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Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Applied Sciences (Switzerland)

Sarma, Raktim S.; Pribisova, Abigail; Sumner, Bjorn; Briscoe, Jayson

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Unraveling Thermodynamic and Kinetic Contributions to the Stability of Doped Nanocrystalline Alloys using Nanometallic Multilayers

Advanced Materials

Cunningham, W.S.; Riano, J.S.; Wang, Wenbo; Hwang, Sooyeon; Hattar, Khalid M.; Hodge, Andrea M.; Trelewicz, Jason R.

Targeted doping of grain boundaries is widely pursued as a pathway for combating thermal instabilities in nanocrystalline metals. However, certain dopants predicted to produce grain-boundary-segregated nanocrystalline configurations instead form small nanoprecipitates at elevated temperatures that act to kinetically inhibit grain growth. Here, thermodynamic modeling is implemented to select the Mo–Au system for exploring the interplay between thermodynamic and kinetic contributions to nanostructure stability. Using nanoscale multilayers and in situ transmission electron microscopy thermal aging, evolving segregation states and the corresponding phase transitions are mapped with temperature. The microstructure is shown to evolve through a transformation at lower homologous temperatures (<600 °C) where solute atoms cluster and segregate to the grain boundaries, consistent with predictions from thermodynamic models. An increase in temperature to 800 °C is accompanied by coarsening of the grain structure via grain boundary migration but with multiple pinning events uncovered between migrating segments of the grain boundary and local solute clustering. Direct comparison between the thermodynamic predictions and experimental observations of microstructure evolution thus demonstrates a transition from thermodynamically preferred to kinetically inhibited nanocrystalline stability and provides a general framework for decoupling contributions to complex stability transitions while simultaneously targeting a dominant thermal stability regime.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Magnetic properties of equiatomic CrMnFeCoNi

Physical Review B

Elmslie, Timothy A.; Startt, Jacob K.; Soto-Medina, Sujeily; Feng, Keke; Zappala, Emma; Frandsen, Benjamin A.; Meisel, Mark W.; Dingreville, Remi; Hamlin, James J.

Magnetic, specific heat, and structural properties of the equiatomic Cantor alloy system are reported for temperatures between 5 and 300 K, and up to fields of 70 kOe. Magnetization measurements performed on as-cast, annealed, and cold-worked samples reveal a strong processing history dependence and that high-temperature annealing after cold working does not restore the alloy to a "pristine"state. Measurements on known precipitates show that the two transitions, detected at 43 and 85 K, are intrinsic to the Cantor alloy and not the result of an impurity phase. Experimental and ab initio density functional theory computational results suggest that these transitions are a weak ferrimagnetic transition and a spin-glass-like transition, respectively, and magnetic and specific heat measurements provide evidence of significant Stoner enhancement and electron-electron interactions within the material.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Elucidating the temperature dependence of TRIP in Q&P steels using synchrotron X-Ray diffraction, constituent phase properties, and strain-based kinetics models

Acta Materialia

Finfrock, Christopher B.; Ellyson, Benjamin; Likith, Sri R.J.; Smith, Douglas; Rietema, Connor; Saville, Alec I.; Thrun, Melissa M.; Becker, C.G.; Araujo, Ana L.; Pavlina, Erik J.; Hu, Jun; Park, Jun-Sang; Clarke, Amy J.; Clarke, Kester D.

Understanding the deformation-induced martensitic transformation (DIMT) is critical for interpreting the structure-property relationships that govern the performance of transformation-induced plasticity (TRIP) assisted steels. However, modern TRIP-assisted steels often exhibit DIMT kinetics that are not easily captured by existing empirical models based on bulk tensile strain. We address this challenge by combined bulk uniaxial tensile tests and in-situ high energy synchrotron X-ray diffraction, which resolved the phase volume fractions, stress-strain response, and microstructure evolution of each constituent phase. A modification of the Olson-Cohen model is implemented, which describes the martensitic transformation kinetics as a function of the estimated partitioned strain in austenite, rather than the bulk tensile strain. This DIMT kinetic model is used as a framework to clarify the root cause of an insufficiently understood toughness trough reported for TRIP-assisted steels during deformation at elevated temperatures. Here, the importance of the temperature-dependent toughness is discussed, based on the opportunity to modify deformation processes to tailor the DIMT kinetics and mechanical properties during forming and in service.

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TYPE Journal Article YEAR 2022
DOIOSTI

2022 MB3a Infrasound Sensor Type Approval Evaluation

Merchant, Bion J.

Sandia National Laboratories has tested and evaluated an updated version of the MB3a infrasound sensor, designed by CEA and manufactured by SeismoWave. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, full scale, self-noise, dynamic range, response, passband, sensitivity variation due to changes in barometric pressure and temperature, and sensitivity to acceleration. The MB3a infrasound sensors are being evaluated for use in the International Monitoring System (IMS) of the Preparatory Commission to the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).

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TYPE SAND Report YEAR 2022
DOIOSTI

Automating Component-Level Stress Measurements for Inverter Reliability Estimation

Energies

Flicker, Jack D.; Johnson, Jay; Hacke, Peter; Thiagarajan, Ramanathan

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous operating modes which induce new stresses on the power electronics components. In this work, an experimental and theoretical framework is introduced which couples laboratory-measured component stress with advanced inverter functionality and derives a reduction in useful lifetime based on an applicable reliability model. Multiple DER devices were instrumented to calculate the additional component stress under multiple reactive power setpoints to estimate associated DER lifetime reductions. A clear increase in switch loss was demonstrated as a function of irradiance level and power factor. This is replicated in the system-level efficiency measurements, although magnitudes were different—suggesting other loss mechanisms exist. Using an approximate Arrhenius thermal model for the switches, the experimental data indicate a lifetime reduction of 1.5% when operating the inverter at 0.85 PF—compared to unity PF—assuming the DER failure mechanism thermally driven within the H-bridge. If other failure mechanisms are discovered for a set of power electronics devices, this testing and calculation framework can easily be tailored to those failure mechanisms.

