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Intrinsic anharmonicity and thermal properties of ultralow thermal conductivity Ba 6 Sn 6 Se 13
Ultralow thermal conductivity materials continue to be of great interest for technologically important applications such as thermal insulators and thermoelectrics. Often, such materials possess constituents with extensive dynamic disorder, or “rattlers,” or structural disorder such as metallic glasses. Nevertheless, targeted crystalline bonding order and anharmonicity can provide effective means for the scattering of the phonons in certain materials. Our combined experimental and theoretical investigation of Ba 6 Sn 6 Se 13 reveals such a material, with ultralow thermal conductivity measured over a large temperature range. Optic phonon modes hybridize with acoustic modes at relatively low energies resulting in strong acoustic-optic scattering and limited phonon lifetimes. Moreover, our investigations reveal various avoided crossings at low energies that contribute to phonon scattering. These are derived from chiral phase symmetries and may result in nontrivial topological behaviors for phonon band crossings in this chiral material. This work contributes to the ongoing research on low thermal conductivity materials and the underlying mechanisms that affect their thermal behaviors. Manipulation of these effects may provide pathways for enhancement of material properties for targeted thermal applications using similar materials.
Real Space Quantum Cluster Formulation for the Typical Medium Theory of Anderson Localization
We develop a real space cluster extension of the typical medium theory (cluster-TMT) to study Anderson localization. By construction, the cluster-TMT approach is formally equivalent to the real space cluster extension of the dynamical mean field theory. Applying the developed method to the 3D Anderson model with a box disorder distribution, we demonstrate that cluster-TMT successfully captures the localization phenomena in all disorder regimes. As a function of the cluster size, our method obtains the correct critical disorder strength for the Anderson localization in 3D, and systematically recovers the re-entrance behavior of the mobility edge. From a general perspective, our developed methodology offers the potential to study Anderson localization at surfaces within quantum embedding theory. This opens the door to studying the interplay between topology and Anderson localization from first principles.
Neural Network Solver for Small Quantum Clusters
Machine learning approaches have recently been applied to the study of various problems in physics. Most of these studies are focused on interpreting the data generated by conventional numerical methods or the data on an existing experimental database. An interesting question is whether it is possible to use a machine learning approach, in particular a neural network, for solving the many-body problem. In this paper, we present a neural network solver for the single impurity Anderson model, the paradigm of an interacting quantum problem in small clusters. We demonstrate that the neural-network-based solver provides quantitative accurate results for the spectral function as compared to the exact diagonalization method. This opens the possibility of utilizing the neural network approach as an impurity solver for other many-body numerical approaches, such as the dynamical mean field theory.
Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems
Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.
Bridging the time scale in exascale computing of chemical systems (Final Technical Report)
This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.
Direct experimental evidence of tunable charge transfer at the LaNiO 3 / CaMnO 3 ferromagnetic interface
Interfacial charge transfer in oxide heterostructures gives rise to a rich variety of electronic and magnetic phenomena. Designing heterostructures where one of the thin-film components exhibits a metal-insulator transition opens a promising avenue for controlling such phenomena both statically and dynamically. In this work, we utilize a combination of depth-resolved soft x-ray standing-wave and hard x-ray photoelectron spectroscopies in conjunction with polarization-dependent x-ray absorption spectroscopy to investigate the effects of the metal-insulator transition in LaNiO 3 on the electronic and magnetic states at the LaNiO 3 /CaMnO 3 interface. Here, we report a direct observation of the reduced effective valence state of the interfacial Mn cations in the metallic superlattice with an above-critical LaNiO 3 thickness (6 unit cells, u.c.) facilitated by the charge transfer of itinerant Ni 3d e g electrons into the interfacial CaMnO 3 layer. Conversely, in an insulating superlattice with a below-critical LaNiO 3 thickness of 2 u.c., a homogeneous effective valence state of Mn is observed throughout the CaMnO 3 layers due to the blockage of charge transfer across the interface. The ability to switch and tune interfacial charge transfer enables precise control of the emergent ferromagnetic state at the LaNiO 3 /CaMnO 3 interface and, thus, has far-reaching consequences on the future strategies for the design of next-generation spintronic devices.
