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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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Solar and Storage Techno-Economic Analysis Tutorial for the IEEE Photovoltaic Specialist Conference (PVSC)

This tutorial will highlight the most recent efforts from the National Renewable Energy Laboratory (NREL) to track solar photovoltaic (PV) technology trends and manufacturing costs, project levelized cost of electricity (LCOE), and project levelized cost of solar plus storage (LCOSS) for systems across the globe. We will begin with an overview of the global PV supply chain and 2021 benchmark input data for NREL's crystalline silicon (c-Si) and thin film PV module manufacturing cost models. The framework that we follow and will review during this tutorial provides a methodology to prepare bottom-up manufacturing cost models including the items within the U.S. Generally Accepted Accounting Principles (GAAP) and the International Financial Reporting Standards (IFRS). For the polysilicon, wafer, cell conversion, and module assembly steps of the c-Si supply chain, and for thin film modules, we will review input data and methods useful for calculating the costs of goods sold (COGS); research and development (R&D) expenses; and sales, general, and business administration (S, G, &A) expenses. This 2021 benchmark analysis is compiled for state-of-the-art c-Si and thin film module manufacturing. We will also review methods for our 2021 system benchmark costs calculations and LCOE technoeconomic analysis of PV systems and solar plus storage systems. Next generation technologies that lower PV manufacturing and installation costs, reduce operations and maintenance (O&M) expenses, and improve system energy yield will also be highlighted. Techniques for comparing LCOE performance will also be reviewed. We look forward to sharing NREL's extensive work in these areas and discussing ideas for future directions.

cost models↗

Tutorial - Electric Motor and Integrated Traction Drive Thermal Management

The share of vehicles with fully electric propulsion systems is constantly increasing, and so is their traction drive power. The continuous push to increase power of electric vehicle (EV) traction drives necessitates their efficient cooling to prevent damage to temperature sensitive components of the drive system and achieving higher power outputs in a smaller footprint. With increasing power and power density of electric traction drives, their thermal management is becoming increasingly challenging. This tutorial will provide an overview of thermal management approaches for electric motors and power electronics in EV applications. It will review examples of current industry solutions for power-dense electric motor cooling, power electronics (inverter) cooling, their integration concepts and thermal management system solutions. We'll look at the advantages and challenges of power electronics integration into a single traction drive unit and respective thermal management system concepts. We'll talk about barriers to implementation of a unified thermal management system. The tutorial will also review key aspects of thermal management system design: modeling and simulation using FEA and CFD tools, experimental characterization, and general workflow for thermal management system evaluation.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.

(S)TEM↗

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modelling single atom catalysts for water splitting and fuel cells: A tutorial review

Here, in this tutorial review, we report the state-of-the-art of the modeling approaches of Single Atom Catalysts (SAC) for water splitting and fuel cells reactions. The discussion applies for Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (OER), Hydrogen Oxidation Reaction (HOR), and Oxygen Reduction Reaction (ORR). The main scope of this work is to underline the relevant aspects of SACs modelling. On the one hand, the review could help computational chemists aiming to start the study of SACs. On the other hand, experimentalists could find the critical analysis of DFT results of interest to understand better the strengths and weaknesses of simulations, and how to interpret computational results. After an introductory section of SACs, we start by briefly presenting the state-of-the-art methodologies. Then, we analyze the critical aspects for a reliable prediction of the electronic properties, and we discuss the robustness of the structural models and ways to validate them. Furthermore, we discuss the main approaches to predict catalytic activity and selectivity, which is the final goal of the computational catalysis. We conclude this review with a critical analysis of the current challenges in the field, and the main limitations of the modeling approaches that are described.

25 ENERGY STORAGE↗

Tutorial: Extracting entanglement signatures from neutron spectroscopy

This tutorial is a pedagogical introduction to recent methods of computing quantum spin entanglement witnesses from spectroscopy, with a special focus on neutron scattering on quantum spin systems. We offer a brief introduction to the concepts and equations, define a data analysis protocol, and discuss the interpretation of three entanglement witnesses: one-tangle, two-tangle, and Quantum Fisher Information. We also discuss practical experimental considerations, and give three examples of extracting entanglement witnesses from experimental data: Copper Nitrate, KCuF 3 , and NiPS 3 .

47 OTHER INSTRUMENTATION↗

A tutorial on the micro-trench technique for incident ion angle, material erosion, and impurity deposition measurements at plasma-facing surfaces

The micro-trench method is a new technique to measure polar and azimuthal incident ion angles, material erosion, and impurity deposition at plasma-facing surfaces, and has been applied in the DIII-D divertor. This article gives a tutorial of the micro-trench technique consisting of six steps: (1) micro-trench fabrication, (2) pre-exposure measurement of the fabricated micro-trench geometry, (3) tracer material deposition, (4) plasma exposure, (5) post-exposure observation of the tracer material, and (6) post-exposure measurement of the micro-trench geometry. Two criteria need to be satisfied to apply the micro-trench method successfully: (i) uniform impurity deposition on the micro-trench floor, and (ii) erosion dominated by the physical sputtering induced by the impinging ions. Furthermore, when those two criteria are satisfied, post-exposure analysis of the impurity deposition patterns on the micro-trench floor may be used to determine the polar and azimuthal incident ion directions (mean values of the ion angle directions), erosion rate, and impurity deposition rate during plasma exposure without computational interpretation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Corrigendum to “Transport of intensity equation: A tutorial” Optics and Lasers in Engineering, Volume 135 (2020) 106187

In this Corrigendum, we correct misprints in equations and figures of the article titled “Transport of intensity equation: a tutorial” Optics and Lasers in Engineering, 135, 106187, 2020.1 These misprints were caused by unanticipated issues in email communication between the authors and the editorial team during the proofreading stage. The authors would like to apologize for any inconvenience caused.

