Search NASA⌕ Search

SEARCH · Search NASA

Results for “work function tuning”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular surface programming of rectifying junctions between InAs colloidal quantum dot solids

Heavy-metal-free III–V colloidal quantum dots (CQDs) show promise in optoelectronics: Recent advancements in the synthesis of large-diameter indium arsenide (InAs) CQDs provide access to short-wave infrared (IR) wavelengths for three-dimensional ranging and imaging. In early studies, however, we were unable to achieve a rectifying photodiode using CQDs and molybdenum oxide/polymer hole transport layers, as the shallow valence bandedge (5.0 eV) was misaligned with the ionization potentials of the widely used transport layers. This occurred when increasing CQD diameter to decrease the bandgap below 1.1 eV. Here, we develop a rectifying junction among InAs CQD layers, where we use molecular surface modifiers to tune the energy levels of InAs CQDs electrostatically. Previously developed bifunctional dithiol ligands, established for II-VI and IV-VI CQDs, exhibit slow reaction kinetics with III-V surfaces, causing the exchange to fail. Here, we study carboxylate and thiolate binding groups, united with electron-donating free end groups, that shift upward the valence bandedge of InAs CQDs, producing valence band energies as shallow as 4.8 eV. Photophysical studies combined with density functional theory show that carboxylate-based passivants participate in strong bidentate bridging with both In and As on the CQD surface. The tuned CQD layer incorporated into a photodiode structure achieves improved performance with EQE (external quantum efficiency) of 35% (>1 μm) and dark current density < 400 nA cm -2 , a >25% increase in EQE and >90% reduced dark current density compared to the reference device. This work represents an advance over previous III-V CQD short-wavelength IR photodetectors (EQE < 5%, dark current > 10,000 nA cm -2 ).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strain Programming of Oxygen Octahedral Symmetry in Perovskite Oxide Thin Films

The collective rotations of oxygen octahedra play an important role in determining the physical properties of functional perovskite oxides. The epitaxial strain can serve as an effective means to modify the oxygen octahedral symmetry (OOS), i.e., oxygen octahedral rotation or tilt (OOR/OOT). However, the strain-OOS coupling that may alter the details of the OOS, thereby the physical properties, has not been fully understood. In this work, it is demonstrated that epitaxial strain can not only induce a structural phase transition but also precisely tune the degree of OOR. The correlated metal CaNbO 3 , which is orthorhombic, is studied by growing as epitaxial thin films. By imposing epitaxial strain, it is found that the film undergoes a structural phase transition from orthorhombic to tetragonal upon fully straining (i.e., from a + b − b − to a 0 a 0 c − ). In unstrained films, the octahedral rotation along the c-axis is as large as 15.7° that can be tuned to 6.6° by strain. This finding offers a general approach to manipulating OOR/OOT via strain engineering in complex oxide heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tuning perovskite nanocrystal superlattices for superradiance in the presence of disorder

The cooperative emission of interacting nanocrystals is an exciting topic fueled by recent reports of superfluorescence and superradiance in assemblies of perovskite nanocubes. Several studies estimated that coherent coupling is localized to a small fraction of nanocrystals (10 -7 –10 -3 ) within the assembly, raising questions about the origins of localization and ways to overcome it. In this work, we examine single-excitation superradiance by calculating radiative decays and the distribution of superradiant wave function in two-dimensional CsPbBr 3 nanocube superlattices. The calculations reveal that the energy disorder caused by size distribution and large interparticle separations reduces radiative coupling and leads to the excitation localization, with the energy disorder being the dominant factor. The single-excitation model clearly predicts that, in the pursuit of cooperative effects, having identical nanocubes in the superlattice is more important than achieving a perfect spatial order. The monolayers of large CsPbBr 3 nanocubes (L NC = 10–20 nm) are proposed as model systems for experimental tests of superradiance under conditions of non-negligible size dispersion, while small nanocubes (L NC = 5–10 nm) are preferred for realizing the Dicke state under ideal conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Single pair of Weyl nodes in the spin-canted structure of EuCd 2 As 2

