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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗
DOE OSTI2024

Enabling fast discharge of Li-ion batteries via electrolyte formulations for urban air mobility applications

High-power discharge requirements are critical for lithium-ion batteries (LIBs) used in electric Vertical Takeoff and Landing (eVTOL) vehicles that are increasingly considered in urban mobility. This investigation places a particular emphasis on understanding the impact of electrolytes on discharge processes and rate capability. We aim to compare the discharge behavior of LiBs using a conventional electrolyte (Gen 2: 1.2 M LiPF 6 in EC:EMC) and the dual salt LiTFSI-LiBOB-based electrolyte. Here we carefully examine the profiles of charging and discharging, the behavior during extended cycles, impedance spectroscopy results, and the characteristics of the electrode surface. Our research findings demonstrate the complex relationship between the composition of electrolytes and the specific high-power discharge requirements of electric vertical takeoff and landing (eVTOL) systems. This research highlights the importance of customizing electrolyte compositions to optimize energy storage density while simultaneously enabling higher power extraction to enhance performance in short-range electric aviation.

25 ENERGY STORAGE↗
DOE OSTI2024

Sliceable, Moldable, and Highly Conductive Electrolytes for All-Solid-State Batteries

All-solid-state batteries (ASSBs) require solid electrolytes with high ionic conductivity, stability, and deformability for optimal energy and power density. Here, we developed lithium-deficient lithium yttrium bromide (LYB) solid electrolytes, Li 3–x YBr 6–x (0 ≤ x ≤ 0.50), using a comelting method with controlled lithium deficiency. These electrolytes exhibit favorable mechanical properties such as high moldability and sliceability. The Li 2.65 YBr 5.65 composition has an ionic conductivity of 4.49 mS cm –1 at 25 °C and an activation energy of 0.28 eV. Compared to Li 3 YBr 6 , Li 2.65 YBr 5.65 demonstrates improved rate performance and cycling stability in ASSBs. High-resolution X-ray diffraction confirms the formation of the LYB phase with a C2/m space group. Structural analysis reveals increased cation disorder and larger polyhedral volumes for x > 0 in Li 3–x YBr 6–x , contributing to reduced Li + migration energy barriers. Bond valence site energy calculations and molecular dynamics simulations reveal enhanced 3D lithium-ion transport. NMR spectroscopy further highlights increased Li + dynamics and impurity elimination.

Poudel, Tej P. [Florida State Univ., Tallahassee, ↗
DOE OSTI2021

Redox conditions correlated with vibronic coupling modulate quantum beats in photosynthetic pigment–protein complexes

Significance Photosynthetic organisms evolved their light-harvesting antenna complexes to optimize energy transfer. It was recently shown that the redox environment can tune the mixing of electronic and vibrational states to steer energy through different pathways of a pigment–protein complex. Quantum beating signals in the spectra of pigment–protein complexes have been used to probe the excited-state dynamics within the complexes, but the microscopic dynamics that generate these signals and their role in promoting energy transfer are not fully understood. Here, we show that the redox environment that tunes energy transfer similarly tunes the quantum beating signals in the same complex. We find that the beats report on excited-state vibrations that maintain coherence through the vibronically enhanced energy transfer process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Plasmonic waveguides from Coulomb-engineered two-dimensional metals

Abstract Coulomb interactions play an essential role in atomically-thin materials. On one hand, they are strong and long-ranged in layered systems due to the lack of environmental screening. On the other hand, they can be efficiently tuned by means of surrounding dielectric materials. Thus all physical properties which decisively depend on the exact structure of the electronic interactions can be in principle efficiently controlled and manipulated from the outside via Coulomb engineering. Here, we show how this concept can be used to create novel plasmonic waveguides in metallic layered materials. We discuss how dielectrically structured environments can be utilized to non-invasively confine plasmonic excitations in an unperturbed homogeneous metallic two-dimensional system by modifications of its many-body interactions. We define optimal energy ranges for this mechanism and demonstrate plasmonic confinement within several nanometers. In contrast to conventional functionalization mechanisms, this scheme relies on a purely many-body concept and does not involve any direct modifications to the active material itself.

