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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Initial operation of high power ICRF system for long pulse in EAST

The ICRF heating system on EAST upgraded by active cooling aims for long pulse operation. In this paper, the main technical features of the ICRF system are described. One of a major challenges for long pulse operation is RF-edge interactions induced impurity production and heat loading. In EAST, ICRF antenna protections and Faraday screen bars damaged due to LH electron beam are found. Preliminary results for the analysis of the interaction between LHCD and ICRF antenna are discussed. Increase of metal impurities in the plasma during RF pulse and in a larger core radiation are also shown. These RF-edge interactions at EAST and some preliminary results for the optimizing RF performance will be presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Controlling the conduction band offset for highly efficient ZnO nanorods based perovskite solar cell

The mechanism of charge recombination at the interface of n-type electron transport layer (n-ETL) and perovskite absorber on the carrier properties in the perovskite solar cell is theoretically studied. By solving the one dimensional diffusion equation with different boundary conditions, it reveals that the interface charge recombination in the perovskite solar cell can be suppressed by adjusting the conduction band offset (ΔE{sub C}) at ZnO ETL/perovskite absorber interface, thus leading to improvements in cell performance. Furthermore, Mg doped ZnO nanorods ETL has been designed to control the energy band levels. By optimizing the doping amount of Mg, the conduction band minimum of the Mg doped ZnO ETL has been raised up by 0.29 eV and a positive ΔE{sub C} of about 0.1 eV is obtained. The photovoltage of the cell is thus significantly increased due to the relatively low charge recombination.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Proton Induced Modulation of ICT and PET Processes in an Imidazo-phenanthroline Based BODIPY Fluorophores

BODIPY fluorophores linked with an imidazo-phenanthroline donor at α and β positions have been synthesized. Intriguing intramolecular charge transfer phenomenon is observed in both the dyes which has been extensively investigated using UV–vis absorption, steady-state and time-resolved fluorescence measurements. H-bonding and intrinsic polarity of the solvents has modulated the absorption and emission bands of these fluorophores strongly causing significant increase in the Stokes shifts. In spite of having difference only in terms of the position of donor subunit, the photophysics of these dyes are not only significantly different from each other, but contradictory too. Interestingly, acidochromic studies revealed the shuttling mechanism between ICT and PET processes for BDP 2. Quantum chemical calculations have been employed further to support experimental findings. DFT and TD-DFT method of analysis have been used to optimize ground and excited state geometries of the synthesized dyes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Determining and Controlling the Stoichiometry of Cu 2 ZnSnS 4 Photovoltaics: The Physics and Its Implications

Cu 2 ZnSnS 4 (CZTS) is an environmentally friendly photovoltaic material with promising applications in thin-film solar cells. Although CZTS’s efficiency is currently too low, stoichiometry/defect engineering presents a strategy for further improvement. As-grown CZTS is typically disordered and therefore prone to form secondary phases, making the final product stoichiometry difficult to determine and even harder to control. In this work, we use first-principles quantum mechanics in combination with Monte Carlo simulations to determine CZTS stoichiometry under various experimental conditions. We develop an approach to predicting the optimal CZTS stoichiometry, explaining the physical origin of Zn-enrichment observed in experiments. We further propose practical ways to introduce more free carriers into CZTS in order to screen observed local potential fluctuations, increase conductivity, and ultimately improve the efficiency of CZTS.

14 SOLAR ENERGY↗
DOE OSTI2025

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Encumbering the Copper(I)-Diimine Coordination Sphere with a Benzyl Group: Impact on the Stability and Photoredox Properties

Copper(I)-bisdiimine complexes, [Cu(NN) 2 ] + (where NN represents a diimine such as phenanthroline or bipyridine derivatives), are considered promising photosensitizers for various photochemical applications. However, their effectiveness is subject to several key challenges. In particular, controlling steric strain around the copper(I) center by introducing appropriate substituents (R) at the α-position of the nitrogen atoms is crucial for optimizing the excited-state properties of the complex. In brief, increasing the size of R leads to longer emission lifetimes and higher quantum yields. Additionally, the energy of the singlet excited state rises with increasing steric bulk, enhancing photoinduced reactivity. However, excessive steric strain from bulky substituents can significantly destabilize the coordination sphere. To balance complex stability with increased steric bulk around the metal center, we have developed two novel non-symmetrical ligands featuring branched alkyl chains and benzyl groups at the α-position of the nitrogen atoms. Here, our findings demonstrate that intramolecular π-stacking interactions between the benzyl group and the opposing phenanthroline ligand contribute to stabilizing the coordination sphere. Furthermore, the flexibility of the benzyl group reinforces the tetrahedral geometry around copper(I), resulting in an increased singlet excitedstate energy compared to benchmark complexes. Notably, we show that this enhancement in excited-state energy translates into greater excited-state reactivity.

