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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.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

New classes of topological crystalline insulators having surface rotation anomaly

We discover new types of quantum anomalies in two-dimensional systems with time-reversal symmetry (T) and discrete rotation symmetry with order of n = 2, 4, and 6 (C n ). The new anomalous states have n flavors of massless Dirac fermions protected by T and C n , whereas any two-dimensional lattices having the two symmetries must have a multiple of 4, 8, and 12 Dirac cones for n = 2, 4, and 6, respectively. We show that these anomalous states are physically realized on the surface of new classes of topological crystalline insulators, normal to the rotation axis. Moreover, these topological crystalline insulators support n gapless one-dimensional helical mode on the otherwise fully gapped side surface, connecting the anomalous two-dimensional states on the top and bottom surfaces. The presence of these helical modes enables a new quantum device made from a topological crystalline insulator nanorod, a “helical nanorod,” which has a quantized longitudinal conductance of ne 2 /h.

Science & Technology - Other Topics↗
DOE OSTI2021

An index for two-dimensional SPT states

We define an index for 2D G-invariant invertible states of bosonic lattice systems in the thermodynamic limit for a finite symmetry group G with a unitary action. Furthermore, we show that this index is an invariant of the symmetry protected phase.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Visualizing Tailored Spin Phenomena in a Reduced‐Dimensional Topological Superlattice

Abstract Emergent topological insulators (TIs) and their design are in high demand for manipulating and transmitting spin information toward ultralow‐power‐consumption spintronic applications. Here, distinct topological states with tailored spin properties can be achieved in a single reduced‐dimensional TI‐superlattice, (Bi 2 /Bi 2 Se 3 )‐(Bi 2 /Bi 2 Se 3 ) N or (□/Bi 2 Se 3 )‐(Bi 2 /Bi 2 Se 3 ) N ( N is the repeating unit, □ represents an empty layer) by controlling the termination via molecular beam epitaxy. The Bi 2 ‐terminated superlattice exhibits a single Dirac cone with a spin momentum splitting ≈0.5 Å −1 , producing a pronounced inverse Edelstein effect with a coherence length up to 1.26 nm. In contrast, the Bi 2 Se 3 ‐terminated superlattice is identified as a dual TI protected by coexisting time reversal and mirror symmetries, showing an unexpectedly long spin lifetime up to 1 ns. The work elucidates the key role of dimensionality and dual topological phases in selecting desired spin properties, suggesting a promise route for engineering topological superlattices for high‐performance TI‐spintronic devices.

Sun, Rui↗
DOE OSTI2020

X Fe 4 Ge 2 ( X = Y , Lu ) and Mn 3 Pt : Filling-enforced magnetic topological metals

Magnetism, coupled with nontrivial band topology, can bring about many interesting and exotic phenomena, so that magnetic topological materials have attracted persistent research interest. However, compared with nonmagnetic topological materials (TMs), the magnetic TMs are less studied, since their magnetic structures and topological phase transitions are usually complex and the first-principles predictions are usually sensitive on the effect of Coulomb interaction. Here we present a comprehensive investigation of XFe 4 Ge 2 (X = Y, Lu) and Mn 3 Pt, and find these materials to be filling-enforced magnetic topological metals. Our first-principles calculations show that XFe 4 Ge 2 (X = Y, Lu) host Dirac points near the Fermi level at high symmetry point S. These Dirac points are protected by $\text{P}\mathcal{T}$ symmetry ($\text{P}$ and $\mathcal{T}$ are inversion and time-reversal transformations, respectively) and a twofold screw rotation symmetry. Moreover, through breaking $\text{P}\mathcal{T}$ symmetry, the Dirac points would split into Weyl nodes. Mn 3 Pt is found to host fourfold degenerate band crossings in the whole high symmetry path of A – Z . We also utilize the GGA + U scheme to take into account the effect of Coulomb repulsion and find that the filling-enforced topological properties are naturally insensitive on U .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Protection Against Graph-Based False Data Injection Attacks on Power Systems

