Search NASA⌕ Search

SEARCH · Search NASA

Results for “channel capacity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Deep Learning for Spectral Filling in Radio Frequency Applications

Due to the Internet of Things (IoT) proliferation, Radio Frequency (RF) channels are increasingly congested with new kinds of devices, which carry unique and diverse communication needs. This poses complex challenges in modern digital communications, and calls for the development of technological innovations that (i) optimize capacity (bitrate) in limited bandwidth environments, (ii) integrate cooperatively with already-deployed RF protocols, and (iii) are adaptive to the ever-changing demands in modern digital communications. In this paper we present methods for applying deep neural networks for spectral filling. Given an RF channel transmitting digital messages with a pre-established modulation scheme, we automatically learn novel modulation schemes for sending extra information, in the form of additional messages, “around” the fixed-modulation signals (i.e., without interfering with them). In so doing, we effectively increase channel capacity without increasing bandwidth. We further demonstrate the ability to generate signals that closely resemble the original modulations, such that the presence of extra messages is undetectable to third-party listeners. We present three computational experiments demonstrating the efficacy of our methods, and conclude by discussing the implications of our results for modern RF applications.

Setzler, Matthew D.↗
DOE OSTI2024

Moderate active Fe 3+ doping enables improved cationic and anionic redox reactions for wide-voltage-range sodium storage

Layered metal oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical specific capacity and wide Na + diffusion channels. However, the irreversible phase transitions and cationic/anionic redoxes cause fast capacity decay. Herein, P2-type Na 0.67 Mg 0.1 Mn 0.8 Fe 0.1 O 2 (NMMF-1) cathode material with moderate active Fe 3+ doping has been designed for sodium storage. Uneven Mn 3+ /Mn 4+ distribution is observed in NMMF-1 and the introduction of Fe 3+ is beneficial for reducing the Mn 3+ contents both at the surface and in the bulk to alleviate the Jahn–Teller effect. The moderate Fe 3+ /Fe 4+ redox can realize the best tradeoff between capacity and cyclability. Therefore, the NMMF-1 demonstrates a high capacity (174.7 mAh g -1 at 20 mA g -1 ) and improved cyclability (78.5% over 100 cycles) in a wide-voltage range of 1.5–4.5 V (vs. Na + /Na). In-situ X-ray diffraction reveals a complete solid-solution reaction with a small volume change of 1.7% during charge/discharge processes and the charge compensation is disclosed in detail. This study will provide new insights into designing high-capacity and stable layered oxide cathode materials for SIBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Efficiently Computable Limits on EPR Pair Generation in Quantum Broadcast Channels

We investigate the generation of EPR pairs between three observers in a general causally structured setting, where communication occurs via a noisy quantum broadcast channel. The most general quantum codes for this setup take the form of tripartite quantum channels. Since the receivers are constrained by causal ordering, additional temporal relationships naturally emerge between the parties. These causal constraints enforce intrinsic no-signalling conditions on any tripartite operation, ensuring that it constitutes a physically realizable quantum code for a quantum broadcast channel. We analyze these constraints and, more broadly, characterize the most general quantum codes for communication over such channels. We examine the capabilities of codes that are fully no-signalling among the three parties, positive partial transpose (PPT)-preserving, or both, and derive simple semidefinite programs to compute the achievable entanglement fidelity. We then establish a hierarchy of semidefinite programming converse bounds -- both weak and strong -- for the capacity of quantum broadcast channels for EPR pair generation, in both one-shot and asymptotic regimes. Notably, in the special case of a point-to-point channel, our strong converse bound recovers and strengthens existing results. Finally, we demonstrate how the PPT-preserving codes we develop can be leveraged to construct PPT-preserving entanglement combing schemes, and vice versa.

FOS: Physical sciences↗
DOE OSTI2026

Capacities of Entanglement Distribution From a Central Source

Distribution of entanglement is an essential task in quantum information processing and the realization of quantum networks. In our work, we theoretically investigate the scenario where a central source prepares an N -partite entangled state and transmits each entangled subsystem to one of N receivers through noisy quantum channels. The receivers are then able to perform local operations assisted by unlimited classical communication to distill target entangled states from the noisy channel output. In this operational context, we define the EPR distribution capacity and the GHZ distribution capacity of a quantum channel as the largest rates at which Einstein-Podolsky-Rosen (EPR) states and Greenberger-Horne-Zeilinger (GHZ) states can be faithfully distributed through the channel, respectively. We establish lower and upper bounds on the EPR distribution capacity by connecting it with the task of assisted entanglement distillation. We also construct an explicit protocol consisting of a combination of a quantum communication code and a classical-post-processing-assisted entanglement generation code, which yields a simple achievable lower bound for generic channels. As applications of these results, we give an exact expression for the EPR distribution capacity over two erasure channels and bounds on the EPR distribution capacity over two generalized amplitude damping channels. We also bound the GHZ distribution capacity, which results in an exact characterization of the GHZ distribution capacity when the most noisy channel is a dephasing channel.