Copper(I)↗
DOE OSTI2017

Perfluoropolyethers: Development of an All-Atom Force Field for Molecular Simulations and Validation with New Experimental Vapor Pressures and Liquid Densities

A force field for perfluoropolyethers (PFPEs) based on the general optimized potentials for liquid simulations all-atom (OPLS-AA) force field has been derived in conjunction with experiments and ab initio quantum mechanical calculations. Vapor pressures and densities of two liquid PFPEs, perfluorodiglyme (CF 3 –O–(CF 2 –CF 2 –O)2–CF 3 ) and perfluorotriglyme (CF 3 –O–(CF 2 –CF 2 –O) 3 –CF 3 ), have been measured experimentally to validate the force field and increase our understanding of the physical properties of PFPEs. Force field parameters build upon those for related molecules (e.g., ethers and perfluoroalkanes) in the OPLS-AA force field, with new parameters introduced for interactions specific to PFPEs. Molecular dynamics simulations using the new force field demonstrate excellent agreement with ab initio calculations at the RHF/6-31G* level for gas-phase torsional energies (<0.5 kcal mol –1 error) and molecular structures for several PFPEs, and also accurately reproduce experimentally determined densities (<0.02 g cm –3 error) and enthalpies of vaporization derived from experimental vapor pressures (<0.3 kcal mol–1). Additional comparisons between experiment and simulation show that polyethers demonstrate a significant decrease in enthalpy of vaporization upon fluorination unlike related molecules (e.g., alkanes and alcohols). Simulation suggests this phenomenon is a result of reduced cohesion in liquid PFPEs due to a reduction in localized associations between backbone oxygen atoms and neighboring molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Investigating magnetic van der Waals materials using data-driven approaches

In this work, we investigate magnetic monolayers of the form A i A ii B 4 X 8 based on the well-known intrinsic topological magnetic van der Waals (vdW) material MnBi 2 Te 4 (MBT) using first-principles calculations and machine learning techniques. We select an initial subset of structures to calculate the thermodynamic properties, electronic properties, such as the band gap, and magnetic properties, such as the magnetic moment and magnetic order using density functional theory (DFT). Data analytics approaches are used to gain insight into the microscopic origin of materials’ properties. The dependence of materials’ properties on chemical composition is also explored. For example, we find that the formation energy and magnetic moment depend largely on A and B sites whereas the band gap depends on all three sites. Finally, we employ machine learning tools to accelerate the search for novel vdW magnets in the MBT family with optimized properties. Finally, this study creates avenues for rapidly predicting novel materials with desirable properties that could enable applications in spintronics, optoelectronics, and quantum computing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Single-ancilla ground state preparation via Lindbladians

We design a quantum algorithm for ground state preparation in the early fault tolerant regime. As a Monte Carlo style quantum algorithm, our method features a Lindbladian where the target state is stationary. The construction of this Lindbladian is algorithmic and should not be seen as a specific approximation to some weakly coupled system-bath dynamics in nature. Our algorithm can be implemented using just one ancilla qubit and efficiently simulated on a quantum computer. It can prepare the ground state even when the initial state has zero overlap with the ground state, bypassing the most significant limitation of methods like quantum phase estimation. As a variant, we also propose a discrete-time algorithm, demonstrating even better efficiency and providing a near-optimal simulation cost depending on the desired evolution time and precision. Numerical simulations using Ising and Hubbard models demonstrate the efficacy and applicability of our method. Published by the American Physical Society 2024

Ding, Zhiyan (ORCID:000000018863403X)↗
DOE OSTI2022

A Logarithmic Bayesian Approach to Quantum Error Detection

We consider the problem of continuous quantum error correction from a Bayesian perspective, proposing a pair of digital filters using logarithmic probabilities that are able to achieve near-optimal performance on a three-qubit bit-flip code, while still being reasonable to implement on low-latency hardware. These practical filters are approximations of an optimal filter that we derive explicitly for finite time steps, in contrast with previous work that has relied on stochastic differential equations such as the Wonham filter. By utilizing logarithmic probabilities, we are able to eliminate the need for explicit normalization and can reduce the Gaussian noise distribution to a simple quadratic expression. The state transitions induced by the bit-flip errors are modeled using a Markov chain, which for log-probabilities must be evaluated using a LogSumExp function. We develop the two versions of our filter by constraining this LogSumExp to have either one or two inputs, which favors either simplicity or accuracy, respectively. Using simulated data, we demonstrate that the single-term and two-term filters are able to significantly outperform both a double threshold scheme and a linearized version of the Wonham filter in tests of error detection under a wide variety of error rates and time steps.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

NASA Tech Briefs, April 2009

Topics covered include: Direct-Solve Image-Based Wavefront Sensing; Use of UV Sources for Detection and Identification of Explosives; Using Fluorescent Viruses for Detecting Bacteria in Water; Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System; Volcano Monitor: Autonomous Triggering of In-Situ Sensors; Wireless Fluid-Level Sensors for Harsh Environments; Interference-Detection Module in a Digital Radar Receiver; Modal Vibration Analysis of Large Castings; Structural/Radiation-Shielding Epoxies; Integrated Multilayer Insulation; Apparatus for Screening Multiple Oxygen-Reduction Catalysts; Determining Aliasing in Isolated Signal Conditioning Modules; Composite Bipolar Plate for Unitized Fuel Cell/Electrolyzer Systems; Spectrum Analyzers Incorporating Tunable WGM Resonators; Quantum-Well Thermophotovoltaic Cells; Bounded-Angle Iterative Decoding of LDPC Codes; Conversion from Tree to Graph Representation of Requirements; Parallel Hybrid Vehicle Optimal Storage System; and Anaerobic Digestion in a Flooded Densified Leachbed.