Materials Science↗
DOE OSTI2020

Properties of La 0.7 Ca 0.3 MnO 3 under extreme tensile strain

The complex phase diagram of manganites with simultaneously active spin, charge, orbital, and lattice degrees of freedom continues providing surprises. In a recent groundbreaking experiment, membranes of the perovskite manganite La 0.7 Ca 0.3 MnO 3 (LCMO) deposited on a flexible polymer layer were strained up to 8% [S. S. Hong et al., Science 368, 71 (2020)], much more than achieved by regular strain induced by a rigid substrate. By increasing this strain, a metal-insulator transition was reported. Here we reproduce the results of the experiments using Monte Carlo simulations of the two-orbital double-exchange model including Jahn-Teller distortions at hole density x=1/3. The full phase diagram with varying temperature and Jahn-Teller coupling λ is presented. When the bandwidth W of mobile electrons is reduced, thus when the effective Jahn-Teller coupling λ/W is increased, a metal-insulator transition is found in our simulations, between a ferromagnetic metallic state with uniform charge distribution and an insulator with diagonal charge stripes that retains its ferromagnetic character. In between the hole-rich diagonals, staggered orbital order occurs. We also report resistivity and magnetization measurements alongside with spin correlations and charge structure factors. Our overall conclusions are in agreement with the recent experimental and density functional theory results by Hong et al., and we confirm much earlier ground state predictions of striped ferromagnetic order using energy optimization techniques by T. Hotta et al. [Phys. Rev. Lett. 86, 4922 (2001)]. The experimental observation of one of the states predicted by theory suggests that diagonal stripes could be achieved at other hole densities as well, such as x=1/4, if LCMO membranes with that hole doping were subject to similar strains.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator

Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.

Ham, Sang woo↗
DOE OSTI2022

An agent-based deployment decision-support system for electric vehicle services

METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.

Lei, Zengxiang↗
DOE OSTI2025

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗
DOE OSTI2023

Evaluation of the first version of the new RFPI system dedicated to PIP-II project accelerator

The Low-Level Radio Frequency (LLRF) control system is one of the most critical superconducting linac infrastructures responsible for the parameters of the beam acceleration. The LLRF system mainly focuses on the electromagnetic field parameters inside the cavity. While it incorporates fast feedback algorithms to optimize energy transfer to the passing particle beam it does not follow other cryomodule or cavity parameter changes. The Radio Frequency Protection Interlock (RFPI) system closely monitors various factors (like cryomodule vacuum, beamline vacuum, field emission probe current level, temperature, RF signal leakage, etc). Its simple but reliable logic has to provide an instant decision about the LLRF system or high-power amplifier output signal blocking in case of safety region excitation. This contribution presents a new version of the RFPI system which logic is implemented in the FPGA chip. The initial work on the prototype of the new system design resulted in the PoC (Proof of Concept) device. The PoC offers the possibility of various protection logic configurations, input signals parameters evaluation, and modularity aspects verification. The structure and test results from the device evaluation are summarized and discussed in this contribution.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Evaluating Thermostats' Deadbands Using HVAC Hardware-In-the-Loop Experiment for Advanced Control Strategies

Smart thermostats have gained significant popularity due to their potential for optimizing energy consumption and enhanced user control while ensuring occupants' comfort. The deadband, also referred to as temperature differential, is defined as the temperature difference between the desired setpoint and upper threshold or lower threshold for the HVAC equipment to turn on. It is a key factor influencing energy efficiency and user satisfaction. This paper presents a comparative analysis of the deadbands of five different smart thermostats, tested with a heat pump, aiming to identify variations in their deadband settings and implications for energy management. The experimental study was conducted using a HVAC hardware-in-theloop (HIL) system that integrates smart thermostats with physical HVAC equipment in a simulated house environment. The study explores the trade-offs between energy efficiency and occupant comfort and highlights how different thermostats participating in demand response event cycle differently based on their deadband settings. The findings offer valuable insights into how selecting the right thermostat or configuring smart thermostat with appropriate deadband settings can be leveraged to enhance demand response capabilities, shift loads effectively and improve operational flexibility in HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