We report time reversal symmetry breaking Weyl semimetals are unique among Weyl materials in allowing the minimal number of Weyl points, thus offering the clearest signatures of the associated physics. Here we present neutron diffraction, density-functional theory, and transport measurement results which indicate that EuCd 2 As 2 , under ambient field, strain, and pressure, is such a material with a single pair of Weyl points. Our work reveals a magnetic structure (magnetic space group C2'/m') with Eu moments pointing along the [210] direction in plane and canted ~ 30° out of plane. Density functional theory calculations using this structure show that the observed canting drastically alters the relevant electronic bands, relative to the in-plane order, leading to a single set of well-defined Weyl points. Furthermore, we find the canting angle can tune the distance of the Weyl points above the Fermi level, with the smallest distance at low canting angles. Finally, transport measurements of the anomalous Hall effect and longitudinal magnetoresistance exhibit properties indicative of a chiral anomaly, thus supporting the neutron scattering and DFT results suggesting EuCd 2 As 2 is close to the ideal situation of the Weyl hydrogen atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Sub-Threshold Low-Power Integrated Bandpass Filter for Highly-Integrated Spectrum Analyzers

Low-power analog filter banks provide frequency analysis with minimal power and space requirements, making them viable solutions for integrated remote audio- and vibration-sensing applications. Compared with their digital counterparts, analog filter banks are better suited to achieve the lower power consumption necessary for IoT applications, while maintaining high dynamic range and a wide operational frequency range. In this work, the design and implementation of a sub-threshold complementary metal-oxide semiconductor (CMOS) integrated low-power tunable analog filter channel for signal spectrum analysis and signal discrimination is presented. Project specifications required a programmable, high-order, monolithic bandpass filter channel with small chip area, low power consumption, high dynamic range, and wide operational frequency range. The 8th-order filter channel presented in this work provides an effective Q-factor of 4.5 and a minimum dynamic range (DR) of approximately 85 dB, while allowing for tuning across a range of center frequencies from 2 kHz to 100 kHz, with power consumption of a single 8th-order filter channel measured at 256 µW nominally at the highest center frequency. An integrated analog Gm-C filter topology was selected for this application. Functionally, the high-Q bandpass filter transfer function is implemented via four cascaded 2nd-order filter cells, resulting in a single 8th-order filter channel, fabricated in 130-nm 1.2-V CMOS technology, suitable for use in monolithic integrated spectral analysis (MISA1) applications.

Long, Gavin B.↗
DOE OSTI2022

Light-induced ferromagnetism in moiré superlattices

Many-body interactions between carriers lie at the heart of correlated physics. The ability to tune such interactions would allow the possibility to access and control complex electronic phase diagrams. Recently, two-dimensional moiré superlattices have emerged as a promising platform for quantum engineering such phenomena. The power of the moiré system lies in the high tunability of its physical parameters by adjusting the layer twist angle, electrical field, moiré carrier filling and interlayer coupling. In this work, we report that optical excitation can highly tune the spin–spin interactions between moiré-trapped carriers, resulting in ferromagnetic order in WS 2 /WSe 2 moiré superlattices. Near the filling factor of v = 1/3 (that is, one hole per three moiré unit cells), as the excitation power at the exciton resonance increases, a well-developed hysteresis loop emerges in the reflective magnetic circular dichroism signal as a function of magnetic field, a hallmark of ferromagnetism. The hysteresis loop persists down to charge neutrality, and its shape evolves as the moiré superlattice is gradually filled, indicating changes of magnetic ground state properties. The observed phenomenon points to a mechanism in which itinerant photoexcited excitons mediate exchange coupling between moiré-trapped holes. This exciton-mediated interaction can be of longer range than direct coupling between moiré-trapped holes, and thus magnetic order arises even in the dilute hole regime. This discovery adds a dynamic tuning knob to the rich many-body Hamiltonian of moiré quantum matter.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM

This work presents a new method for online selection of multiple penalty parameters for the alternating direction method of multipliers (ADMM) algorithm applied to optimization problems with multiple constraints or functions with block matrix components. ADMM is widely used for solving constrained optimization problems in a variety of fields, including signal and image processing. Implementations of ADMM often utilize a single hyperparameter, referred to as the penalty parameter, which needs to be tuned to control the rate of convergence. However, in problems with multiple constraints, ADMM may demonstrate slow convergence regardless of penalty parameter selection due to scale differences between constraints. Accounting for scale differences between constraints to improve convergence in these cases requires introducing a penalty parameter for each constraint. The proposed method is able to adaptively account for differences in scale between constraints, providing robustness with respect to problem transformations and initial selection of penalty parameters. It is also simple to understand and implement. Our numerical experiments demonstrate that the proposed method performs favorably compared to a variety of existing penalty parameter selection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Iterative sampling of expensive simulations for faster deep surrogate training

Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Manipulating Photoconduction in Cu–Pyrene 1-D Coordination Nanosheets by Modulating Interlayer π–π Stacking

2D conductive metal organic frameworks (MOFs) have become promising candidates for applications in electronic and photoelectronic devices. However, the lack of a fundamental understanding of the charge transport mechanism and synthetic design to alter their conductivity limits their potential applications. In this work, we report the design and synthesis of two 1D Cu–pyrene coordination nanosheets, Cu–pyrene-4,5,9,10 tetrathiol (Cu-PTT) and Cu–2,7-di-tert-butylpyrene-4,5,9,10-tetrathiol (Cu– tBu PTT), as models of 2D conductive MOFs, where the introduction of two different functional groups (H and tert-butyl groups) at the 2 and 7 positions of the PTT ligands is used to tune the interlayer distance and π–π stacking of MOFs. Using optical pump terahertz probe spectroscopy, we show that both nanosheets exhibit appreciable photoconduction, but the photoconduction in Cu– tBu PTT is reduced with respect to that in Cu–PTT, which can be attributed to the larger interlayer distance in the former leading to the decoupling of the interlayer charge transport pathway. Furthermore, these results demonstrate a unique strategy to investigate the impact of out-of-plane extended conjugation on photoconduction in conductive conjugated polymers, MOFs, or coordination nanosheets through adjusting their interlayer spacing.

14 SOLAR ENERGY↗
DOE OSTI2021

Conjugation- and Aggregation-Directed Design of Covalent Organic Frameworks as White-Light-Emitting Diodes

2D covalent organic frameworks (COFs) have emerged as a promising class of organic luminescent materials due to their structural diversity, which allows the systematic tuning of organic building blocks to optimize emitting properties. However, a significant knowledge gap exists between the design strategy and the fundamental understanding of the key structural parameters that determine their photophysical properties. Here, in this work, we report two highly emissive sp 2 -C-COFs and the direct correlation of the structure (conjugation and aggregation) with their light absorption/emission, charge transfer (CT), and exciton dynamics, the key properties that determine their function as luminescent materials. We show that white light can be obtained by simply coating COFs on an LED strip or mixing the two COFs. Using the combination of time-resolved absorption and emission spectroscopy as well as computational prediction, we show that the planarity, conjugation, orientation of the dipole moment, and interlayer aggregation not only determine the light-harvesting ability of COFs but also control the exciton relaxation pathway and photoluminescent quantum yield.

14 SOLAR ENERGY↗
DOE OSTI2024

Hierarchical Ion Interactions in the Direct Air Capture of CO 2 at Air/Aqueous Interfaces

The direct air capture (DAC) of CO 2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly - ), an effective CO 2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly - and captured carbonaceous anions (HCO 3 - , CO 3 2 -, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Novel Functional Thermal Energy Storage Materials for Buildings Applications

The leakage of solid-liquid phase change materials (PCMs) tremendously limits their long-term application in thermal energy storage (TES). In this work, we present durable and form-stable shape-stabilized PCMs (ss-PCMs) for TES in building envelopes. These ss-PCMs are fabricated by encapsulating polyethylene glycol (PEG) consisting of different molecular weights within mesoporous magnesium oxide and silica dioxide. For the first time, the phase transition temperature (Tt) of ss-PCMs has been fine-tuned synthetically to be comfortable to building occupants by utilizing PEG blends with molecular weights of 600 and 800 g/mol. Several parameters, including surface hydrophilicity/hydrophobicity, surface area, and PCM loading percentage, have been studied to maximize the latent heat enthalpy for high energy efficiency and maintain form stability. The best ss-PCM candidate with suitable Tt and appreciable latent heat enthalpy exhibits a repeatable phase change behavior for up to 1,000 thermal cycles without leakage, which provides a promising solution for durable TES in buildings. The Tt tunability extends its application over a wider temperature range beyond buildings.