Source record↗
NASA NTRS2021

Advances in Detector-Integrated Filter Coatings for the Far Ultraviolet

We report on the continued development of multilayer optical coatings on back-illuminated silicon imaging sensors in order to enhance the functionality of such systems at ultraviolet wavelengths. This includes the development metal-dielectric filter structures to enable solar-blind operation, and graded thickness coatings to tune the spatial response of a detector system to the dispersion of a spectrometer. Such systems can maintain the high internal quantum efficiency afforded by the delta-doping process utilized at NASA JPL, while also providing long-wavelength rejection or a spatially optimized efficiency (or both). We present the characterization of CCD and CMOS image sensors incorporating these processes, and describe the atomic layer deposition coating processes. Such detectors are currently being developed for ground-based high energy physics applications as well as NASA orbital astrophysics instruments operating at wavelengths shorter than 200 nm.

Nikzad, Shouleh↗
DOE OSTI2026

Sparse Phase Ansatzes for Resource-Efficient Qudit State Preparation via the SNAP-Displacement Protocol

Efficient preparation of nonclassical bosonic states is a central requirement for quantum computing, simulation, and precision metrology. We study resource-efficient quantum state preparation in bosonic qudit systems using the SNAP-displacement (SD) protocol. Existing SD-based approaches typically require a large number of gates and SNAP phases, resulting in complex control pulses with longer ansatz durations and amplified impact of photon-loss and control errors. In this work, we focus on the near- to medium-term regime, in which noisy quantum devices impose trade-offs on the fidelity that can be achieved, which must be taken into account. Specifically, we propose to optimize only a subset of the SNAP phases and introduce three progressively more general sparse ansatzes. To provide fine-grained control and identify the most suitable ansatz for a given target fidelity, we further employ a scalarized multi-objective optimization that trades off fidelity against either the number of phases or the duration of the ansatz. Numerical results for several target states and qudit dimensions up to $d=64$, evaluated through the hypervolume of the Pareto frontiers, show that these sparse ansatzes achieve favorable trade-offs over the fully parameterized SD protocol in both ideal and noisy settings. The advantage is strongest and most consistent when minimizing the number of phases, while improvements in ansatz duration are smaller and more dependent on the target-state family and noise level, suggesting a practical route to more efficient near- and medium-term bosonic state preparation.

Ferrari Dacrema, Maurizio [Milan Polytechnic] (ORC↗
DOE OSTI2025

A Sensitive Electrochemical Cholinesterase-Inhibiting Biosensor for Organophosphorus Pesticides Based on Ti 3 C 2 TX MXene Quantum Dots

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti 3 C 2 T x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10 −17 M and a wide linear range (10 −14 –10 −8 M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection.

Chemistry↗
DOE OSTI2020

Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials

Here we employed Density Functional Theory (DFT) to compute oxidation potentials of 1,400 homobenzylic ether molecules to search for the ideal sustainable redoxmer design. The generated data were used to construct an active learning model based on Bayesian optimization (BO) that targets candidates with desired oxidation potentials utilizing only a minimal number of DFT calculations. The active learning model demonstrated not only significant efficiency improvement over the random selection approach but also robust capability in identifying desired candidates in an untested set of 112,000 homobenzylic ether molecules. Our findings highlight the efficacy of quantum chemistry-informed active learning to accelerate the discovery of materials with desired properties from a vast chemical space.

25 ENERGY STORAGE↗
DOE OSTI2023

Low-efficiency-droop c -plane InGaN/GaN light-emitting diodes through the use of thick single quantum wells and doped barriers

Efficiency droop at high current densities is a problem for InGaN-based light-emitting diodes (LEDs), especially for conventional c-plane devices. The large internal electric fields in c-plane quantum wells (QWs) lead to an increase in the active region carrier density (n), causing the electrical efficiency droop onset to occur at low current densities. Here, we present an approach to reduce the internal electric fields (Eint) in c-plane QWs by placing doped p-type and n-type GaN barriers close to the QW. The reduced Eint also allows a thick QW active region design, which helps to lower n to further reduce the droop. The concept of using doped barriers to control Eint is explained using theory and device simulations. Following that, multiple series of thick single QW (SQW) LEDs were grown and characterized. Key parameters in the epitaxial design such as the doping levels and the relative position of the doped barriers were systematically studied and optimized. In conclusion, by using optimized doped barriers and a thick SQW, c-plane LEDs with a low-efficiency droop of 14% at 300 A/cm2 [with respect to the peak external quantum efficiency (EQE)] and a high peak EQE of 49% were demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