Design considerations for gallium arsenide pulse compression photoconductive switch
In this paper, we present the physics and design-space exploration of a novel pulse compression photoconductive switch (PCPS) using semi-insulating gallium arsenide (GaAs) operating in the negative differential mobility (NDM) regime of electron transport. We systematically quantify the relationship between the PCPS performance and various design options, including contact separation, laser energy and placement, and trap dynamics. Specifically, we report the full-width at half-maximum and the peak output current generated by the PCPS as a function of applied electrical and optical bias. We discuss the optimal spacing between the electrodes and the distance of the laser spot to the anode to achieve higher electron confinement and superior radio-frequency (RF) metrics. Reducing the laser energy is important to prevent the appearance of secondary peaks due to diffusive transport, but there exists a trade-off between the bandwidth and the maximum current of the PCPS. We also compare the PCPS response with and without trap dynamics and find that the electrostatic screening from the trap-induced space charge is time-independent when the trapping time constant is set larger than the recombination lifetime. Overall, trap dynamics are detrimental to performance, unless the compensation doping scheme to achieve semi-insulating GaAs is carefully selected. Results presented in this paper can be used by experimentalists to fine-tune the PCPS design parameters to meet the specifications of various RF applications. Moreover, our results will provide a strong theoretical basis to the measurements of PCPS devices using GaAs and other NDM materials under investigation.
Topological phase transition without single particle gap closing in strongly correlated systems
Here, in this study, we show two models where changing topology does not necessarily close the bulk insulating charge gap as demanded in the standard noninteracting picture. From extensive determinantal and dynamical cluster quantum Monte Carlo simulations of the half-filled and quarter-filled Kane-Mele-Hubbard model, we show that, for sufficiently strong interactions at either half- or quarter-filling, a transition between topological and trivial insulators occurs without the closing of a charge gap. To shed light on this behavior, we illustrate that an exactly solvable model reveals that while the single-particle gap remains, the many-body gap does, in fact, close. These two gaps are the same in the noninteracting system but depart from each other as the interaction turns on. We purport that for interacting systems, the proper probe of topological phase transitions is the closing of the many-body rather than the single-particle gap.
Quasi-two-dimensional ferromagnetism and anisotropic interlayer couplings in the magnetic topological insulator MnBi 2 Te 4
MnBi 2 Te 4 (MBT) is a promising van der Waals layered antiferromagnetic (AFM) topological insulator that combines a topologically nontrivial inverted Bi-Te band gap with ferromagnetic (FM) layers of Mn ions. Here, the inelastic neutron scattering on single crystals reported here describes rather complex magnetism in MBT. The magnetic anisotropy that controls the bulk and surface magnetic field response of MBT is found to have contributions from both single-ion and interlayer two-ion terms. A description of the quasi-two-dimensional intralayer FM spin waves requires long-range, competing FM and AFM interactions and anomalous damping. While this might suggest carrier-mediated magnetic coupling, abinitio calculations in insulating MBT also find long-range interactions, and classical spin dynamics simulations suggest that magnetic vacancies are at least partially responsible for observations of anomalous damping near the zone boundary.
Terahertz parametric amplification as a reporter of exciton condensate dynamics
Condensates are a hallmark of emergence in quantum materials with superconductors and charge density wave as prominent examples. An excitonic insulator (EI) is an intriguing addition to this library, exhibiting spontaneous condensation of electron-hole pairs. However, condensate observables can be obscured through parasitic coupling to the lattice. Time-resolved terahertz (THz) spectroscopy can disentangle such obscurants through measurement of the quantum dynamics. We target Ta 2 NiSe 5 , a putative room-temperature EI where electron-lattice coupling dominates the structural transition (T c = 326 K), hindering identification of excitonic correlations. A pronounced increase in the THz reflectivity manifests following photoexcitation and exhibits a BEC-like temperature dependence. This occurs well below the T c , suggesting a novel approach to monitor exciton condensate dynamics. Nonetheless, dynamic condensate-phonon coupling remains as evidenced by peaks in the enhanced reflectivity spectrum at select infrared-active phonon frequencies. This indicates that parametric reflectivity enhancement arises from phonon squeezing, validated using Fresnel-Floquet theory and density functional calculations. In conclusion, our results highlight that coherent dynamics can drive parametric stimulated emission with concomitant possibilities, including entangled THz photon generation.
Evidence for spin swapping in an antiferromagnet
Antiferromagnetic insulators offer strategic advantages in spintronic applications because of their negligible stray fields and ultrafast magnetic dynamics. Control of their magnetization and readout of their magnetic state are essential for these applications but remain challenging. In this work, we report the electrical detection of room-temperature magnetization switching in the canted antiferromagnetic insulator LaFeO 3 , capped with a Pt or W overlayer. The observation of a large magneto-thermovoltage with an in-plane temperature gradient suggests that the mechanism is the swapping of spin currents in the antiferromagnet. This effect provides a sensitive electrical probe of the tiny net magnetization in the insulator, which can be manipulated by a magnetic field on the order of 10 mT. Our results highlight a new material class of insulating canted antiferromagnets for spintronics and spin caloritronics and suggests a method for the electrical readout of magnetic signals in an antiferromagnetic insulator. Electrical readout of the state of an antiferromagnet is an important goal for spintronic applications. Now, detection of the electrical voltage created by a thermal gradient in a canted antiferromagnet suggests a route for achieving this goal.
