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At least 235 records · Page 13

Excellent high cyclic fatigue properties of a novel ultrafine-grained medium entropy alloy

Fatigue is a major cause of failure and requires dedicated investigation to validate the integrity of potential structural materials. As high and medium entropy alloys (HEAs and MEAs) are garnering significant attention from scientific communities, it is important to test the structural integrity of these novel alloys in cyclic loading environment. This study analyzed both monotonic and cyclic loading properties of a novel medium entropy alloy (MEA) CoCr 1.3 Ni in the ultrafine-grained (UFG) and fine grain (FG) conditions. The UFG MEA performs better than the FG MEA during cyclic loading. Microstructural evolution after cyclic loading via electron back-scattered diffraction shows microstructural stability of both FG and UFG microstructures. Transmission electron microscopy suggests formation of stacking faults and fine-scale HCP transformation during cyclic loading.

36 MATERIALS SCIENCE↗

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗

Exceptional Mineral Scaling Resistance from the Surface Gas Layer: Impacts of Surface Wetting Properties and the Gas Layer Charging Mechanism

Mineral scaling is a phenomenon that occurs on submerged surfaces in contact with saline solutions. In membrane desalination, heat exchangers, and marine structures, mineral scaling reduces process efficiency and eventually leads to process failure. Therefore, achieving long-term scaling resistance is beneficial to enhancing process performance and reducing operating and maintenance costs. While evidence shows that superhydrophobic surfaces may reduce mineral scaling kinetics, prolonged scaling resistance is limited due to the finite stability of the entrained gas layer present in a Cassie–Baxter wetting state. Additionally, superhydrophobic surfaces are not always feasible for all applications, but strategies for long-term scaling resistance with smooth or even hydrophilic surfaces are often overlooked. In this study, we elucidate the role of interfacial nanobubbles on the scaling kinetics of submerged surfaces of varied wetting properties, including those that do not entrain a gas layer. We show that both solution conditions and surface wetting properties that promote interfacial bubble formation enhances scaling resistance. In the absence of interfacial bubbles, scaling kinetics decrease as surface energy decreases, while the presence of bulk nanobubbles enhances the scaling resistance of the surface with any wetting property. The findings in this study allude to scaling mitigation strategies that are enabled by solution and surface properties that promote the formation and stability of interfacial gas layers and provide insights to surface and process design for greater scaling resistance.

calcite↗

Low Temperature Cyclic Deformation Behavior of Ultrafine-grained Pure Magnesium (Final Technical Report)

The primary goal of the project is to explore the fundamental deformation and fatigue failure mechanisms for magnesium with a hexagonal close packed (HCP) crystal structure. It is important to perform the project for several reasons. Firstly, magnesium is the lightest structural metal and its application in various structural components can reduce the final component weight.

36 MATERIALS SCIENCE↗

Impact of Laboratory-Accelerated Aging Methods to Study Alkali–Silica Reaction and Reinforcement Corrosion on the Properties of Concrete

This study focuses on two separate investigations of the main aging mechanisms: alkali–silica reactivity (ASR) and the corrosion of reinforcing steel (rebar) concrete, both of which may result in a premature failure to meet the serviceability or strength requirements of a concrete structure. However, these processes occur very slowly, spanning decades. The impact of direct chemical additives to fresh concrete to accelerate ASR and the corrosion of reinforcing steel on the fresh and hardened properties of the ensuing material are investigated to inform the potential use of chemicals in large-scale studies. The deterioration of reinforced concrete (RC) is determined by means of expansion, cracking, bulk diffusivity and surface resistivity measurements, and compressive, split tensile and flexural strength tests. The results indicate that the addition of sodium hydroxide and calcium chloride can effectively accelerate the crack formation and propagation in concrete due to ASR and the corrosion of rebar, respectively. The ASR-induced cracks maintained a constant crack width from 0.05 mm to 0.1 mm over the measurement period regardless of the intensity of aging acceleration. Adding 4% chloride by weight of cement for accelerating rebar corrosion resulted in an average crack that was 82% larger than in the case of ASR accelerated with the addition of sodium hydroxide. The addition of alkali resulted in an increase in early-age (7-day) strength. At a total alkali loading of 2.98 kg/m3, 3.84 kg/m3 and 5.57 kg/m3, the 28-day compressive strength of concrete decreased by 3%, 10% and 24%, respectively. Similarly, a higher early-age strength and a lower later-age strength was observed for the concrete in the presence of corrosive calcium chloride. The results from this research are expected to inform future studies on the long-term performance of RC structures under accelerated ASR and corrosion.

