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At least 1,531 records · Page 85

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

36 MATERIALS SCIENCE↗

Preliminary results addressing material qualification using combined ion irradiation and modeling data

Additively-manufactured (AM) materials have attracted increasing attention in recent years as a new method to make novel and customized components. While AM and conventionally produced materials are compositionally similar, they do possess different microstructures, necessitating assessment of materials produced via AM for their behavior in reactor environments. Some microstructures unique to AM materials, such as compositional micro-inhomogeneity and dislocation cell structures, are of particular importance since they may lead to different radiation performance. The performance of AM materials for advanced nuclear reactor applications is of interest to the Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy. The AMMT program aims to demonstrate its new accelerated development and qualification methods via laser powder bed fusion (LPBF) 316 stainless steel (SS). Focusing on material bearing both 316L and 316H specifications, we integrate ion irradiation and modeling. This year, we focus on answering foundational questions related to process variability, alloy chemistry variation, and microchemical segregation. Experimental results provide information and motivate questions to the modeling effort, which aims to develop the ability to model radiation-driven microstructural evolution in additively-manufactured 316 stainless steel under a variety of advanced reactor conditions, including different temperatures, neutron spectra, and fluxes, in a sort of "virtual experiment". We perform in-situ and ex-situ ion irradiations and microstructural characterizations to support the development of AM materials for reactor applications, develop a phase field model of radiation-induced segregation in additively manufactured material with high angle grain boundaries and dislocation cells, and investigate the effect of carbon and chromium content on point defect behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impurities in silicon solar cells

The paper investigates the effects of metallic impurities on the performance of silicon solar cells. Czochralski and polycrystalline ingots were employed with boron and phosphorus as primary dopants and with controlled additions of secondary impurities. The data obtained from over 200 crystals indicate that impurity-induced performance loss is primarily due to a reduction of the base diffusion length. Based on this observation, a model is developed which predicts cell performance as a function of secondary impurity concentrations. The model calculations are in good agreement with experimental values except for Cu, Ni, Fe, and to a lesser degree, carbon, which at higher concentrations degrade the cell by junction defect mechanisms.

Davis, J. R., Jr.↗

Oxidation characteristics of Ti-14Al-21Nb ingot alloy

Static oxidation kinetics of Ti14Al21Nb (wt pct) ingot alloy were studied in air over the temperature interval of 649 to 1093 C in a thermogravimetric apparatus. The oxidation products were characterized by x ray diffraction, electron microprobe analysis, energy dispersive x ray analysis, and Auger electron spectroscopy. Cross-sections of the oxidized samples were also examined using light and scanning electron microscopy. The oxidation rate was substantially lower than the conventional alloys of titanium, but the kinetics displayed a complex behavior involving two or more oxidation rates depending on the temperature and duration of exposure. The primary oxide formed was TiO2, but this oxide was doped with Nb. Small amounts of Al2O3 and TiN were also present in the scale. Diffusion of oxygen into the alloy was observed and the diffusivity seemed to be dependent on the microstructure of the metal. A model was presented to explain the oxidation behavior of the alloy in terms of the reduction in the oxygen diffusivity in the oxide caused by the modification of the defect structure of TiO2 by Nb ions.

Sankaran, Sankara N.↗

Why Are Buckyonions Round?

Multi-layered round carbon particles (onions) containing tens to hundreds of thousands of atoms form during electron irradiation of graphite carbon. However, theoretical models of large icosahedral fullerenes predict highly faceted shapes for molecules with more than a few hundred atoms. This discrepancy in shape may be explained by the presence of defects during the formation of carbon onions. Here, we use the semi-empirical tight-binding method for carbon to simulate the incorporation of pentagon-heptagon defects on to the surface of large icosahedral fullerenes. We show a simple mechanism that results in energetically competitive derivative structures and a global change in molecular shape from faceted to round. Our results provide a plausible explanation of the apparent discrepancy between experimental observations of round buckyonions and theoretical predictions of faceted icosahedral fullerenes.

Bates, Kevin R.↗

Why are Buckyonions Round?

Multi-layered round carbon particles (onions) containing tens to hundreds of thousands of atoms form during electron irradiation of graphite. However. theoretical models or large icosahedral fullerenes predict highly faceted shapes for molecules with more than a few hundred atoms. This discrepancy in shape may be explained by the presence of defects during the formation of carbon onions. Here, we use the semi-empirical tight-binding method for carbon to simulate the incorporation of pentagon-heptagon defects on to the surface of large icosahedral fullerenes. We show a simple mechanism that results in energetically competitive derivative structures and a global change in molecular shape from faceted to round. Our results provide a plausible explanation of the apparent discrepancy between experimental observations or round buckyonions and theoretical predictions of faceted icosahedral fullerenes.