42 ENGINEERING↗
DOE OSTI2023

Decoupling Accurate Electrochemical Behaviors for High-Capacity Electrodes via Reviving Three-Electrode Vehicles

Developing high-capacity electrodes requires the evaluation of electrochemical behaviors with an increasing current density. Currently, the current density for evaluation of high-capacity electrodes has reached a new stage where the polarization at the lithium counter electrode has become a technical barrier for the accurate evaluation of battery electrodes, resulting in severe performance and mechanism mischaracterizations. Here, the accurate electrochemical behavior for high-capacity electrodes via a single-channel three-electrode vehicle is decoupled, by which the impact of lithium counter electrode is minimized. The testing high-capacity graphite electrode is capable of delivering an excellent rate capability with 81.7% capacity retention at 0.3 C, as well as stable cycling performance retaining 97.5% practical reversible capacity after 225 cycles, much higher than the graphite electrode tested with traditional half-cell testing vehicle but in close agreement with the results obtained from a well-matched full cell, reflecting accurate electrochemical performance evaluations of high-capacity electrodes. Moreover, detailed electrochemical mechanisms of impedance and diffusion properties for working electrodes are also successfully decoupled individually. Here, this work uncovers the mismatch between traditional evaluation configuration and increasing testing current density and provides a guideline for accurate electrochemical evaluation for ever-increasing high-capacity electrodes, which is of great significance for high-energy lithium or other alkali-metal ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Quantum capacities of transducers

Abstract High-performance quantum transducers, which faithfully convert quantum information between disparate physical carriers, are essential in quantum science and technology. Different figures of merit, including efficiency, bandwidth, and added noise, are typically used to characterize the transducers’ ability to transfer quantum information. Here we utilize quantum capacity, the highest achievable qubit communication rate through a channel, to define a single metric that unifies various criteria of a desirable transducer. Using the continuous-time quantum capacities of bosonic pure-loss channels as benchmarks, we investigate the optimal designs of generic quantum transduction schemes implemented by transmitting external signals through a coupled bosonic chain. With physical constraints on the maximal coupling rate $${g}_{\max }$$ g max , the highest continuous-time quantum capacity $${Q}^{\max }\approx 31.4{g}_{\max }$$ Q max ≈ 31.4 g max is achieved by transducers with a maximally flat conversion frequency response, analogous to Butterworth electric filters. We further investigate the effect of thermal noise on the performance of transducers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Modeling the cooldown of cryocooler conduction-cooled devices

Cryocooler conduction cooled devices can experience significant cooldown time due to lower available cooling capacity compares to convection cooled devices. Therefore, the cooldown time is an important design parameter for conduction cooled devices. This article introduces a framework developed in Python for calculating the cooldown profiles and cooldown time of cryocooler conduction-cooled devices such as superconducting magnets and accelerator cavities. The cooldown time estimation problem is essentially a system of ordinary first-order differential equations comprising the material properties (temperature dependent thermal conductivity and specific heat capacity) of the components intertwined with the prevailing heat transfer channels (conduction, radiation, and heat flow across pressed contacts) and the cryocooler capacity. The formulation of this ODE system is first presented. This ODE system is then solved using the in-built Python library odeint. A case study is presented comprising a small cryocooler conduction-cooled copper stabilized niobium-titanium magnet. The case study is supplemented with the Python script enabling the reader to simply tweak the device design parameters and optimize the design from the point of view of slow/fast cooldown.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Tuning the Chern number in quantum anomalous Hall insulators

A quantum anomalous Hall (QAH) state is a two-dimensional topological insulating state that has a quantized Hall resistance of h/(Ce 2 ) and vanishing longitudinal resistance under zero magnetic field (where h is the Planck constant, e is the elementary charge, and the Chern number C is an integer). The QAH effect has been realized in magnetic topological insulators and magic-angle twisted bilayer graphene. However, the QAH effect at zero magnetic field has so far been realized only for C = 1. Here we realize a well quantized QAH effect with tunable Chern number (up to C = 5) in multilayer structures consisting of alternating magnetic and undoped topological insulator layers, fabricated using molecular beam epitaxy. The Chern number of these QAH insulators is determined by the number of undoped topological insulator layers in the multilayer structure. Moreover, we demonstrate that the Chern number of a given multilayer structure can be tuned by varying either the magnetic doping concentration in the magnetic topological insulator layers or the thickness of the interior magnetic topological insulator layer. We develop a theoretical model to explain our experimental observations and establish phase diagrams for QAH insulators with high, tunable Chern number. Furthermore, the realization of such insulators facilitates the application of dissipationless chiral edge currents in energy-efficient electronic devices, and opens up opportunities for developing multi-channel quantum computing and higher-capacity chiral circuit interconnects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Achievable Rates for Concatenated Square Gottesman-Kitaev-Preskill Codes