36 MATERIALS SCIENCE↗

Real-Time Observation of Nanoscale Kink Band Mediated Plasticity in Ion-Irradiated Graphite: An In Situ TEM Study

Graphite IG-110 is a synthetic polycrystalline material used as a neutron moderator in reactors. Graphite is inherently brittle and is known to exhibit a further increase in brittleness due to radiation damage at room temperature. To understand the irradiation effects on pre-existing defects and their overall influence on external load, micropillar compression tests were performed using in situ nanoindentation in the Transmission Electron Microscopy (TEM) for both pristine and ion-irradiated samples. While pristine specimens showed brittle and subsequent catastrophic failure, the 2.8 MeV Au2+ ion (fluence of 4.378 × 1014 cm−2) irradiated specimens sustained extensive plasticity at room temperature without failure. In situ TEM characterization showed nucleation of nanoscale kink band structures at numerous sites, where the localized plasticity appeared to close the defects and cracks while allowing large average strain. We propose that compressive mechanical stress due to dimensional change during ion irradiation transforms buckled basal layers in graphite into kink bands. The externally applied load during the micropillar tests proliferates the nucleation and motion of kink bands to accommodate the large plastic strain. The inherent non-uniformity of graphite microstructure promotes such strain localization, making kink bands the predominant mechanism behind unprecedented toughness in an otherwise brittle material.

36 MATERIALS SCIENCE↗

Physical Properties of Hilti HIT-RE 500 V3 After Irradiation: Slant Shear, Tensile, Flexural, and Compressive

There are various applications in which epoxy adhesives may be used within hot-cell environments. These epoxies currently see limited use within hot cells since it is known that organics see degradation after small doses even as low as 50 kilogray (kGy). These losses in physical property strengths limit the use of these epoxies to non-structural applications. In modern construction, however, the use of epoxies to bond structural components such as rebar or threaded anchors is becoming increasingly prevalent. To employ these types of materials the Idaho National Laboratory (INL) has begun investigating the specific degradation properties of epoxies for use in structural applications in environments where radiation is present. Hilti HIT-RE 500 V3 is used extensively in new construction and renovation projects across the world. The INL has conducted various tests on this epoxy for low dose environments. These tests include tensile, flexural, compression, and slant shear tests following the American Society for Testing Material International (ASTM) standards D638, D790, D695, and C882/882M respectively. Two sample sets for each test were created where the baseline specimens were not irradiated, and another set was irradiated to an accumulated dose of approximately 50-60 kGy. All the samples were destructively tested and analyzed focusing on the change in physical properties, examples of these tests are shown in Figures 1-4. Tensile testing results indicate a 0.9% loss in maximum load capacity, a 0.5% loss in tensile stress at maximum load, a 1.4% loss in tensile strain at break, and a 15% decrease in modulus of elasticity. Flexural testing results display an increase in all the following: 12% in strain at maximum load, 10% in maximum load capacity, 5% in stress at maximum load, and 3% in young’s modulus. The compressive physical properties after irradiation display a 1% increase in maximum load, a 3% decrease in stress at yield, and a 5% decrease in modulus of elasticity. The maximum compressive stress saw no measurable change after irradiation. The slant shear specimens after irradiation displayed a 2% increase in maximum load capacity and maximum compressive stress. Though a structural analysis would have to be completed as is normal for building design the increases and decreases in the measured physical properties indicate that this material may be used for structural applications in low dose hot-cell environments without adhesive failure.

