. The repaired hole coupons are defect-free and exhibit good fatigue performance under fully reversed tension-compression loading (R = -1). At a nominal stress amplitude of 123.5 MPa, the average number of cycles to failure is 12,666 for unrepaired baseline coupons and 17,372 for effectively repaired coupons. Restoring complex geometries without compromising fatigue performance has been difficult in aerospace applications; this study marks the first demonstration of additive repair that consistently outperforms the unrepaired baseline coupons. Notably, the result is achieved through a low-energy, cost-effective solution without the need for post-repair heat treatment. Except for a few outliers, the post-repair fatigue performance generally remains inferior to that of undamaged, pristine coupons, likely due to precipitate evolution in AA7050 caused by the thermomechanical processing nature of additive friction stir deposition. This evolution weakens the repair region and the adjacent base material, leading to faster crack initiation and growth compared to the properly aged base material, AA7050-T7451.

36 MATERIALS SCIENCE↗

Area-based composition predictions of materials fabricated using simultaneous wire-powder-directed energy deposition

Functionally graded materials are an emergent method for designing components with programmable site-specific material properties. These materials are typically fabricated using metal additive manufacturing tools by simultaneously feeding multiple wire and/or powder feedstocks at various rates to achieve spatial composition change. The wire-powder-directed energy deposition (WP-DED) technique is of particular interest for many functionally graded material applications by balancing the low raw materials cost of wire with the high resolution of powder. However, feeding wire and powder are inherently different processes since all extruded wire enters the melt pool, while much of the blown powder is scattered, which makes determining the composition of the build challenging. In this study, we devise a simple area-based measurement method for estimating the composition of WP-DED structures. WP-DED single beads are printed using 309L stainless steel wire and commercially pure Fe powder at five wire feed rates (0.5, 0.75, 1.00, 1.25, 1.50 mm/mm) and five powder feed rates (2, 4, 6, 8, 10 rpm). Characteristic defects including interface gaps and macrosegregation (lack of mixing) tendencies are examined. High powder feed rates (8, 10 rpm) result in interface gaps at all wire feed rates, but smooth deposition and complete mixing is achieved at low powder feed rates, particularly with lower wire feed rates as well. The area-based composition measurement method is within ±20% of energy dispersive x-ray spectroscopy measurements for all samples, showing its effectiveness as a rapid composition estimate for WP-DED materials development.

36 MATERIALS SCIENCE↗