Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Complex quantum materials”

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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A galactic approach to neutron scattering science

Neutron scattering science is leading to significant advances in our understanding of materials and will be key to solving many of the challenges that society is facing today. Improvements in scientific instruments are actually making it more difficult to analyze and interpret the results of experiments due to the vast increases in the volume and complexity of data being produced and the associated computational requirements for processing that data. New approaches to enable scientists to leverage computational resources are required, and Oak Ridge National Laboratory (ORNL) has been at the forefront of developing these technologies. We recently completed the design and initial implementation of a neutrons data interpretation platform that allows seamless access to the computational resources provided by ORNL. For the first time, we have demonstrated that this platform can be used for advanced data analysis of correlated quantum materials by utilizing the world's most powerful computer system, Frontier. In particular, we have shown the end-to-end execution of the DCA++ code to determine the dynamic magnetic spin susceptibility χ(q, ω) for a single-band Hubbard model with Coulomb repulsion U/t = 8 in units of the nearest-neighbor hopping amplitude t and an electron density of n = 0.65. The following work describes the architecture, design, and implementation of the platform and how we constructed a correlated quantum materials analysis workflow to demonstrate the viability of this system to produce scientific results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Magnetic field driven emergent phenomena: Insights from magneto-optics and nanoscopy

This review explores magnetic field-driven emergent phenomena across various material systems, emphasizing the pivotal roles of magneto-optical and nanoscopy techniques. We examine fundamental aspects of Landau electrodynamics in both 2D and 3D systems, including quantum Hall and topological magnetoelectric effects in graphene and topological insulators. Particularly attention is given to magnetic excitations and magnetopolaritons, such as surface magnon polaritons, magnetoplasmons, and magnetoexcitons in novel quantum materials, including quantum magnets and hybrid heterostructures. Advanced imaging techniques, such as scattering-type scanning near-field optical microscopy (SNOM) and microwave impedance microscopy, are showcased for their capability to resolve these phenomena with microscopic and nanoscopic resolution. These insights are complemented by discussions of advanced experimental approaches, including cryogenic environments, ultrafast pump-probe techniques, and the integration of magnetic fields into near-field optical methodologies. We further investigate the potential of these imaging techniques for unraveling complex magnetic orders, quantum phases, and correlated electronic behaviors. Finally, we offer perspectives on future research directions and highlight emerging opportunities in the evolving field of optical magneto-nanoscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Scientific Case for Concurrent Neutron and X-ray Scattering and Spectroscopy

The interrogation of materials with X-rays or neutrons to determine the structure, energetics, and dynamics of materials is fundamental to advancing materials' physical and chemical science and developing innovative material technologies. A transcending challenge in developing novel materials is that progress hinges on understanding the structure and dynamics across multiple time and length scales in complex materials that feature multiple components, interfaces, and compositions. Despite the ever-growing demands on materials’ characterization, existing approaches are almost exclusively based on isolated X-ray or neutron scattering, i.e., an approach commensurate with the more narrowly defined needs of fifty years ago. A three-day workshop sponsored by the U.S. National Science Foundation (NSF) analyzed the demand for concurrent neutron and X-ray (NeX) experiments. It was held at the Spring Hill Suites, San Jose, California, from June 2 to 4, 2022. In this workshop, 70 national and international experts ascertained the crucial need to establish NeX capabilities to advance the science of complex materials and systems in the US. Here, we illustrate the need for NeX scattering and spectroscopy experiments by showcasing examples that span areas as diverse as biomaterials, energy science, soft matter, and nanomaterials. To provide NeX capability will require new instrumentation that enables concurrent experiments. Affected areas include chemistry, soft matter, quantum materials, pure and applied chemistry, bioscience, geoscience, and applied materials. NeX benefits research outcomes due to the complementarity of the two techniques, which is essential for better model refinement. While joint refinement of data from separate neutron and X-ray experiments is critical to avoid ambiguities, especially in multiphase-multicomponent materials, concurrent experiments overcome scientific and technical barriers associated with single measurements, separated by location and, thus, time. Among all the examples, these factors introduce uncertainties in the results that complicate data analysis. [1,2] [3] While models are strongly sample-dependent, the principles of joint refinement are generally applicable to these disciplines, including the development of advanced parameterization, modeling, and analysis techniques that also consider the temporal and spatial resolutions of the two methods, leading to unambiguous data interpretation. Solutions for technical barriers must be found to realize NeX experiments, including developing robust sample environments that meet the optical requirements of neutrons and X-rays.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Low energy electrodynamics of CrI 3 layered ferromagnet