36 MATERIALS SCIENCE↗

Role of tilt grain boundaries on the structural integrity of WSe 2 monolayers

Transition metal dichalcogenides (TMDCs) are potential materials for future optoelectronic devices. Grain boundaries (GBs) can significantly influence the optoelectronic properties of TMDC materials. Here, we have investigated the mechanical characteristics of tungsten diselenide (WSe 2 ) monolayers and failure process with symmetric tilt GBs using ReaxFF molecular dynamics simulations. In particular, the effects of topological defects, loading rates, and temperatures are investigated. We considered nine different grain boundary structures of monolayer WSe 2 , of which six are armchair (AC) tilt structures, and the remaining three are zigzag (ZZ) tilt structures. Our results indicate that both tensile strength and fracture strain of WSe 2 with symmetric tilt GBs decrease as the temperature increases. We revealed an interfacial phase transition for high-angle GBs reduces the elastic strain energy within the interface at finite temperatures. Furthermore, brittle cracking is the dominant failure mode in the WSe 2 monolayer with tilted GBs. WSe 2 GB structures showed more strain rate sensitivity at high temperatures than at low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Targeted mutagenesis of the herpesvirus fusogen central helix captures transition states

Herpesviruses remain a burden for animal and human health, including the medically important varicella-zoster virus (VZV). Membrane fusion mediated by conserved core glycoproteins, the fusogen gB and the heterodimer gH-gL, enables herpesvirus cell entry. The ectodomain of gB orthologs has five domains and is proposed to transition from a prefusion to postfusion conformation but the functional relevance of the domains for this transition remains poorly defined. Here we describe structure-function studies of the VZV gB DIII central helix targeting residues 526 EHV 528 . Critically, a H527P mutation captures gB in a prefusion conformation as determined by cryo-EM, a loss of membrane fusion in a virus free assay, and failure of recombinant VZV to spread in cell monolayers. Importantly, two predominant cryo-EM structures of gB[H527P] are identified by 3D classification and focused refinement, suggesting they represented gB conformations in transition. These studies reveal gB DIII as a critical element for herpesvirus gB fusion function.

59 BASIC BIOLOGICAL SCIENCES↗

Mapping 3D grain and precipitate structure during in situ mechanical testing of open-cell metal foam using micro-computed tomography and high-energy X-ray diffraction microscopy

Open-cell metal foams are ultra-low-density cellular metals with complex hierarchical structures that span bulk, cell, ligament, and sub-ligament scales and give rise to desirable properties such as high strength-to-weight ratio and excellent energy absorption. Although literature suggests that intrinsic material structures at sub-ligament length scales (e.g., grains and precipitates) play an important role in mechanical behavior of open-cell metal foams, there are very few experimental measurements of such structures in three dimensions and for meaningful volumes of foam. This study seeks to map and track the three-dimensional (3D) grain and precipitate structures of an intact volume of open-cell aluminum foam by advancing microstructural characterization techniques that leverage X-ray micro-computed tomography (μCT) and far-field high-energy X-ray diffraction microscopy (FF-HEDM). A 6%-relative-density aluminum foam sample was mechanically tested in compression while μCT and FF-HEDM measurements were collected at interrupted loading states at beamline 1-ID of the Advanced Photon Source. Further, a new scanning strategy and reconstruction algorithm were established to enable characterization of a foam volume with diameter approximately four times wider than the nominal width of the X-ray beam. The result is a set of maps that detail both the 3D grain and precipitate structures throughout the foam volume at successive strain steps. A novel grain tracking procedure was developed to track individual grains within the foam volume by accounting for the large rigid-body motions that individual ligaments can undergo during mechanical loading. The ability to track grains and precipitate structures in three dimensions throughout large bulk deformation of ultra-low-density polycrystalline materials enables new possibilities for validating numerical models and investigating local failure mechanisms. Furthermore, the methods and procedures developed in this study could be applied to other ultra-low-density structures, such as additively manufactured lattices.