The Gottesman-Kitaev-Preskill (GKP) codes are known to achieve optimal rates under displacement noise and pure-loss channels, which establishes theoretical foundations for its optimality. However, such optimal rates are only known to be achieved at a discrete set of noise strengths with the current self-dual symplectic lattice construction. In this work, we develop a new coding strategy using concatenated continuous variable-discrete variable encodings to go beyond past results and establish GKP’s optimal rate over all noise strengths. In particular, for displacement noise, the rate is obtained through a constructive approach by concatenating GKP codes with a quantum polar code and analog decoding. For a pure-loss channel, we prove the existence of capacity-achieving GKP codes through a random coding approach. These results highlight the capability of concatenation-based GKP codes and provides new methods for constructing good GKP lattices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Fetch-trap Pairs: Exploring definition of carbon storage prospects to increase capacity and flexibility in areas with competing uses

As CCS grows beyond isolated first-mover projects, the question of how to identify potential storage sites (prospects) is key to siting projects amidst the constraints of neighboring storage projects, hydrocarbon fields and other considerations. To date, prospects have been defined either by the extent of a buoyant trap or by the predicted maximum extent of the CO 2 or pressure plume. Both approaches have worked, but they may struggle in places like the Gulf of Mexico where complex geologic structure can invalidate simple assumptions of radial plume spread and buoyant traps are commonly unattractive due to numerous legacy well penetrations. Here, we propose identifying prospective storage sites by fetch area (drainage cell) rather than by buoyant closure alone. Doing so offers 1) greater freedom in siting injectors to avoid surface and subsurface constraints, including legacy wells that tend to cluster on structural high; and 2) a coherent flow regime in which buoyancy drives all injected CO 2 toward a common high. This strategy gives space to dissipate injection pressure and minimize the number of legacy wells needing review. It may also offer 1) better injectivity by bringing synclines and associated channel axes into play; and 2) potentially improved capacity by tapping a larger rock volume and taking advantage of migration losses.

58 GEOSCIENCES↗
DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗
DOE OSTI2024

High Current Density Diamond Photoconductive Semiconductor Switches With a Buried, Metallic Conductive Channel

Laterally configured diamond photoconductive semiconductor switches (PCSS) with a buried, metallic p+ current channel are reported. Above bandgap ( λ ≤ 226 nm) optical triggering enables responsivity of over 130 mA/W. The use of low-impurity semi-insulating diamond as an active absorption layer enables fast rise and fall times (~2 ns) and on/off ratios greater than 10 11 . The PCSS excited with a laser energy of 20 nJ per pulse passes a high current density (44 A/cm) under a DC bias of 60 V, thanks to the buried metallic p+ current channel. The reported devices promise high current carrying capacity without the need for filamenting while leveraging the excellent optical, electronic, and thermal properties of diamond.

42 ENGINEERING↗
DOE OSTI2020

Enabling fast charging of lithium-ion batteries through secondary- /dual- pore network: Part I - Analytical diffusion model

Battery performance is strongly correlated with electrode microstructural properties. Enabling fast charging of lithium-ion batteries requires improved through-plane ionic diffusion that can be achieved through, among other strategies, structured electrodes with a secondary- or dual-pore network (SPN). In this work, an analytical model investigates the impact of such an SPN on ionic diffusion with a composite electrode, considering various pore-channel geometries and comparing to standard electrodes with identical gravimetric- and volumetric-specific theoretical capacities. Relevant SPN design parameters and tortuosity coefficients are identified according to three optimization objectives that aim to balance the improved overall through-plane diffusion, thanks to the coarse aligned channels, and degraded in-plane diffusion because of the porous matrix densification required to maintain gravimetric- and volumetric-specific theoretical capacities. The model indicates that a relatively low amount of SPN is required and that electrodes with high through-plane tortuosity and low in-plane tortuosity benefit most from such architecture.

