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At least 1,135 records · Page 63

Surface science of shape-selective metal nanocrystal synthesis from first-principles: Growth of Cu nanowires and nanocubes

The authors present results from first-principles density functional theory aimed at understanding the aqueous solution-phase growth of fivefold twinned copper nanowires and single-crystal nanocubes capped by hexadecylamine (HDA). The role of solution-phase chloride, present in the Cu salt or as an additive, is emphasized. Using ab initio thermodynamics, the authors delineate the range of solution-phase conditions, characterized by the chemical potentials of chloride and HDA, under which Cu nanowires and nanocubes can be grown. The authors discuss the likelihood of thermodynamic and/or kinetic nanostructures for various solution-phase concentrations. Their results are in good agreement with experiments and indicate that methods and insights developed for surface science in gas-phase or vacuum conditions can yield much insight into liquid-phase systems.

36 MATERIALS SCIENCE↗

Future of plasma etching for microelectronics: Challenges and opportunities

Plasma etching is an essential semiconductor manufacturing technology required to enable the current microelectronics industry. Along with lithographic patterning, thin-film formation methods, and others, plasma etching has dynamically evolved to meet the exponentially growing demands of the microelectronics industry that enables modern society. At this time, plasma etching faces a period of unprecedented changes owing to numerous factors, including aggressive transition to three-dimensional (3D) device architectures, process precision approaching atomic-scale critical dimensions, introduction of new materials, fundamental silicon device limits, and parallel evolution of post-CMOS approaches. The vast growth of the microelectronics industry has emphasized its role in addressing major societal challenges, including questions on the sustainability of the associated energy use, semiconductor manufacturing related emissions of greenhouse gases, and others. The goal of this article is to help both define the challenges for plasma etching and point out effective plasma etching technology options that may play essential roles in defining microelectronics manufacturing in the future. The challenges are accompanied by significant new opportunities, including integrating experiments with various computational approaches such as machine learning/artificial intelligence and progress in computational approaches, including the realization of digital twins of physical etch chambers through hybrid/coupled models. These prospects can enable innovative solutions to problems that were not available during the past 50 years of plasma etch development in the microelectronics industry. To elaborate on these perspectives, the present article brings together the views of various experts on the different topics that will shape plasma etching for microelectronics manufacturing of the future.

Engineering↗

A characterization of quantum Kerr optical frequency combs

Quantum Kerr optical frequency combs are generated by pumping a high-Q microresonator with a continuous wave resonant laser. Below threshold, two pump photons are symmetrically up- and down-converted as twin photons via spontaneous four-wave mixing, thereby generating up to a hundred paired channels. Furthermore, these chipscale, high-dimensional and room-temperature systems are expected to play a major role in quantum engineering. However, their theoretical description is still unclear. Here, we present an explicit description of this quantum system via a frequency-bin state and its density operator, and explore the properties of the eigenkets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Soft crystal martensites: An in situ resonant soft x-ray scattering study of a liquid crystal martensitic transformation

Liquid crystal blue phases (BPs) are three-dimensional soft crystals with unit cell sizes orders of magnitude larger than those of classic, atomic crystals. The directed self-assembly of BPs on chemically patterned surfaces uniquely enables detailed in situ resonant soft x-ray scattering measurements of martensitic phase transformations in these systems. The formation of twin lamellae is explicitly identified during the BPII-to-BPI transformation, further corroborating the martensitic nature of this transformation and broadening the analogy between soft and atomic crystal diffusionless phase transformations to include their strain-release mechanisms.

36 MATERIALS SCIENCE↗

Mechanistic basis of oxygen sensitivity in titanium

One of the most potent examples of interstitial solute strengthening in metal alloys is the extreme sensitivity of titanium to small amounts of oxygen. Unfortunately, these small amounts of oxygen also lead to a markedly decreased ductility, which in turn drives the increased cost to purify titanium to avoid this oxygen poisoning effect. Here, we report a systematic study on the oxygen sensitivity of titanium that provides a clear mechanistic view of how oxygen impurities affect the mechanical properties of titanium. The increased slip planarity of Ti-O alloys is caused by an interstitial shuffling mechanism, which is sensitive to temperature, strain rate, and oxygen content and leads to the subsequent alteration of deformation twinning behavior. The insights from our experimental and computational work provide a rationale for the design of titanium alloys with increased tolerance to variations in interstitial content, with notable implications for more widespread use of titanium alloys.

