Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Phase transformations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

Facile Oxide to Chalcogenide Conversion for Actinides Using the Boron–Chalcogen Mixture Method

Actinide chalcogenides are of interest for fundamental studies of the behavior of 5f electrons in actinides located in a soft ligand coordination environment. As actinides exhibit an extremely high affinity for oxygen, the synthesis of phase pure actinide chalcogenide materials free of oxide impurities is a great challenge and, moreover, requires the availability and use of oxygen free starting materials. Herein, we report a new method, the Boron-Chalcogen Mixture (BCM) method, for the synthesis of phase pure uranium chalcogenides based on the use of a boron/chalcogen mixture, where boron functions as an “oxygen sponge” to remove oxygen from an oxide precursor and where the elemental chalcogen effects transformation of the oxide precursor into an oxygen free chalcogenide reagent. Here, the boron oxide can be separated from the reaction mixture that is left to react to form the desired chalcogenide product. Several syntheses are presented that demonstrate the broad functionali-ty of the technique and thermodynamic calculations that show the underlying driving force are discussed. Specifically, three classes of chalcogenides that include both new (rare earth uranium sulfides and alkali-thorium thiophosphates) and previously reported compounds were prepared to validate the approach: binary uranium and thorium sulfides, oxide to sulfide transfor-mation in solid state reactions, and in situ generation of actinide chalcogenides in flux crystal growth reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cooperation in a fluid swarm of fuel-free micro-swimmers

Abstract While motile bacteria display rich dynamics in dense colonies, the phoretic nature of artificial micro-swimmers restricts their activity when crowded. Here we introduce a new class of synthetic micro-swimmers that are driven solely by light. By coupling a light absorbing particle to a fluid droplet we produce a colloidal chimera that transforms optical power into propulsive thermo-capillary action. The swimmers’ internal drive allows them to operate for a long duration (days) and remain active when crowded, forming a high density fluid phase. We find that above a critical concentration, swimmers form a long lived crowded state that displays internal dynamics. When passive particles are introduced, the dense swimmer phase can re-arrange to spontaneously corral the passive particles. We derive a geometrical, depletion-like condition for corralling by identifying the role the passive particles play in controlling the effective concentration of the micro-swimmers.

59 BASIC BIOLOGICAL SCIENCES↗

Directing the adsorption and assembly of laponite nano-discs at oil–water interfaces

Achieving tunable controls on the adsorption and self-assembly of nanoscale building blocks at immiscible fluid interfaces is essential for synthesizing advanced materials, stabilizing emulsions, and the sustainable storage and recovery of fluids. Although extensive efforts have been directed toward resolving the assembly of spherical nanoparticles at water–hydrocarbon interfaces, 2D nanoparticles have received far less attention. In this study, we developed novel controls to direct the adsorption and assembly of 2D laponite nano-discs (diameter = ∼30 nm and thickness = ∼1 nm) at water–heptane interfaces using traces of sodium dodecyl sulfate (SDS) surfactant, demonstrated by advanced in situ small-angle X-ray scattering, atomic force microscopy, spinning drop tensiometer measurements and molecular dynamics simulations. The results show that SDS surfactant displaces the adsorbed laponite nano-discs from the interface toward the aqueous phase. The extent of this displacement increases with SDS concentration such that high SDS concentrations convert laponite-rich interfaces to SDS-rich interfaces free of laponite nano-discs. This transformation is associated with significant alterations in the rheological and nanomechanical properties of the host interface. In this context, reduction in interfacial tension and interfacial stiffness and an increase in the interfacial deformation is observed on increasing the SDS concentration from 0 to 0.1 wt%. The displacement of laponite nano-discs from the interface is driven by strong electrostatic interactions between the hydrophilic SDS group and interfacial water molecules. These studies unlock new insights into the adsorption and assembly of 2D nanoscale particles at water–hydrocarbons interfaces that are relevant for various applications related to energy and environmental science and engineering.

interfacial tension↗

Signatures of van Hove singularities in the anisotropic in-plane optical conductivity of the topological semimetal Nb 3 ⁢SiTe 6

In this work, we present a temperature-dependent infrared spectroscopy study on the layered topological semimetal Nb 3 ⁢SiTe 6 combined with density-functional theory calculations of the electronic band structure and optical conductivity. Our results reveal an anisotropic behavior of the in-plane (ac-plane) optical conductivity, with three pronounced excitations located at around 0.15, 0.28, and 0.41 eV for the polarization of the incident radiation along the c axis. These excitations are well reproduced in the theoretical spectra. Based on the ab initio results, the excitations around 0.15 and 0.28 eV are interpreted as fingerprints of van Hove singularities in the electronic band structure and compared to the findings for other topological semimetals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Power System Network Reduction for Power Hardware-in-the-Loop Simulation