5.1.6 Demo #6: NanoStitch (NAWAStitch) Multifunctional Composites Trade Validation

The overall objective of the NanoStitch Multifunctional Composites Trade Validation Demonstration project was to determine the value proposition of adding NanoStitch to rapid-cure composite systems for structures used in the expanding sector of advanced air mobility (AAM) and specifically electric vertical take-off and landing (eVTOL) aircraft. The expected value proposition was stronger composite parts, with new multifunctional attributes, that are lower cost to fabricate and maintain. NanoStitch is a new composite innovation where a contiguous vertically aligned carbon nanotube (VACNT) forest is located between each ply of a laminate composite resulting in improved mechanical properties as well as other multifunctional properties such as enhanced thermal and electrical conductivity. NanoStitch was originally distributed by N12, later acquired by NAWA Technologies, now called NAWAStitch, and henceforth referred to in this document as NAWAStitch. Two significant evaluations were framed to help meet the overall objective. First, was Task 1 to evaluate the effects that adding NAWAStitch to a rapid cure material system would have on the mechanical and processing properties of the material. Second, was Task 2 to evaluate the workability of adding NAWAStitch to practical flight demonstration articles. From previous research, it was already known that the application of NAWAStitch to a composite structure can enhance the mechanical properties of that structure. However, this project will help the engineering community understand those benefits and the basic structural strength values to apply when incorporating NAWAStitch material into composite structure that utilizes a rapid-cure resin system, which is novel. Testing showed that by adding NAWAStitch to the prepreg, most material properties were improved because the VACNTs strengthened the resin to fiber interface, and the interface itself, between plies. For example compression strength improved by more than 20%, and erosion resistance by more than 50%. The UDRI team identified two flight demonstration articles through discussions with Aurora Flight Sciences (Aurora) and reviewing literature on air mobility and the eVTOL market. The demonstration articles were a thin skin honeycomb panel and a section from an eVTOL propeller blade. The manufacturing and testing trials of the demonstration articles were as follows: • NAWAStitch added no manufacturing complexity or detriment to the article physical qualities, while at the same time added multifunctional properties such as enhanced rain erosion and electrothermal de-icing besides enhanced mechanical properties • VACNTs did not increase or hurt the mechanical properties of the interface between honeycomb core materials and the thin skin face sheet • Demonstrated successful de-icing function in an eVTOL propeller meeting real-world specifications in uniformity and endurance • Multifunctional eVTOL propeller cost analysis showed a cost savings of at least 67 % for a single propeller blade with multifunctional de-icing capability and improved mechanical properties which equates to a potential savings of $10,116 per eVTOL aircraft with six three-bladed propellers Overall, the results of this project can provide additional tools for the composite industry to optimize energy efficiency through faster and stronger composite parts that are lower cost to fabricate and maintain. Additionally, the results of this effort can help US industry like NAWA America set the stage for rapid growth and establishment of a manufacturing facility in Ohio. The project has given NAWA America the basic understanding of how the addition of VACNTs to a composite structure can affect the mechanical properties and hence point them to potential commercial applications. The project has also provided Teijin Carbon US with another potential material application for their rapid cure materials that are manufactured at the Renegade facility in Miamisburg, OH.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Panning for Gold: New Emission Lines from UV–VIS Spectroscopy of Au i and Au ii

The recent detection of a neutron star merger by the LIGO collaboration has renewed interest in laboratory studies of r-process elements. Accurate modeling and interpretation of the electromagnetic transients following the mergers requires computationally expensive calculations of both the structure and opacity of all trans-iron elements. To date, the necessary atomic data to benchmark structure codes are incomplete or, in some cases, absent entirely. Within the available laboratory studies, the literature on Au i and Au ii provides incomplete reports of the emission lines and level structures. We present a new study of Au i and Au ii lines and levels by exposing a solid gold target to plasma in the Compact Toroidal Hybrid (CTH) experiment at Auburn University. A wavelength range from 187 to 800 nm was studied. In Au i, 86 lines are observed, 43 of which are unreported in the literature, and the energies of 18 $5{d}^{9}6s6p$ levels and 16 of the 18 known $5{d}^{9}6s6d$ levels are corroborated by a least-squares level energy optimization. In Au ii, 76 emission lines are observed, and 51 of the lines are unreported in the literature. For both Au i and Au ii, the new lines predominantly originate from the most energetic of the known levels, and over half of the new Au ii lines have wavelengths longer than 300 nm. For the estimated electron parameters of CTH plasmas at the gold target (ne ~ 10 12 cm -3 , T e ~ 10 eV), two-electron transitions are similar in intensity to LS-allowed one-electron transitions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Direct-detection optical communication with color coded pulse position modulation signaling

The performance characteristics of a direct-detection optical communication system which is based on a laser transmitter which produces single light pulses at selected nonoverlapping optical center frequencies are discussed. The signal format, called color coded pulse position modulation (CCPPM), uses more of the total available response bandwidth characteristics of the photodetector than does ordinary PPM signaling. The advantages of CCPPM signaling are obtained at the expense of an increased optical bandwidth of the transmitted signal and a more complicated transmitter and receiver structure. When the signal format is used in conjunction with block length Reed-Solomon codes, high data rates and reliable high-speed optical communications under conditions of optimal energy efficiency are obtained.

Davidson, F.↗