36 MATERIALS SCIENCE↗

Impacts of Dissolved Ni 2+ on the Solid Electrolyte Interphase on a Graphite Anode

Transition metal (e.g. Ni) ions dissolved from layered-structured Ni-rich cathodes can migrate to the anode side and accelerate the failure of lithium-ion batteries. The investigations of the impact and distribution of Ni species on the solid electrolyte interphase (SEI) on the anode are crucial to understand the failure mechanism. Herein, we used time-of-flight secondary ion mass spectroscopy (TOF-SIMS) coupled with multivariate curve resolution (MCR) analysis to intuitively characterize the distribution of Ni species in the SEI. We find that the SEI on the graphite electrode using an EC-based electrolyte exhibits a multi-stratum structure. During accelerated aging of the LiNi 0.88 Co 0.08 Mn 0.04 O 2 /graphite full cell, the dissolution of Ni aggravates significantly upon cycling. A strong correlation between the dissolved-Ni and organic species in the SEI on graphite is illustrated. Here, the ion-exchange reaction between Ni 2+ and Li + ions in the SEI is demonstrated to be the main reason for the increase of SEI resistivity.

25 ENERGY STORAGE↗

Creep behavior of an additively manufactured 9Cr steel in the as-built condition

Limited studies have evaluated the creep behavior of additively manufactured (AM) ferritic-martensitic (FM) steels. This work investigated the creep behavior of a 9Cr FM steel fabricated by powder blown directed energy deposition (DED) technique. Here, the creep testing at 550–650 °C and 150 MPa for the specimens along the deposition direction in the as-built condition, together with corresponding microstructural characterization, revealed a threshold temperature between 600 and 625 °C, below which the steel has creep resistance comparable with Grade 91 cross-welds and noticeably greater than 9Cr-1Mo steel. The threshold temperature distinguishes the creep behavior in two regimes differentiated in creep activation energy, creep deformation, and failure mechanism. Unlike the creep rupture surface ~45° from the loading direction when tested above the threshold temperature, the creep rupture for testing below the threshold temperature resembles type IV failure in the cross-welds of ferritic steels. The DED-induced layer structure in the as-built steel played a significant role on the change of creep behavior.

36 MATERIALS SCIENCE↗

Development and Validation of a Simulation Tool to Predict the Combined Structural, Electrical, Electrochemical and Thermal Responses of Automotive Batteries

Battery safety is one of the most important design factors of electrified vehicles (EVs) since battery failure may lead to a catastrophic consequence. To improve the safety of battery systems in EVs, battery behaviors under various abuse conditions should be well understood. One way to examine battery response under extreme conditions is to conduct abuse tests in different scenarios. They can provide first-hand pass/fail information on battery safety, but they are usually expensive and time-consuming, which is inconvenient during design iterations and optimization. On the other hand, computational modeling can predict the battery behaviors in a more efficient and cost-effective way, which becomes an important tool to evaluate battery safety. Modeling battery responses and failure is challenging since it involves multiple coupled physical processes, needs to consider complex material properties and is computationally intensive. This project aims to develop a practical simulation tool to predict the combined structural, electrical, electrochemical, and thermal responses of automotive batteries to crash-induced crush and short circuit and validate it for conditions relevant to automotive crash. Advanced material constitutive models will be utilized to capture the mechanical response of cell components. Moreover, methods will be developed to reduce computational complexity of the model and allow battery safety simulations to extend from cell-level to module/pack level with affordable computational resources.