This paper proposes single-port equivalent and two-port equivalent network reduction methods to respectively reduce single-port and two-port areas in a large power network. Parameters of the reduced systems are rigorously derived, which guarantees that the electrical quantities at the port(s) remain unchanged over the reduction, including voltage magnitude and phase and active and reactive power injections into the area to be reduced. The proposed techniques are applied to reduce a practical Maui grid, where the total numbers of buses, lines and transformers are respectively reduced from 212, 106 and 108 to 45, 30 and 13. Dynamic behaviors between the full model and the reduced model are compared in detail to illustrate the efficacy and accuracy of the proposed network reduction.

model reduction↗

Topology-imprinting in nonlinear metasurfaces

Flat optical components, or metasurfaces, have transformed optical imaging, data storage, information processing, and biomedical applications by providing unprecedented control over light-matter interactions. These nano-engineered structures enable compact, multidimensional manipulation of light’s amplitude, phase, polarization, and wavefront, producing scalar and vector beams with unique properties such as orbital angular momentum and knotted topologies. This flexibility has potential applications in optical communication and imaging, particularly in complex environments such as atmospheric turbulence and undersea scattering. However, designing metasurfaces for shorter wavelengths, such as visible and ultraviolet light, remains challenging due to fabrication limitations and material absorption. Here, we introduce an innovative concept called topology imprinting using judiciously designed all-dielectric nonlinear optical metasurfaces to replicate desired waveforms at fundamental and harmonic frequencies, opening promising avenues for advanced photonic applications.

42 ENGINEERING↗

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome”

Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

54 ENVIRONMENTAL SCIENCES↗

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

2020 International Conference on Smart Grids and Energy Systems (SGES)

This paper is concerned about phasor-based linear state estimation of three-phase power grids which contain non transposed lines and unsymmetrical branches. It builds upon our previous work where the linear measurement equations were decoupled into three independent sets via the symmetrical component transformation. Such a transformation may however not fully decouple the measurement equations if there are nontransposed transmission lines and unsymmetrical branches in the system. This paper addresses this limitation by deriving additive terms that compensate for the remaining coupling between sequence measurements after the application of the conventional transformation. It will be shown that general unbalanced threephase power grids can still be transformed into three decoupled subsystems and their state estimation solution can be obtained in parallel by the proposed approach.

Khalili, Ramtin↗

Network Reduction for Power Hardware-in-the-Loop (PHIL) Simulation

This paper proposes single-port equivalent and two-port equivalent network reduction methods to respectively reduce single-port and two-port areas in a large power network. Parameters of the reduced systems are rigorously derived, which guarantees that the electrical quantities at the port(s) remain unchanged over the reduction, including voltage magnitude and phase and active and reactive power injections into the area to be reduced. The proposed techniques are applied to reduce a practical Maui grid, where the total numbers of buses, lines and transformers are respectively reduced from 212, 106 and 108 to 45, 30 and 13. Dynamic behaviors between the full model and the reduced model are compared in detail to illustrate the efficacy and accuracy of the proposed network reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗

MEUMAPPS (C++ Version)

Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.

DeWitt, Stephen [Oak Ridge National Lab. (ORNL), O↗

MoS 2 Catalysts Selectively Achieve High Yield of Liquid Oxygenate from Direct Conversion of Methane via Hydroxyl Radicals

Directly converting methane (CH 4 ) into liquid oxygenates (e.g., methanol) can circumvent the cost and engineering limits of natural gas transportation and storage. However, oxygenate yields from CH 4 remain low, and sulfur present in natural gas hinders activity in most catalysts. Here, to overcome these barriers, we employ bulk molybdenum disulfide (MoS 2 ), a low-cost, robust catalyst which selectively produces large quantities of liquid oxygenates (>900 µmol/g cat ∙hr) from methane in the presence of hydroxyl (OH • ) radicals produced from dilute hydrogen peroxide (H 2 O 2 ) at 75°C. Under realistic reaction conditions, MoS 2 partially and reversibly adopts a metastable, more electrically conductive phase (1T’) that can only be observed through in situ structural probes. Herein, we elucidate that redox synergy between H 2 O 2 and MoS 2 produces active OH • radical species that selectively transform CH 4 to surface methoxy species at the gas-solid liquid interface, leading to the unitary production of liquid oxygenate at a rate competitive with more costly precious metal catalysts, without additional catalyst preparation steps.

36 MATERIALS SCIENCE↗

Transformation and twinning induced plasticity in metastable Ti-Mo alloys under high strain rate deformation

The development of metastable titanium (Ti) alloys provides an unprecedented opportunity to expand their use in plasticity and damage critical applications like protective structures. However, such applications require knowledge of quasi-static to dynamic mechanical behavior, which is currently lacking. Here we perform in-situ, ultrafast synchrotron x-ray diffraction during high strain rate (Kolsky) pressure bar testing in tension and post-mortem electron microscopy to study TRansformation Induced Plasticity (TRIP) and TWinning Induced Plasticity (TWIP) in metastable Ti-Mo alloys. Two alloys, namely Ti-12Mo and Ti-15Mo (wt.%), were selected for study having different β -phase chemical stabilities. TWIP was observed in both Ti-12Mo and Ti-15Mo by in-situ synchrotron diffraction during high strain rate testing. Post-mortem microstructural characterization also revealed the presence of TRIP in Ti-12Mo. TWIP in Ti-15Mo was found to under-perform in terms of total elongation compared to TRIP/TWIP in Ti-12Mo. Ti-12Mo exhibited an average elongation of 17% compared to only 12% for Ti-15Mo with deformation at 1000 s -1 . In conclusion, TRIP resulted in significantly finer microstructure evolution and alleviated local strain accumulations in Ti-12Mo, suggesting TRIP can be used to tune available strength/ductility combinations in metastable Ti alloys under high strain rate deformation conditions.