25 ENERGY STORAGE↗
DOE OSTI2020

Elastic NaxMoS2-carbon-BASE triple interface direct robust solid-solid interface for all-solid-state Na-S batteries

The promises of all-solid-state (ASS) sodium batteries for the next generation energy storage are widely recognized but their developments have been severely constrained by the difficulties to design favorable solid-solid interfaces for unhindered Na-ion transport. Using the most promising ß?-Al2O3 solid state electrolyte (BASE) as a platform, we demonstrate here a triple nanojunction strategy that provides simultaneous strong Na adhesion and continuous Na-ions diffusion at solid-solid interface. Such triple junctions (NaxMoS2-carbon-BASE) were constructed by adhering ternary composite Na anodes containing dispersed 3 wt% MoS2 and 3 wt% carbon on BASE, and provide nearly complete adhesion of Na on BASE with a much smaller contact angle (~ 45o vs. 120o of pristine Na). The composite Na anodes exhibited ~ 3 times improved elastic property and the synergy of NaxMoS2 and carbon provides the required ionic and electronic diffusion channels at solid-solid interface, which significantly improve Na utilization and resist premature failure due to loss of solid-solid contact as Na shrink during high capacity stripping. As a result, Na metal at the triple junction exhibited more than five time reduced charge transfer resistance and at least 200 hours stable battery cycling at practical current densities. The novel anode architecture also enabled high capacity cycling of prototype ASS sodium sulfur batteries when coupled with advanced sulfur cathodes containing intrinsic Na-ions diffusion channels and redox catalytic mediators, leading to stable cycling with specific capacity of 1110 mAh g-1.

ß”-Al2O3 solid electrolyte, solid state batteries,↗
DOE OSTI2020

A Strategy for Constructing Pore-Space-Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Introduction of pore partition agents into hexagonal channels of MIL-88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4, 4'-dipyridylsulfide (dps) ligands. As a result, one third of open metal sites in the parent acs net are retained in pacs MOFs, while two thirds are used for pore space partition. The newly synthesized Co 2 V-pacs MOFs, with optimized pore space and open metal sites, exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. For example, the storage capacity of C 2 H 2 is 234 cm 3 /g -1 (298 K) and 330 cm 3 /g -1 (273K) at 1 atm for CPM-733-dps (the Co 2 V-BDC form, BDC=1,4-benzenedicarboxylate), higher than benchmark MOFs such as MOF-74 and all other pacs members. These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low-energy-cost adsorbent regeneration. CPM-733-dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

25 ENERGY STORAGE↗
DOE OSTI2023

The Mechanism of Fluorine Doping for the Enhanced Lithium Storage Behavior in Cation-Disordered Cathode Oxide

Li-rich cation-disordered rock-salt (DRX) materials have emerged as promising candidates for high-capacity oxide cathodes. Their fluorinated variants have shown improved cycling stability with effectively suppressed oxygen loss. However, a comprehensive understanding of how fluorination impacts the multiscale structure and lithium transportation in DRX remains elusive in experiments. In this study, the neutron total scattering technique in conjunction with the advanced reverse Monte Carlo (RMC) fitting method is employed to characterize the intricate structure of Li 1.16 Ti 0.37 Ni 0.37 Nb 0.1 O 2 (LTNNO) and the fluorinated Li 1.2 Ti 0.35 Ni 0.35 Nb 0.1 O 1.8 F 0.2 (LTNNOF). Through rigorous statistical analysis, the multiscale structural evolution upon fluorination is quantified from atomic (≤5 Å) to long-range scale (≈100 Å). The local Li-rich environments around F induce a modest 2.4% increment in the number of fast Li 0TM (transition metal) channels. Crucially, at a broader scale, the proportion of 0TM channels participating in percolation increases significantly from 2.9% in LTNNO to 8.7% in LTNNOF. Fluorination improves the capacity release mainly through merging isolated fast Li channels into the percolation network. This work experimentally unravels the multiscale mechanism of fluorination-induced performance improvement in DRX materials and highlights the necessity of adopting an advanced RMC fitting method to obtain a full view of the complex structural features in developing high-capacity DRX cathodes.

25 ENERGY STORAGE↗
DOE OSTI2020

CP-DSSS: A Novel Waveform for Multiple Access in IoT

Cyclic prefix direct sequence spread spectrum (CPDSSS) is a novel waveform with versatile characteristics that positions itself well as a secondary network to relieve the congested wireless spectrum. The underlying structure of CPDSSS allows for efficient and effective multi-access capabilites through frequency and time division schemes in a given system. The sum-rate capacity of the system is maximized when the spectrum is divided and allocated to users with the best signal-to-noise (SNR) ratio for the given channel slice. We propose an algorithm for dividing and allocating portions of the spectrum to multiple users with the final goal of maximizing the sumrate capacity of the network. We also propose and develop a precoding/equalization technique that reduces the length of the channel impulse response. This, when used along with a matched filter detector, leads to some improvement in the sum-rate capacity of the network

5G and Beyond Communications↗