building envelope↗
DOE OSTI2023

Technical Report on Waveform Fit Metrics for Global Models

The new WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes an increased emphasis on the development of Earth models and methods to predict entire seismic and acoustic waveforms more accurately. In general, this increased emphasis is predicated on the need to better characterize seismic events and provide improved model-based discrimination between event types including earthquakes and explosions. More specifically, while current moment tensor inversion methods tend to work well for larger events (M>~4) using tuned 1-D Earth models, the development of state-of-the-art 3-D models and methods is required for the prediction of shorter period waves over large areas for discrimination of smaller events. There is no standard metric for model-based waveform prediction accuracy used in the waveform modeling/inversion community. However, there are several popular waveform misfit definitions; and minimizing the corresponding objective functions is the goal of waveform inversion. Some example misfit definitions employed for adjoint waveform tomography include measures of simple travel time differences (e.g. Tape et al., 2010), cross-correlation travel time differences (e.g. Luo and Schuster, 1991), multi-taper frequency dependent methods (e.g. Lei et al., 2020), time-frequency phase misfit functions (e.g. Fichtner 2010; Rodgers et al., 2022), normalized cross-correlation methods (e.g. Tao et al., 2018), and others. In some cases, these misfit definitions also involve complicated weighting schemes and summations over multiple frequency bands making it difficult to duplicate the misfit measurement with alternative models and datasets. Although each of the misfit definitions mentioned above are useful for developing waveform models, the actual misfit values are not usually meaningful outside of a given project, model, and/or dataset. Therefore, it is difficult to understand and communicate model performance for predicting waveforms and comparing to other models and/or new model iterations with a different dataset. Therefore, there is a need for a generalized method for evaluating overall model performance that is independent from the specific misfit chosen to develop the waveform models that is also intuitive and meaningful. In this report, we describe a new metric we refer to as ‘Percent of Correlated Signal’. The following sections describe and demonstrate the metric with a case study event and a more rigorous test using a random selection of globally distributed events. While the focus here is on global tomography models, the metric is meant to applicable to regional ‘wiggle-for-wiggle’ waveform models/studies as well.

58 GEOSCIENCES↗
DOE OSTI2021

Artificial Judgement Assistance from teXt (AJAX): Applying Open Domain Question Answering to Nuclear Non-proliferation Analysis

Nuclear non-proliferation analysis is complex and subjective, as the data is sparse, and examples are rare and diverse. While analysing non-proliferation data, it is often desired that the findings be completely auditable such that any claim or assertion can be sourced directly to the reference material from which it was derived. Currently this is accomplished by analysts thoroughly documenting underlying assumptions and clearly referencing details to source documents. This is a labour-intensive and time-consuming process that can be difficult to scale with geometrically increasing quantities of data. In this work, we describe an approach to leverage bi-directional language models for nuclear non-proliferation analysis. It has been shown recently that these models not only capture language syntax but also some of the relational knowledge present in the training data. We have devised a unique Salt and Pepper strategy for testing the knowledge present in the language models, while also introducing auditability function in our pipeline. We demonstrate that fine-tuning the bi-directional language models on domain specific corpus improves their ability to answer domain-specific factoid questions. Our hope is that the results presented in this paper will further the natural language processing (NLP) field by introducing the ability to audit the answers provided by the language models to bring forward the source of said knowledge.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Tunable magnetic order in low-symmetry SeO 3 ligand linked TM 3 (SeO 3 ) 3 H 2 O ( TM =Mn , Co, and Ni) compounds

The ability to design crystal lattices with specific sublattice geometries has long been sought after especially in the context of harnessing magnetic frustration to elicit emergent physics. One approach which has seen some success recently is to design magnetic sublattices chemically through the use of nonmagnetic linker ligands as scaffolding for the magnetic ions. In this work we report the magnetic properties of one such family of materials, the transition metal (TM) selenite hydrates with chemical formula TM 3 (SeO 3 ) 3 H 2 O. These materials link highly distorted TMO 6 octahedra via nonmagnetic [SeO 3 ] 2+ linkers. Studying members with TM = Mn, Co, and Ni we use magnetic susceptibility and neutron powder diffraction to identify antiferromagnetic order in all three compounds with moderate frustration indexes. A comparison of the magnetic structures suggests that while the overall structure of the SeO 3 scaffolding remains unchanged the TM effects changes in the magnetic properties through tuning the internal bonding parameters and the single-ion physics. Changing from Mn to Co is found to be particularly consequential manifesting changes in both the ordered-moment direction and in the direction of the ordering vector. Field-dependent measurements of the susceptibility and heat capacity reveal metamagnetic transitions in both Mn 3 (SeO 3 ) 3 H 2 O and Co 3 (SeO 3 ) 3 H 2 O indicating nearby magnetic ground states accessible under relatively small applied fields. Density functional theory calculations broadly confirm these results, showing both a sensitivity of the magnetic structure to the TM and its local environment. Although no spin liquid behavior is achieved, these results suggest the fruitfulness of such synthesis philosophies and encourage future work to engender higher frustration in these materials via doping, field, pressure, or larger linker ligands.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Additive‐Free Aqueous MXene Inks for Thermal Inkjet Printing on Textiles