36 MATERIALS SCIENCE↗

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering↗

Formation of distinctive nanostructured metastable polymorphs mediated by kinetic transition pathways in germanium

High-pressure β -Sn germanium may transform into diverse metastable allotropes with distinctive nanostructures and unique physical properties via multiple pathways under decompression. However, the mechanism and transition kinetics remain poorly understood. Here, we investigate the formation of metastable phases and nanostructures in germanium via controllable transition pathways of β -Sn Ge under rapid decompression at different rates. High-resolution transmission electron microscopy reveals three distinct metastable phases with the distinctive nanostructures: an almost perfect st12 Ge crystal, nanosized bc8/r8 structures with amorphous boundaries, and amorphous Ge with nanosized clusters (0.8–2.5 nm). Fast in situ x-ray diffraction and x-ray absorption measurements indicate that these nanostructured products form in certain pressure regions via distinct kinetic pathways and are strongly correlated with nucleation rates and electronic transitions mediated by compression rate, temperature, and stress. This work provides deep insight into the controllable synthesis of metastable materials with unique crystal symmetries and nanostructures for potential applications.

36 MATERIALS SCIENCE↗

A15 Nb 3 Si: a ‘high’ T c superconductor synthesized at a pressure of one megabar and metastable at ambient conditions

A15 Nb 3 Si is, until now, the only 'high' temperature superconductor produced at high pressure (~110 GPa) that has been successfully brought back to room pressure conditions in a metastable condition. Based on the current great interest in trying to create metastable-at-room-pressure high temperature superconductors produced at high pressure, we have restudied explosively compressed A15 Nb 3 Si and its production from tetragonal Nb 3 Si. First, diamond anvil cell pressure measurements up to 88 GPa were performed on explosively compressed A15 Nb 3 Si material to trace T c as a function of pressure. T c is suppressed to ~5.2 K at 88 GPa. Then, using these T c (P) data for A15 Nb 3 Si, pressures up to 92 GPa were applied at room temperature (which increased to 120 GPa at 5 K) on tetragonal Nb 3 Si. Measurements of the resistivity gave no indication of any A15 structure production, i.e. no indications of the superconductivity characteristic of A15 Nb 3 Si. This is in contrast to the explosive compression (up to P ~ 110 GPa) of tetragonal Nb 3 Si, which produced 50%–70% A15 material, T c = 18 K at ambient pressure, in a 1981 Los Alamos National Laboratory experiment. This implies that the accompanying high temperature (1000 °C) caused by explosive compression is necessary to successfully drive the reaction kinetics of the tetragonal → A15 Nb 3 Si structural transformation. Our theoretical calculations show that A15 Nb 3 Si has an enthalpy vs the tetragonal structure that is 70 meV atom –1 smaller at 100 GPa, while at ambient pressure the tetragonal phase enthalpy is lower than that of the A15 phase by 90 meV atom –1 . Furthermore, the fact that 'annealing' the A15 explosively compressed material at room temperature for 39 years has no effect shows that slow kinetics can stabilize high pressure metastable phases at ambient conditions over long times even for large driving forces of 90 meV atom –1 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Solving quasi-free and quadratic Lindblad master equations for open fermionic and bosonic systems

The dynamics of Markovian open quantum systems are described by Lindblad master equations. For fermionic and bosonic systems that are quasi-free, i.e. with Hamiltonians that are quadratic in the ladder operators and Lindblad operators that are linear in the ladder operators, we derive the equation of motion for the covariance matrix. This determines the evolution of Gaussian initial states and the steady states, which are also Gaussian. Using ladder super-operators (a.k.a. third quantization), here we show how the Liouvillian can be transformed to a many-body Jordan normal form which also reveals the full many-body spectrum. Extending previous work by Prosen and Seligman, we treat fermionic and bosonic systems on equal footing with Majorana operators, shorten and complete some derivations, also address the odd-parity sector for fermions, give a criterion for the existence of bosonic steady states, cover non-diagonalizable Liouvillians also for bosons, and include quadratic systems. In extension of the quasi-free open systems, quadratic open systems comprise additional Hermitian Lindblad operators that are quadratic in the ladder operators. While Gaussian states may then evolve into non-Gaussian states, the Liouvillian can still be transformed to a useful block-triangular form, and the equations of motion for k-point Green’s functions form a closed hierarchy. Based on this formalism, results on criticality and dissipative phase transitions in such models are discussed in a companion paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