Graph signal processing (GSP) has emerged as a powerful tool for practical network applications, including power system monitoring. By representing power system voltages as smooth graph signals, recent research has focused on developing GSP-based methods for state estimation, attack detection, and topology identification. Included, efficient methods have been developed for detecting false data injection (FDI) attacks, which until now were perceived as non-smooth with respect to the graph Laplacian matrix. Consequently, these methods may not be effective against smooth FDI attacks. In this paper, we propose a graph FDI (GFDI) attack that minimizes the Laplacian-based graph total variation (TV) under practical constraints. In addition, we develop a low-complexity algorithm that solves the non-convex GDFI attack optimization problem using ell_1-norm relaxation, the projected gradient descent (PGD) algorithm, and the alternating direction method of multipliers (ADMM). We then propose a protection scheme that identifies the minimal set of measurements necessary to constrain the GFDI output to high graph TV, thereby enabling its detection by existing GSP-based detectors. Our numerical simulations on the IEEE-57 bus test case reveal the potential threat posed by well-designed GSP-based FDI attacks. Moreover, we demonstrate that integrating the proposed protection design with GSP-based detection can lead to significant hardware cost savings compared to previous designs of protection methods against FDI attacks.

Morgenstern, Gal↗
DOE OSTI2020

Layer-dependent topological phase in a two-dimensional quasicrystal and approximant

The electronic and topological properties of materials are derived from the interplay between crystalline symmetry and dimensionality. Simultaneously introducing “forbidden” symmetries via quasiperiodic ordering with low dimensionality into a material system promises the emergence of new physical phenomena. Here, we isolate a two-dimensional (2D) chalcogenide quasicrystal and approximant, and investigate their electronic and topological properties. The 2D layers of the materials with a composition close to Ta 1.6 Te, derived from a layered transition metal dichalcogenide, are isolated with standard exfoliation techniques, and investigated with electron diffraction and atomic resolution scanning transmission electron microscopy. Density functional theory calculations and symmetry analysis of the large unit cell crystalline approximant of the quasicrystal, Ta 21 Te 13 , reveal the presence of symmetry-protected nodal crossings in the quasicrystalline and approximant phases, whose presence is tunable by layer number. Our study provides a platform for the exploration of physics in quasicrystalline, low-dimensional materials and the interconnected nature of topology, dimensionality, and symmetry in electronic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anderson critical metal phase in trivial states protected by average magnetic crystalline symmetry

Transitions between distinct obstructed atomic insulators (OAIs) protected by crystalline symmetries, where electrons form molecular orbitals centering away from the atom positions, must go through an intermediate metallic phase. In this work, we find that the intermediate metals will become a scale-invariant critical metal phase (CMP) under certain types of quenched disorder that respect the magnetic crystalline symmetries on average. We explicitly construct models respecting average C 2z T, m, and C 4z T and show their scale-invariance under chemical potential disorder by the finite-size scaling method. Conventional theories, such as weak anti-localization and topological phase transition, cannot explain the underlying mechanism. A quantitative mapping between lattice and network models shows that the CMP can be understood through a semi-classical percolation problem. Ultimately, we systematically classify all the OAI transitions protected by (magnetic) groups Pm, P2', P4', and P6' with and without spin-orbit coupling, most of which can support CMP.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Optimized Highly Efficient SSCB Using Organic Substrate Packaging for Electric Vehicle Applications

Solid State Circuit Breakers (SSCBs) are an attractive protection solution for their arcless current interruption and fast actuation speeds over mechanical breakers. This paper proposes a Bidirectional SSCB (BSSCB) with a thermally defined and digitally controlled current time profile for fault protection in EV and other low-voltage DC systems. The paper proposes an organic packaging approach utilizing flex circuitry to develop a reliable, cost-effective power module for BSSCBs. The paper studies transient heat transfer in the power modules using finite element analysis (FEA). An RC themal ladder network is extracted to define a fusing curve. To demonstrate and verify the design, a 1kV/50 A SiC MOSFET BSSCB prototype is fabricated and tested, having a power density of 60 W/cm3 and 4x reduction in form factor over presently researched breakers. Also, given are results for 750 V/150 A operation showing interruption in 2.4 μs.

organic power packaging↗
DOE OSTI2023

Synthesis of hyperbranched polymer films via electrodeposition and oxygen-tolerant surface-initiated photoinduced polymerization