We report on the optical properties from terahertz (THz) to Near-Infrared (NIR) of the layered magnetic compound CrI 3 at various temperatures, both in the paramagnetic and ferromagnetic phase. In the NIR spectral range, we observe an insulating electronic gap around 1.1 eV which strongly hardens with decreasing temperature. The blue shift observed represents a record in insulating materials and it is a fingerprint of a strong electron-phonon interaction. Moreover, a further gap hardening is observed below the Curie temperature, indicating the establishment of an effective interaction between electrons and magnetic degrees of freedom in the ferromagnetic phase. Similar interactions are confirmed by the disappearance of some phonon modes in the same phase, as expected from a spin-lattice interaction theory. Therefore, the optical properties of CrI 3 reveal a complex interaction among electronic, phononic and magnetic degrees of freedom, opening many possibilities for its use in 2-Dimensional heterostructures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Recent developments in the PySCF program package

PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. Here, we explain the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.

42 ENGINEERING↗
DOE OSTI2021

The multi-faceted inverted harmonic oscillator: Chaos and complexity

The harmonic oscillator is the paragon of physical models; conceptually and computationally simple, yet rich enough to teach us about physics on scales that span classical mechanics to quantum field theory. This multifaceted nature extends also to its inverted counterpart, in which the oscillator frequency is analytically continued to pure imaginary values. In this article we probe the inverted harmonic oscillator (IHO) with recently developed quantum chaos diagnostics such as the out-of-time-order correlator (OTOC) and the circuit complexity. In particular, we study the OTOC for the displacement operator of the IHO with and without a non-Gaussian cubic perturbation to explore genuine and quasi scrambling respectively. In addition, we compute the full quantum Lyapunov spectrum for the inverted oscillator, finding a paired structure among the Lyapunov exponents. We also use the Heisenberg group to compute the complexity for the time evolved displacement operator, which displays chaotic behaviour. Finally, we extended our analysis to N-inverted harmonic oscillators to study the behaviour of complexity at the different timescales encoded in dissipation, scrambling and asymptotic regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗
DOE OSTI2026

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗
DOE OSTI2022

A 9.2-GHz clock transition in a Lu(II) molecular spin qubit arising from a 3,467-MHz hyperfine interaction

Spins in molecules are particularly attractive targets for next-generation quantum technologies, enabling chemically programmable qubits and potential for scale-up via self-assembly. Here, we report observation of one of the largest hyperfine interactions for a molecular system, A iso = 3467±50 MHz, along with an associated clock transition of unprecedented magnitude. This is achieved through chemical control of the degree of s-orbital mixing into the spin-bearing d-orbital associated with a series of spin-½ La(II) and Lu(II) complexes. Increased s-orbital character reduces spin-orbit coupling and enhances the electron-nuclear Fermi contact interaction. Both outcomes are advantageous for quantum applications: the former reduces spin-lattice relaxation, while the latter maximizes the hyperfine interaction that, in turn, generates a 9 gigahertz clock transition, leading to an increase in phase memory time from 1.0±0.4 to 12±1 microseconds for one of the Lu(II) complexes. Furthermore, these findings suggest strategies for development of molecular quantum technologies, akin to trapped ion systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Porosity modeling in a TiNbTaZrMo high-entropy alloy for biomedical applications

High-entropy alloys (HEAs) have attracted great attention for many biomedical applications. However, the nature of interatomic interactions in this class of complex multicomponent alloys is not fully understood. We report, for the first time, the results of theoretical modeling for porosity in a large biocompatible HEA TiNbTaZrMo using an atomistic supercell of 1024 atoms that provides new insights and understanding. Our results demonstrated the deficiency of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with available experimental data to reduce Young's modulus. We utilized the novel concepts of the total bond order density (TBOD) and partial bond order density (PBOD) via ab initio quantum mechanical calculations as an effective theoretical means to chart a road map for the rational design of complex multicomponent HEAs for biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Helical Edge States and Quantum Phase Transitions in Tetralayer Graphene

Helical conductors with spin-momentum locking are promising platforms for Majorana fermions. Here we report observation of two topologically distinct phases supporting helical edge states in charge neutral Bernal-stacked tetralayer graphene in Hall bar and Corbino geometries. As the magnetic field B ⊥ and out-of-plane displacement field D are varied, we observe a phase diagram consisting of an insulating phase and two metallic phases, with 0, 1, and 2 helical edge states, respectively. These phases are accounted for by a theoretical model that relates their conductance to spin-polarization plateaus. Transitions between them arise from a competition among interlayer hopping, electrostatic and exchange interaction energies. Finally, our work highlights the complex competing symmetries and the rich quantum phases in few-layer graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling the Effect of Film Morphology on the Performance of an OLED Device