36 MATERIALS SCIENCE↗

Design metastability in high-entropy alloys by tailoring unstable fault energies

Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

36 MATERIALS SCIENCE↗

Discovery of spontaneous mesoscopic strain waves in nematic domains using dark-field x-ray microscopy

Electronic nematic order arises when correlated electrons spontaneously break the rotational symmetry of a crystal lattice. When electronic nematic order couples bilinearly to symmetry-breaking lattice strain, both appear together at a single ferroelastic phase transition, producing structural twin domains with distinct orientations of the nematic director. While the effects of applied strain on these domains are well established, the intrinsic behavior of spontaneous subdomain strain fields has remained unexplored. Here, we report the discovery of spontaneous mesoscopic strain waves within individual nematic domains of an iron-based superconductor, observed using dark-field x-ray microscopy (DFXM). Using this advanced full-field imaging technique, we visualize subdomain strain modulations emerging concurrently with nematic order. Elastic compatibility relations governing inhomogeneous strains provide a natural mechanism for the strain waves. Our findings reveal a broadly relevant form of strain self-organization and position DFXM as a powerful probe of the local interplay between lattice strain and electronic order.

36 MATERIALS SCIENCE↗

Steam-created grain boundaries for methane C–H activation in palladium catalysts

Defects may display high reactivity because the specific arrangement of atoms differs from crystalline surfaces. We demonstrate that high-temperature steam pretreatment of palladium catalysts provides a 12-fold increase in the mass-specific reaction rate for carbon-hydrogen (C–H) activation in methane oxidation compared with conventional pretreatments. Through a combination of experimental and theoretical methods, we demonstrate that an increase in the grain boundary density through crystal twinning is achieved during the steam pretreatment and oxidation and is responsible for the increased reactivity. The grain boundaries are highly stable during reaction and show specific rates at least two orders of magnitude higher than other sites on the palladium on alumina (Pd/Al 2 O 3 ) catalysts. Theoretical calculations show that strain introduced by the defective structure can enhance C–H bond activation. Introduction of grain boundaries through laser ablation led to further rate increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gradient cell–structured high-entropy alloy with exceptional strength and ductility

We report that similar to conventional materials, most multicomponent high-entropy alloys (HEAs) lose ductility as they gain strength. In this study, we controllably introduced gradient nanoscaled dislocation cell structures in a stable single-phase HEA with face-centered cubic structure, thus resulting in enhanced strength without apparent loss of ductility. Upon application of strain, the sample-level structural gradient induces progressive formation of a high density of tiny stacking faults (SFs) and twins, nucleating from abundant low-angle dislocation cells. Furthermore, the SF-induced plasticity and the resultant refined structures, coupled with intensively accumulated dislocations, contribute to plasticity, increased strength, and work hardening. These findings offer a promising paradigm for tailoring properties with gradient dislocation cells at the nanoscale and advance our fundamental understanding of the intrinsic deformation behavior of HEAs.

36 MATERIALS SCIENCE↗

Exceptional fracture toughness of CrCoNi-based medium- and high-entropy alloys at 20 kelvin