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TYPE Conference Presentation YEAR 2022
DOIOSTIScopus

A Scalable Lower Bound for the Worst-Case Relay Attack Problem on the Transmission Grid

INFORMS Journal on Computing

Johnson, Emma S.; Dey, Santanu S.

We consider a bilevel attacker–defender problem to find the worst-case attack on the relays that control transmission grid components. The attacker infiltrates some number of relays and renders all of the components connected to them inoperable with the goal of maximizing load shed. The defender responds by minimizing the resulting load shed, redispatching using a DC optimal power flow (DCOPF) problem on the remaining network. Though worst-case interdiction problems on the transmission grid have been studied for years, there remains a need for exact and scalable methods. Methods based on using duality on the inner problem rely on the bounds of the dual variables of the defender problem in order to reformulate the bilevel problem as a mixed integer linear problem. Valid dual bounds tend to be large, resulting in weak linear programming relaxations and, hence, making the problem more difficult to solve at scale. Often smaller heuristic bounds are used, resulting in a lower bound. In this work, we also consider a lower bound, but instead of bounding the dual variables, we drop the constraints corresponding to Ohm’s law, relaxing DCOPF to capacitated network flow. We present theoretical results showing that, for uncongested networks, approximating DCOPF with network flow yields the same set of injections and, thus, the same load shed, which suggests that this restriction likely gives a high-quality lower bound in the uncongested case. Furthermore, we show that, in the network flow relaxation of the defender problem, the duals are bounded by one, so we can solve our restriction exactly. Finally, because the big-M values in the linearization are equal to one and network flow has a well-known structure, we see empirically that this formulation scales well computationally with increased network size. Through empirical experiments on 16 networks with up to 6,468 buses, we find that this bound is almost always as tight as we can get from guessing the dual bounds even for congested networks in which the theoretical results do not hold. In addition, calculating the bound is approximately 150 times faster than achieving the same bound with the reformulation guessing the dual bounds.

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TYPE Conference Presentation YEAR 2022
DOIOSTIScopus

Ensuring a Nuclear Power Plant Safe State Following an EMP Event - Task 7 Deliverable: EMP Testing of Secondary Coupling to Instrumentation Cables

Bowman, Tyler C.; Guttromson, Ross; San Martin, Luis

Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.

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TYPE SAND Report YEAR 2022
DOIOSTI

Cybersecurity for Electric Vehicle Charging Infrastructure

Johnson, Jay; Anderson, Benjamin; Wright, Brian J.; Quiroz, Jimmy E.; Berg, Timothy M.; Graves, Russell; Daley, Josh; Phan, Kandy; Kunz, Michael; Pratt, Rick; Carroll, Tom; Oneil, Lori R.; Dindlebeck, Brian; Maloney, Patrick; Brien, David'; Gotthold, David; Varriale, Roland; Bohn, Ted; Hardy, Keith

As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing area of concern as charging stations increase power delivery capabilities and must communicate to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid operator communication systems could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks — or public perception of such — would ripple across the industry and produce lasting effects. Unfortunately, there is currently no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured inter faces. Comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project provided the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team created a cybersecurity threat model and performed a technical risk assessment of EVSE assets across multiple manufacturers and vendors, so that automotive, charging, and utility stakeholders could better protect customers, vehicles, and power systems in the face of new cyber threats.

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TYPE SAND Report YEAR 2022
DOIOSTI

Onboarding in a Virtual Environment

Khan, Rabia; Miller, Michelle; Valerio, Analise; Willhite, Isabella; Hernandez, Zachary

A need for a standardized Division 10000 onboarding program for virtual hires was identified by management to formalize the way employees and interns are onboarded and trained into Division 10000. This white paper provides effective short and long-term suggestions in the efforts of improving virtual onboarding. Data suggests that remote work is going to become the forefront of many industry practices, which indicates the need of a standardized virtual onboarding practices. With our research, gap assessments, benchmarking, and conducting interviews both internally and externally, we found that clarity, culture, and connection proved to be the strongest solutions in order to maintain Sandia’s competitive edge and sustain workers both remote and in-person.

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TYPE Other Report YEAR 2022
DOIOSTI

Detecting hidden transient events in noisy nonlinear time-series

Chaos

Montoya, Angela C.; Habtour, E.; Moreu, F.

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Incipient Melting in AA7075

Brehm, Johnathon R.; Buckner, Jessica L.; Profazi, Christina A.; Foulk, James W.

Incipient melting is a phenomenon that can occur in aluminum alloys where solute rich areas, such as grain boundaries, can melt before the rest of the material; incipient melting can degrade mechanical and corrosion properties and is irreversible, resulting in material scrapping. After detecting indications of incipient melting as the cause of failure in 7075 aluminum alloy parts (AA7075), a study was launched to determine threshold temperature for incipient melting. Samples of AA7075 were solution annealed using temperatures ranging from 870-1090F. A hardness profile was developed to demonstrate the loss of mechanical properties through the progression of incipient melting. Additionally, Zeiss software Zen Core Intellesis was utilized to more accurately quantify the changes in microstructural properties as AA7075 surpassed the onset of incipient melting. The results from this study were compared with previous AA7075 material that demonstrated incipient melting.

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TYPE SAND Report YEAR 2022
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Results 6101–6200 of 99,299
Results 6101–6200 of 99,299