36 MATERIALS SCIENCE↗

Tutorial: The equations of electron emission and their evaluation

Electron emission and transport through and over potential barriers is an essential process requiring modeling and simulation to meet the design needs and characterization of an exceedingly broad range of technologically important devices and processes. The simulation and description of thermal, field, and photoemission, and the related concerns of space–charge affected electron flow, often make use of specialized formulations developed in the early days of quantum mechanics. Advancements in the utilization of electron sources and particularly the simulation of devices and applications using advanced particle-in-cell and trajectory methods for beam optics codes create a strong need for a pedagogical account of the emission models to ensure correct numerical evaluation of their equations. This Tutorial starts from simple phenomenological accounts and progressively builds to comprehensive models emphasizing straightforward and often rapid calculation. It recommends formulations to supplant the canonical Richardson–Laue–Dushman (thermal), Fowler–Nordheim (field), Fowler–DuBridge (photo), and Baroody (secondary) equations and provides a useful formulation of space–charge affected flow commonly described by the Child–Langmuir relation that takes into account cathode dependence on surface field.

Physics↗

Tutorial: Defects in topological semimetals

Three-dimensional topological semimetals are a class of electronic materials in which their bulk and surface states contain linear band touching nodes near the Fermi level. Like semiconductors, their properties will be affected by point and extended defects in their crystal structures, although the extent to which defects and disorders influence topological semimetals may differ in key ways due to their unique electronic structures. In this Tutorial, we provide an overview of the defects in topological semimetals, covering both computational and experimental methods for exploring defect-property relationships. We also include a discussion on open questions that still need to be explored further.

36 MATERIALS SCIENCE↗

Ice sculpting: An artificial spin ice Tutorial on controlling microstate and geometry for magnonics and neuromorphic computing

Artificial spin ice, arrays of strongly interacting nanomagnets, are complex magnetic systems with many emergent properties, rich microstate spaces, intrinsic physical memory, high-frequency dynamics in the GHz range, and compatibility with a broad range of measurement approaches. This Tutorial article aims to provide the foundational knowledge needed to understand, design, develop, and improve the dynamic properties of artificial spin ice. Special emphasis is placed on introducing the theory of micromagnetics, which describes the complex dynamics within these systems, along with their design, fabrication methods, and standard measurement and control techniques. The article begins with a review of the historical background, introducing the underlying physical phenomena and interactions that govern artificial spin ice. We then explore the standard experimental techniques used to prepare the microstate space of the nanomagnetic array and to characterize magnetization dynamics, both in artificial spin ice and more broadly in ferromagnetic materials. Finally, we introduce the basics of neuromorphic computing applied to the case of artificial spin ice systems with a goal to help researchers new to the field grasp these exciting new developments.

Sultana, Rawnak [Univ. of Delaware, Newark, DE (Un↗

A tutorial on high-order harmonic generation in atoms, molecules, and condensed matter

This tutorial introduces strong-field-driven high-order harmonics, their experimental generation and characterization techniques, and their main applications including attosecond pulse generation and ultrafast spectroscopy of the target material. We begin from the use of atomic targets, where the first high-order harmonic generation (HHG) experiments were realized in the late 1980s. Then, we briefly discuss the basics of the microscopic generation mechanism and how various steps of the mechanism were exploited in applications such as generating isolated attosecond pulses and probing molecular orbitals. We introduce and describe the standard experimental approaches for condensed phase HHG, where we discuss unique technical challenges of the use of solid-state materials, such as the mitigation of plasma formation and laser damage. We cover the fundamentals of high-harmonic spectroscopy in condensed matter systems, such as wide bandgap dielectrics, semiconductors, liquid media, and 2D-crystals. We provide some examples of rapidly emerging spectroscopic capabilities, such as for probing crystal symmetries, Berry phases, and associated non-trivial topological properties of the source material. Finally, we provide an overview of the research field, including some of the challenges, opportunities, and open questions.

Attosecond pulses↗

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗

e3nn tutorial v0.2

Repository and website for tutorials on 3d Euclidean equivariant neural networks.

Smidt, Tess↗

2024 Workshop - Remote Sensing and Fluxes Upscaling for Real-world Impact - Tutorial v1

The software-tutorial was developed within the 2024 Remote Sensing and Fluxes Upscaling for Real-world Impact workshop as part of the hands-on session. The workshop was supported by AmeriFlux, National Ecological Observatory Network (NEON) and CarbonDew. The software provides basic tools to perform the following tasks: - gather remote sensing images using Google Earth Engine API; - gather flux data; - perform basic functions, such as plotting time-series, perform QA of the data, compute vegetation indices; - perform correlation analysis between flux data and remote sensing data; - perform flux predictions based on remote sensing data integrated in different modalities.

Falco, Nicola [Lawrence Berkeley National Laborato↗

A tutorial review of machine learning-based model predictive control methods

Abstract This tutorial review provides a comprehensive overview of machine learning (ML)-based model predictive control (MPC) methods, covering both theoretical and practical aspects. It provides a theoretical analysis of closed-loop stability based on the generalization error of ML models and addresses practical challenges such as data scarcity, data quality, the curse of dimensionality, model uncertainty, computational efficiency, and safety from both modeling and control perspectives. The application of these methods is demonstrated using a nonlinear chemical process example, with open-source code available on GitHub. The paper concludes with a discussion on future research directions in ML-based MPC.

Wu, Zhe [Department of Chemical and Biomolecular E↗

OCHRE User Tutorial

OCHRE user tutorial via a browser extension.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