Medium- and high-entropy alloys based on the CrCoNi-system have been shown to display outstanding strength, tensile ductility and fracture toughness (damage-tolerance properties), especially at cryogenic temperatures. Here we examine the J Ic and (back-calculated) K JIc fracture toughness values of the face-centered cubic, equiatomic CrCoNi and CrMnFeCoNi alloys at 20 K. At flow stress values of ~1.5 GPa, crack-initiation K JIc toughnesses were found to be exceptionally high, respectively 235 and 415 MPa√m for CrMnFeCoNi and CrCoNi, with the latter displaying a crack-growth toughness K ss exceeding 540 MPa√m after 2.25 mm of stable cracking, which to our knowledge is the highest such value ever reported. Characterization of the crack-tip regions in CrCoNi by scanning electron and transmission electron microscopy reveal deformation structures at 20 K that are quite distinct from those at higher temperatures and involve heterogeneous nucleation, but restricted growth, of stacking faults and fine nanotwins, together with transformation to the hexagonal closed-packed phase. The coherent interfaces of these features can promote both the arrest and transmission of dislocations to generate respectively strength and ductility which strongly contributes to sustained strain hardening. Indeed, we believe that these nominally single-phase, concentrated solid-solution alloys develop their fracture resistance through a progressive synergy of deformation mechanisms, including dislocation glide, stacking-fault formation, nano-twinning and eventually in situ phase transformation, all of which serve to extend continuous strain hardening which simultaneously elevates strength and ductility (by delaying plastic instability), leading to truly exceptional resistance to fracture.

36 MATERIALS SCIENCE↗

Design of a Robust Memristive Spiking Neuromorphic System with Unsupervised Learning in Hardware

Spiking neural networks (SNN) offer a power efficient, biologically plausible learning paradigm by encoding information into spikes. The discovery of the memristor has accelerated the progress of spiking neuromorphic systems, as the intrinsic plasticity of the device makes it an ideal candidate to mimic a biological synapse. Despite providing a nanoscale form factor, non-volatility, and low-power operation, memristors suffer from device-level non-idealities, which impact system-level performance. To address these issues, this article presents a memristive crossbar-based neuromorphic system using unsupervised learning with twin-memristor synapses, fully digital pulse width modulated spike-timing-dependent plasticity, and homeostasis neurons. Additionally, the implemented single-layer SNN was applied to a pattern-recognition task of classifying handwritten-digits. The performance of the system was analyzed by varying design parameters such as number of training epochs, neurons, and capacitors. Furthermore, the impact of memristor device non-idealities, such as device-switching mismatch, aging, failure, and process variations, were investigated and the resilience of the proposed system was demonstrated.

97 MATHEMATICS AND COMPUTING↗

Optimization Of Real-time Capacity Allocation

ORCA is a modeling toolset to accelerate real-time control and optimization of digital twins, including virtual models of facilities, physical facilities, and interconnections to allow optimal control of physical facilities using virtual models. ORCA is enabled by INL's RAVEN and DeepLynx software codes.

Talbot, Paul [Idaho National Laboratory] (00000002↗

Mobiliti v1.0

Mobiliti is a software platform designed to emulate the dynamics of a regional transportation road network. It is built on open-source software that provides parallel discrete-event simulation. The software is transformative in the area of transportation network simulation because of the geospatial scale and fidelity of the network model and the computational time it takes to model a full day of travel demand. For example, it runs a simulation of the entire San Francisco Bay Area, with a network model of ~1M links and a population that completes ~19M trips in ~5 minutes. This scale of simulation has not been attempted with existing simulation models due to the complexity of the model and the computational time it would take to complete. The intent of the software is to create a digital twin capability for cities to evaluate consequences of infrastructure or policy changes on road network dynamics.

Macfarlane, Jane↗

Automatic Building Energy Modeling (AutoBEM)

AutoBEM provides automated building energy modeling for quantifying energy, demand, emissions, and cost reductions for over 1 million buildings per hour. It creates a digital twin energy model of a building from a set of descriptors. Benefits include: Scale - has been used to simulate every building in the U.S. Speed - fastest creation and simulation of energy models for buildings. Accuracy - validated against 15-minute data for 178,000 buildings as well as multiple cities.

New, JoshuaR↗

ExaDigiT/RAPS

ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.

Brewer, Wesley [Oak Ridge National Laboratory (ORN↗

datacenterCoolingModel

ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library and the open-source autocsm library. The library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.

Kumar, Vineet [Oak Ridge National Laboratory (ORNL↗

AutoCSM

A template system-of-systems modeling approach for automating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework. AutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).

Greenwood, MichaelScott [Oak Ridge National Labora↗