Abstract Direct printing of functional inks onto flexible substrates allows for scalable fabrication of wearable electronics. However, existing ink formulations for inkjet printing require toxic solvents and additives, which make device fabrication more complex, limit substrate compatibility, and hinder device performance. Even water‐based carbon or metal nanoparticle inks require supplemental surfactants, binders, and cosolvents to produce jettable colloidal suspensions. Here, a general approach is demonstrated for formulating conductive inkjet printable, additive‐free aqueous Ti 3 C 2 T x MXene inks for direct printing on various substrates. The rheological properties of the MXene inks are tuned by controlling the Ti 3 C 2 T x flake size and concentration. Ti 3 C 2 T x ‐based electrical conduits and microsupercapacitors (MSCs) are printed on textile and paper substrates by optimizing the nozzle geometry for high‐resolution inkjet printing. The chemical stability and electrical properties of the printed devices are also studied after storing the devices for six months under ambient conditions. Current collector‐free, textile‐based MSCs show areal capacitance values up to 294 mF cm −2 (2 mV s −1 ) in poly(vinyl alcohol)/sulfuric acid gel electrolyte, surpassing reported printed MXene‐based MSCs and inkjet‐printed MSCs using other 2D nanomaterials. This work is an important step toward increasing the functional capacity of conductive inks and simplifying the fabrication of wearable textile‐based electronics.

Uzun, Simge↗
DOE OSTI2022

Synergistic Electrocatalytic Syngas Production from Carbon Dioxide by Bi‐Metallic Atomically Dispersed Catalysts

Abstract The production of syngas by traditional processes such as steam methane reforming is energetically intensive and produces a large amount of CO 2 emissions. In contrast, the electrochemical CO 2 reduction reaction (CO 2 RR) enables the carbon neutral production of syngas at ambient conditions. Among non‐precious metal catalysts, metal‐nitrogen‐carbon electrocatalysts are inexpensive and highly selective towards syngas production. This study examined the selectivity of mono‐ and bi‐metallic (M−N−C, M=Fe, Mo or FeMo) electrocatalysts towards syngas production. The ratio of the CO : H 2 in the syngas was tuned by modifying the ratio of the metallic precursors in the bi‐metallic FeMo−N−C catalysts, tailoring the catalysts’ selectivity towards the CO 2 RR or the hydrogen evolution reaction (HER). The catalyst synthesis temperature(s) were considered as they influence the catalyst morphology and activity. Further, the dependence of the ratio of CO : H 2 in the syngas as a function of the potential was explored for the different bi‐metallic catalysts. This work showed that by tailoring both the ratio of Fe : Mo in the bi‐metallic catalyst and optimizing the reductive potential, a CO : H 2 ratio between 0.25 to 5 was achievable. This study demonstrated a novel approach in which the ratio of the product syngas composition could be tailored in a single reaction, without the need for further downstream processing to reach a desired composition.

Delafontaine, Laurent↗
DOE OSTI2020

Autotuning of Double-Dot Devices In Situ with Machine Learning

The current practice of manually tuning quantum dots (QDs) for qubit operation is a relatively time-consuming procedure that is inherently impractical for scaling up and applications. In this work, we report on the in situ implementation of a recently proposed autotuning protocol that combines machine learning (ML) with an optimization routine to navigate the parameter space. In particular, we show that a ML algorithm trained using exclusively simulated data to quantitatively classify the state of a double-QD device can be used to replace human heuristics in the tuning of gate voltages in real devices. Here, we demonstrate active feedback of a functional double-dot device operated at millikelvin temperatures and discuss success rates as a function of the initial conditions and the device performance. Modifications to the training network, fitness function, and optimizer are discussed as a path toward further improvement in the success rate when starting both near and far detuned from the target double-dot range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