Organic Light Emitting Diode (OLED) technology is replacing the liquid crystal displays (LCD) in cell phones and is also expected to impact television displays in the future. Dow has an active OLED research program. To complement and ultimately drive this effort, it is necessary to develop efficient computational screening tools for selection and optimization of target molecules. To this end we sought to identify and expand on existing models used by Dow that can better predict the mobility of electrons and holes in organic materials. We focused on N,N'- bis(1-naphthyl)-N,N'-diphenyl-1,1'-biphenyl-4,4'-diamine (NPD), frequently used in academic studies of organic light-emitting diodes; we also studied 4,4'-Bis(N-carbazolyl)-1,1'-biphenyl (CBP), tris(4-carbazoyl-9-ylphenyl)amine (TCTA), and bathophenanthroline (BPhen). We developed a workflow, using a combination of molecular dynamics and quantum chemistry calculations, to predict trends in the electronic structure that correlate with measured electron and hole mobilities of small molecule materials such as NPD for OLEDs, comparing with measurements in the literature and at Dow. This work comprised a first step toward predictive charge carrier mobilities in small-molecule electronic materials with complex morphologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Stability and molecular pathways to the formation of spin defects in silicon carbide

Abstract Spin defects in wide-bandgap semiconductors provide a promising platform to create qubits for quantum technologies. Their synthesis, however, presents considerable challenges, and the mechanisms responsible for their generation or annihilation are poorly understood. Here, we elucidate spin defect formation processes in a binary crystal for a key qubit candidate—the divacancy complex (VV) in silicon carbide (SiC). Using atomistic models, enhanced sampling simulations, and density functional theory calculations, we find that VV formation is a thermally activated process that competes with the conversion of silicon (V Si ) to carbon monovacancies (V C ), and that VV reorientation can occur without dissociation. We also find that increasing the concentration of V Si relative to V C favors the formation of divacancies. Moreover, we identify pathways to create spin defects consisting of antisite-double vacancy complexes and determine their electronic properties. The detailed view of the mechanisms that underpin the formation and dynamics of spin defects presented here may facilitate the realization of qubits in an industrially relevant material.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Atomic-scale 3D imaging of individual dopant atoms in an oxide semiconductor

The physical properties of semiconductors are controlled by chemical doping. In oxide semiconductors, small variations in the density of dopant atoms can completely change the local electric and magnetic responses caused by their strongly correlated electrons. In lightly doped systems, however, such variations are difficult to determine as quantitative 3D imaging of individual dopant atoms is a major challenge. We apply atom probe tomography to resolve the atomic sites that donors occupy in the small band gap semiconductor Er(Mn,Ti)O 3 with a nominal Ti concentration of 0.04 at. %, map their 3D lattice positions, and quantify spatial variations. Our work enables atomic-level 3D studies of structure-property relations in lightly doped complex oxides, which is crucial to understand and control emergent dopant-driven quantum phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrically driven amplified spontaneous emission from colloidal quantum dots

Colloidal quantum dots (QDs) are attractive materials for realizing solution-processable laser diodes that could benefit from size-controlled emission wavelengths, low optical-gain thresholds and ease of integration with photonic and electronic circuits. However, the implementation of such devices has been hampered by fast Auger recombination of gain-active multicarrier states, poor stability of QD films at high current densities and the difficulty to obtain net optical gain in a complex device stack wherein a thin electroluminescent QD layer is combined with optically lossy charge-conducting layers. Here we resolve these challenges and achieve amplified spontaneous emission (ASE) from electrically pumped colloidal QDs. The developed devices use compact, continuously graded QDs with suppressed Auger recombination incorporated into a pulsed, high-current-density charge-injection structure supplemented by a low-loss photonic waveguide. These colloidal QD ASE diodes exhibit strong, broadband optical gain and demonstrate bright edge emission with instantaneous power of up to 170 μW.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic Resolution Cryogenic 4D-STEM Imaging via Robust Distortion Correction

Cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) imaging is a useful technique for studying quantum materials and their interfaces by simultaneously probing charge, lattice, spin, and chemistry on the atomic scale with the sample held at temperatures ranging from room to cryogenic. However, its applications are currently limited by the instabilities of cryo-stages and electronics. To overcome this challenge, we develop an algorithm to effectively correct the complex distortions present in atomic resolution cryogenic 4D-STEM data sets. This method uses nonrigid registration to identify localized distortions in a 4D-STEM and relate them to an undistorted experimental STEM image, followed by a series of affine transformations for distortion corrections. This method allows a minimum loss of information in both reciprocal and real spaces, enabling the reconstruction of sample information from 4D-STEM data sets. This method is computationally cheap, fast, and applicable for on-the-fly data analysis in future in situ cryogenic 4D-STEM experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