Properties of Electronic Materials
This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.
Charge Transfer Dynamics in MoSe 2 /hBN/WSe 2 Heterostructures
Ultrafast charge transfer processes provide a facile way to create interlayer excitons in directly contacted transition metal dichalcogenide (TMD) layers. More sophisticated heterostructures composed of TMD/hBN/TMD enable new ways to control interlayer exciton properties and achieve novel exciton phenomena, such as exciton insulators and condensates, where longer lifetimes are desired. In this work, we experimentally study the charge transfer dynamics in a heterostructure composed of a 1 nm thick hBN spacer between MoSe 2 and WSe 2 monolayers. We observe the hole transfer from MoSe 2 to WSe 2 through the hBN barrier with a time constant of 500 ps, which is over 3 orders of magnitude slower than that between TMD layers without a spacer. Furthermore, we observe strong competition between the interlayer charge transfer and intralayer exciton–exciton annihilation processes at high excitation densities. Here, our work opens possibilities to understand charge transfer pathways in TMD/hBN/TMD heterostructures for the efficient generation and control of interlayer excitons.
Ultrafast nonequilibrium dynamics and high-harmonic generation in two-dimensional quantum spin Hall materials
For this work, we develop the theoretical framework of nonequilibrium ultrafast photonics in monolayer quantum spin Hall insulators supporting a multitude of topological states. In these materials, ubiquitous strong light-matter interactions in the femtosecond scale lead to nonadiabatic quantum dynamics, resulting in topology-dependent nonlinear optoelectronic transport phenomena. We investigate the mechanism driving topological Dirac fermions interacting with strong ultrashort light pulses and uncover various experimentally accessible physical quantities that encode fingerprints of the quantum material's topological electronic state from the high-harmonic generated spectrum. Our work sets the theoretical cornerstones to realize the full potential of time-resolved harmonic spectroscopy for understanding nonequilibrium processes in quantum topological systems and identifying topological invariants in two-dimensional quantum spin Hall solid state systems.
Neuromorphic learning with Mott insulator NiO
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. In this work, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia, habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.
Dynamic Tuning of Moiré Excitons in a WSe 2 /WS 2 Heterostructure via Mechanical Deformation
Moiré superlattices in van der Waals (vdW) heterostructures form by stacking atomically thin layers on top of one another with a twist angle or lattice mismatch. The resulting moiré potential leads to a strong modification of the band structure, which can give rise to exotic quantum phenomena ranging from correlated insulators and superconductors to moiré excitons and Wigner crystals. Here, in this study, we demonstrate the dynamic tuning of moiré potential in a WSe 2 /WS 2 heterostructure at cryogenic temperature. We utilize the optical fiber tip of a cryogenic scanning near-field optical microscope (SNOM) to locally deform the heterostructure and measure its near-field optical response simultaneously. The deformation of the heterostructure increases the moiré potential, which leads to a red shift of the moiré exciton resonances. We observe the interlayer exciton resonance shifts up to 20 meV, while the intralayer exciton resonances shift up to 17 meV.
Reversible Switch in Charge Storage Enabled by Selective Ion Transport in Solid Electrolyte Interphase
Solid-electrolyte interphases (SEIs) in advanced rechargeable batteries ensure reversible electrode reactions at extreme potentials beyond the thermodynamic stability limits of electrolytes by insulating electrons while allowing working ions to transport. Such selective ion transport occurs naturally in biological cell membranes as a ubiquitous prerequisite of many life processes and a foundation of biodiversity. In addition, cell membranes can selectively open and close the ion channels in response to external stimuli (e.g., electrical, chemical, mechanical, thermal), giving rise to “gating” mechanisms that help manage intracellular reactions. We wondered whether the chemistry and structure of SEIs can mimic cell membranes, such that ion gating can be replicated. That is, can SEIs realize a reversible switching between two electrochemical behaviors, i.e., the ion intercalation chemistry of batteries and the ion adsorption of capacitors? Herein, we report such SEIs that result in thermally activated selective ion transport. The function of open/close gate switches is governed by the chemical and structural dynamics of SEIs under different thermal conditions, with precise behaviors as conducting and insulating interphases that enable battery and capacitive processes within a finite temperature window. Such an ion gating function is synergistically contributed by Arrhenius-activated ion transport and SEI dissolution/regrowth. Following the understanding of this new mechanism, we then develop an electrochemical method to heal the SEI layer in situ. As a result, the knowledge acquired in this work reveals the possibility of hitherto unknown biomimetic properties of SEIs, which will guide us to leverage such complexities to design better SEIs for future battery chemistries.