Hypothesis Hyperbranched polymers, not only possess higher functionality, but are also easier to prepare compared to dendrimers and dendric polymers. Combining electrodeposition and surface-initiated photoinduced electron transfer-reversible addition-fragmentation chain transfer (SI-PET-RAFT) polymerization is hypothesized to be a novel strategy for preparing hyperbranched polymer films on conductive surfaces without degassing. Experiments In this study, polymer brush grafted films with four different architectures (i.e. linear, branched, linear- block -branched, and branched- block -linear) were prepared on gold-coated glass substrates using electrodeposition, followed by SI-PET-RAFT polymerization. The resulting film structure and thickness, surface topology, absorption property, and electrochemical behavior were confirmed by spectroscopy, microscopy, microbalance technique, and impedance measurement. Findings These hyperbranched polymer brushes were capable of forming a thicker but more uniformly covered films compared to linear polymer brush films, demonstrating that hyperbranched polymer films can be potentially useful for fabricating protective polymer coatings on various conductive surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evidence for deconfined U(1) gauge theory at the transition between toric code and double semion

Building on quantum Monte Carlo simulations, we study the phase diagram of a one-parameter Hamiltonian interpolating between trivial and topological Ising paramagnets in two dimensions, which are dual to the toric code and the double semion. We discover an intermediate phase with stripe order which spontaneously breaks the protecting Ising symmetry. Remarkably, we find evidence that this intervening phase is gapless due to the incommensurability of the stripe pattern and that it is dual to a $U(1)$ gauge theory exhibiting Cantor deconfinement.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗
DOE OSTI2022

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2020

Laser-interference pulse number dependence of surface chemistry and sub-surface microstructure of AA2024-T3 alloy

The laser-based treatment of a metal surface is an intrinsically non-chemical technique that can alter both the topology and chemistry of surfaces. A laser-based treatment for coating and joining applications can offer alternative surface preparations to the chemically-based surface preparation techniques, which are subject to severe environmental protection and hazardous-waste management considerations. In this study, the surface chemistry and sub-surface microstructural changes are investigated for a novel surface processing method using laser interferometry produced by two beams of a pulsed Nd:YAG laser. The two-beam laser-interference allowed the structuring of the surface at length scales much less than that of the laser beam spot. Surface chemistry changes in the oxide layer of AA 2024-T3 aluminum alloy rolled sheet due to laser processing were investigated using x-ray photoelectron spectroscopy (XPS). Near surface microstructural changes have been investigated with scanning electron microscopy and energy dispersive x-ray spectroscopy (SEM/EDS), and scanning transmission electron microscopy (STEM) as a function of number of interfering laser shots. SEM microstructure pictures of the top surface shows the minimization of surface defects, as all of the sharp features from a rolled sheet surface were smoothed by laser-structuring. STEM images indicate that the laser-interference processing reduced the formation of CuMn-rich precipitates over a 500–800 nm depth from the top surface. XPS data indicated that the Al oxide layer is modified compared to that of the baseline specimen and that the oxide thickness increases with the number of shots per spot. Finally, the additional thicker oxide on Al alloys is expected to increase the corrosion resistance of the coated Al 2024.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Real-Time Testbed for Smart Inverter Cyber Security Studies

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Probing ferroelectric domain structures and their switching dynamics in SrBi2Ta2O9 by in-situ electric biasing in transmission electron microscopy

Abstract Lead-free SrBi 2 Ta 2 O 9 (SBT) has been a promising ferroelectric material for various applications such as electronics and data storage due to its outstanding ferroelectric properties including high fatigue endurance and low leakage current. However, the atomic-scale domain structure and switching dynamics of ferroelectric SBT remain elusive. This study reveals that spontaneous polarization arises from canted bismuth-cation displacements, forming 90° and Ising-type 180° domain walls. Interestingly, topological pairs of ferroelectric vortex and antivortex connect ferroelectric boundaries where three domain walls converge. In situ electrical biasing transmission electron microscopy (TEM) reveals the dominance of 180° switching over 90°, where oxygen octahedral connectivity is protected by ferroelastic energy in the 90° domain wall. Consequently, all 180° domain walls and (anti)vortices are removed, leaving only 90° domain walls in the electrically poled states. Chemical deterioration along domain walls highlights vulnerability of SBT to ferroelectric fatigue. This study provides insight into crucial aspects for practical applications of SBT.

36 MATERIALS SCIENCE↗