Bates, Kevin R.↗

Interpretation of Zerodur® Strength Data

Recent, detailed fractographic analysis of Zerodur® strength test specimens prepared by linear grinding and etching with a proprietary process indicated low frequency damage to be the strength limiting defects Recent, detailed fractographic analysis of Zerodur® strength test specimens prepared by linear grinding and etching with a proprietary process indicated low frequency damage to be the strength limiting defects [1]. The 2-parameter Weibull distribution is usually assumed when working with ceramic and glasses such as Zerodur®, although 3-parameter behavior is occasionally considered [2]. Detailed statistical modeling of the Zerodur® strength data with the was initial perspective of a 3-parameter Weibull distribution gave unsatisfying results [3]. The subsequent fractographic investigation indicated [1] that the usual assumption of many small, random, noninteracting flaws [4] was not represented, but instead, less frequent, aligned flaws along etching ridges parallel to the grinding direction were present, Figure 1. It was thus concluded that the strength of Zerodur® as prepared was not Weibull distributed. The flaws represent a sparse flaw population relative to typical grinding damage, but an extensive occurrence (high frequency) of handling damage. We examine the type of distribution present and explain the appearance of a 3-parameter distribution.

Glass, ceramic, strength, Weibull, distribution, m↗

MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS

This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗

Interplay of electronic structure, magnetism, strain, and defects in carbide $\mathrm{MX}$enes

We report the two-dimensional (2D) magnetic and semiconducting materials, including carbide MXenes, are in high demand for magneto-electronic devices and applications. Here, we report a first-principles study of electronic structure and magnetism of a Ti 2 C MXene, its derivatives Ti 2 CT 2 (T = -F, -O, -OH, -H), and the effect of single vacancy defects (25% C, 12.5% O, and 12.5% and 5.5% Ti) and transition metal (V, Cr, Mn, and Co) dopings. The MAX phase Ti 2 AlC is a non-magnetic (NM) metal which upon removal of Al layer forms a pristine Ti 2 C MXene with A-type antiferromagnetic (AFM) semiconductor having reliable transition temperature (T N = 41K) predicted by the Heisenberg model. All the functionalized MXenes are stable as NM metal except for Ti 2 CO 2 which remains semiconducting with NM ground state. The significant effect of spin–orbit coupling (SOC) is evident in the band structure forming Dirac-like cones and band inversions near the Fermi level. Depending upon the type of vacancy defects Ti 2 CO 2 is NM metal and ferromagnetic (FM) metal. The transition metal (TM) doped MXenes fulfill FM Stoner criterion. The V- and Co-doped MXenes are metals, whereas Cr- and Mn-doped are half-metal and semiconductor.

2D magnetism↗

Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [1]. We focus here on test cases of physical interest where the dynamics of the system is modelled by the Langevin equation and is simulated using the molecular dynamics software LAMMPS. In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. We consider a self-interstitial atom in a tungsten lattice and compute the average residence time of the system in metastable states. Our numerical results demonstrate significant computational gains using the adaptive parareal algorithm in comparison to a sequential integration of the Langevin dynamics. We also identify a large regime of numerical parameters for which statistical accuracy is reached without being a consequence of trajectorial accuracy.

36 MATERIALS SCIENCE↗

Strain-Induced asymmetry and on-site dynamics of silicon defects in graphene

In the last decade, the atomically-focused electron beams utilized in scanning transmission electron microscopes (STEMs) have been shown to induce a broad set of local structural transformations in materials, opening pathways for directing material synthesis and modification atom-by-atom. The mechanisms underlying these transformations remain largely unknown, due to the intractability of modeling the myriad of reaction pathways that can be accessed through high-energy electron scattering. The information on materials’ structure and dynamics that can be extracted from STEM images is similarly left underexplored. Here, we report the observation of anomalous on-site dynamics of individual silicon impurity atoms in graphene during STEM imaging. Density functional theory-based structural optimizations of anisotropically-strained molecular nanographenes reveal two distinct (but nearly degenerate) stable structures for four-fold coordinated silicon impurities, where interconversion between the two structures manifests slight changes of the silicon position within the lattice site. Implications for defect-based strain engineering in graphene are discussed.