25 ENERGY STORAGE↗

Population Structure of White Sturgeon (Acipenser transmontanus) in the Columbia River Inferred from Single-Nucleotide Polymorphisms

White sturgeon (Acipenser transmontanus) are the largest freshwater fish in North America, with reproducing populations in the Sacramento-San Joaquin, Fraser, and Columbia River Basins. Of these, the Columbia River is the largest, but it is also highly fragmented by hydroelectric dams, and many segments are characterized by declining abundance and persistent recruitment failure. Efforts to conserve and supplement these fish requires an understanding of their spatial genetic structure. Here, we assembled a large set of samples from throughout the Columbia River Basin, along with representative collections from adjacent basins, and genotyped them using a panel of 325 single-nucleotide markers. Results from individual- and group-based analyses of these data indicate that white sturgeon in the uppermost Columbia River Basin, in the Kootenai and upper Snake Rivers, are the most distinct, while the remaining populations downstream in the basin can be described as a genetic gradient consistent with an isolation-by-distance effect. Notably, the population in the lowest reaches of the Columbia River is more distinct from the middle or upper reaches than from outside basins, and suggests historically a higher or more recent gene exchange through coastal routes than with populations in the interior Columbia Basin. Nonetheless, proximal reaches were generally only marginally or non-significantly divergent, suggesting that transplanting larvae or juveniles from nearby sources poses relatively little risk of outbreeding depression. Indeed, we inferred examples of dispersal between reaches via close-kin mark-recapture and genetic mark-recapture that indicate movement between nearby reaches is not unusual. Samples from the Kootenai and upper Snake Rivers exhibited notably lower genetic diversity than the remaining samples as a result of population bottlenecks, genetic drift, and/or historical divergence. Conservation actions, such as supplementation, are underway to maintain population viability and will require balanced efforts to increase demographic abundance while maintaining genetic diversity.

Willis, Stuart C.↗

Laser interference structuring of Cu for adhesive joining of HVAC equipment

Due to potential energy and cost savings benefits, adhesive joining has been recently considered for heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems. HVAC adhesive bonding requires cost-effective and adequate surface preparations of adherents. Here, this article investigates the use of abrasion, traditional single-beam laser, and a laser-interference technique as surface preparations of copper surfaces. Surface morphology is characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Effective submicrometer peak-to-valley structuring with a periodicity of ∼2.7μ⁢m was demonstrated for laser-interference processing. Single-lap shear tests were conducted for 89 joints made with bondline thicknesses of 0.15 and 0.3 mm. Data on process variables and measured variables included open-time, bond length, maximum load, displacement at failure, shear lap strength, and failure mode. A statistical analysis was conducted on each lot to determine the lower limit with 95% confidence intervals for displacements at failure and shear lap strengths. A comparison is presented between the properties of laser-structured joints with respect to those prepared by abrasion, which is considered the baseline surface preparation technique. Based on this comparison, one single-beam laser technique and two laser-interference techniques were shown to exhibit vastly superior performance over the joints made with abraded specimens.

Sabau, Adrian S. [Oak Ridge National Laboratory (O↗

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗

Integrated machine learning-molecular dynamics framework for electrolyte property prediction

Electrochemical stability windows determine the operating range of battery electrolytes, yet accurate prediction remains challenging because stability emerges from statistical ensembles of local solvation environments rather than single ground-state molecular structures. Traditional density functional theory calculations on energy-minimized clusters cannot capture the thermal variations in local coordination environments and geometries that govern decomposition, while SMILES-based machine learning methods lack explicit representation of three-dimensional solvation structure and ion pairing. Here, we introduce a structure-aware machine learning framework that predicts frontier orbital energies (HOMO and LUMO) directly from molecular dynamics-sampled solvation configurations, achieving sub-0.6 eV accuracy at computational costs 3–4 orders of magnitude lower than first-principles methods. Across twelve representative battery electrolytes, we demonstrate that solvent-separated and contact ion pairs exhibit strong size- and local chemistry dependent electronic stability, with variations in coordination shifts of HOMO or LUMO level by 2–3 eV, and that extended solvation structure and partially desolvated environment further modulate stability by up to 3 eV. By encoding the statistical nature of electrochemical failure through ensemble sampling of explicit solvation geometries, our approach enables high-throughput screening and rational design of next-generation battery electrolytes with mechanistic understanding of structure–property relationships.

Energy - Storage↗