36 MATERIALS SCIENCE↗

Solidification of II-VI Compounds in a Rotating Magnetic Field

This project is aimed at using a rotating magnetic field (RMF) to control fluid flow and transport during directional solidification of elemental and compound melts. Microgravity experiments have demonstrated that small amounts of residual acceleration of less than a micro-g can initiate and prolong fluid flow, particularly when there is a static component of the field perpendicular to the liquid solid interface. Thus a true diffusion boundary layer is not formed, and it becomes difficult to verify theories of solidification or to achieve diffusion controlled solidification. The RMF superimposes a stirring effect on an electrically conducting liquid, and with appropriate field strengths and frequencies, controlled transport of material through a liquid column can be obtained. As diffusion conditions are precluded and complete mixing conditions prevail, the technique is appropriate for traveling solvent zone or float zone growth methods in which the overall composition of the liquid can be maintained throughout the growth experiment. Crystals grown by RMF techniques in microgravity in previous, unrelated missions have shown exceptional properties. The objective of the project is two-fold, namely (1) using numerical modeling to simulate the behavior of a solvent zone with applied thermal boundary conditions and demonstrate the effects of decreasing gravity levels, or an increasing applied RMF, or both, and (2) to grow elements and II-VI compounds from traveling solvent zones both with and without applied RMFs, and to determine objectively how well the modeling predicts solidification parameters. Numerical modeling has demonstrated that, in the growth of CdTe from a tellurium solution, a rotating magnetic field can advantageously modify the shape of the liquid solid interface such that the interface is convex as seen from the liquid. Under such circumstances, the defect structure is reduced as any defects which are formed tend to grow out and not propagate. The flow of liquid, however, is complex due to the competing flow induced by the rotating magnetic field and the buoyancy driven convection. When the acceleration forces are reduced to one thousandth of gravity, the flow pattern is much simplified and well controlled material transport through the solvent zone can be readily achieved. Triple axis diffractometry and x-ray synchrotron topography have demonstrated that there is no significant improvement in crystal quality for HgCdTe grown on earth from a tellurium solution when a rotating magnetic field is applied. However, modeling shows that the flow in microgravity with a rotating magnetic field would produce a superior product.

Gillies, D. C.↗

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗

Flux Pinning Mechanism in BaSnO{sub 3}-Added GdBa{sub 2}Cu{sub 3}O{sub 7-x} Films with Different Thickness

Types of flux pinning mechanism in pure and BaSnO{sub 3} (BSO)-added GdBa{sub 2}Cu{sub 3}O{sub 7-x} (GdBCO) superconducting films have been determined by using the Dew-Hughes model. We have found that as the BSO content increases up to 4 wt%, dominant pinning mechanism of GdBCO films has changed from normal surface pinning due to intrinsic linear defects to normal point pinning by BSO addition. Careful analysis on the scaling of the flux pinning for the 4 wt% BSO-doped GdBCO films with various film thicknesses revealed that the pinning mechanism came from the hybrid pinning of two kinds of pinning types. In addition to the normal point pinning by BSO addition, another type of Δκ-pinning was observed to be prominent in the thinner films in low magnetic field region as normal point pinning was deteriorated. Through the EXAFS analysis, it was found that the Δκ-pinning is possibly originated from the oxygen deficiency in localized position. These results suggested that film thickness directly affects the flux pinning mechanism of the BSO-doped GdBCO films, and in the application point of view, an optimization of the film thickness may be crucial to operate normal point pinning induced by BSO addition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗

Pushing the limits of size selectivity in nanoscale solute separations

Transport of a spherical solute through a cylindrical pore has been modelled for decades using well-established hindered transport theory, predicting solutes with a size smaller than the pore to be rejected nonetheless because of convective and diffusive hindrance; this rejection mechanism prevents extremely sharp solute separations by a membrane. Whereas the model has been historically verified, solute transport through near-perfect isoporous membranes may finally overcome this limitation. Here, in this study, encouraging solute rejections are achieved using nanofabricated, defect-free silicon nitride isoporous membranes. The membrane is challenged by a recirculated feed to increase the opportunity for interactions between solutes and the pore array. Results show the membrane completely reject solutes with greater size than the pore size while effectively allowing smaller solutes to permeate through. With effectively increasing the number of interactions, we propose that a steeper size-selective rejection curve may be achieved. With this traditional hurdle overcome, there is new promise for unprecedented membrane separations through judicious process design and extremely tight pore-size distributions.

Gao, Feng↗

Data-driven design of novel halide perovskite alloys

The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. Here, in this work, we develop a framework powered by high-throughput computations and machine learning for the design and prediction of mixed cation halide perovskite alloys. In a chemical space of ABX 3 perovskites with a selected set of options for A, B, and X species, pseudo-cubic structures with B-site mixing are simulated using density functional theory (DFT) and several properties are computed, including stability, lattice constant, band gap, vacancy formation energy, refractive index, and optical absorption spectrum, using both semi-local and hybrid functionals. Neural networks (NN) are used to train predictive models for every property using tabulated elemental properties of A, B, and X site species as descriptors. Starting from a DFT dataset of 229 points, we use the trained NN models to predict the structural, energetic, electronic, and optical properties of an extensive dataset of 17955 compounds, and perform high-throughput screening in terms of stability, band gap, and defect tolerance, to obtain 392 promising compounds that are ranked as potential absorbers according to their photovoltaic figure of merit. Compositional trends in the screened set of attractive mixed cation halide perovskites are revealed and additional computations are performed on selected compounds. The data-driven design framework developed here is promising for designing novel mixed compositions and can be extended to a wider perovskite chemical space in terms of A, B, and X species, different kinds of mixing at the A, B, or X sites, non-cubic phases, and other properties of interest.

36 MATERIALS SCIENCE↗