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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Unified Workflow for Sensitivity-Based Kinetic Analysis in Microkinetic Models

Degrees of rate control (DRC), apparent activation energies, and apparent reaction orders are established local sensitivity diagnostics for interpreting microkinetic models, but applying them routinely to large mechanisms often requires substantial reaction-specific bookkeeping, perturbation design, and postprocessing. Here, in this study, we present a unified derivative-based workflow that evaluates these quantities from a single compiled reaction-network model and target-rate definition. For any user-provided microkinetic model, the workflow compiles the mechanism into stoichiometrically consistent mass-action rate equations, solves the surface dynamics, and uses automatic differentiation to compute sensitivities with respect to rate constants, temperature, and gas partial pressures. By combining their calculations in the same framework, the workflow clearly demonstrates the relationships between different DRCs and the apparent activation energy. Using existing examples of propylene partial oxidation and methane oxidation on Pd(100), we verify expected transient redistribution of rate control, distinguish net Campbell DRCs from one-sided directional sensitivities, and show how apparent activation energy can be reconstructed either from one-sided DRCs or from state-based DRCs while critical mechanistic insights are obtained consistently. In the methane oxidation case, a pathway-subset test further illustrates how a simplified mechanism preserves key kinetic signatures of a full model, showing the potential of our user-friendly tool for model construction beyond kinetic analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Ligand-Sensitized Lanthanide Nanocrystals: Merging Solid-State Photophysics and Molecular Solution Chemistry

To date, the breadth of scientific research that has been devoted to investigating the photochemical and photophysical behavior of the lanthanide elements has generally fallen into one of two camps: solution studies of luminescent lanthanide metal-ligand complexes or investigations of solid-state nanoparticles, composed primarily of, or doped with, lanthan ide lumiphores. In the latter case, most research of lanthanide nanocolloids has precluded any investigations regarding the use of organic ligands to overcome the difficulties associated with f-f excitation of lanthanides. Instead, most work on condensed-phase lanthanide luminescence has centered on strategies such as d-f charge separation in divalent lanthanides and the sensitization of lanthanide excited states using quantum dots. Current work now aims at bridging the camps of condensed-phase lanthanide photophysics and the solution chemistry of ligand-lanthanide molecular complexes. Some recent efforts have partly focused on the fundamental characterization of NaGd 1-x Ln x F 4 nanoparticles featuring surface display of the sensitizer ligand 3,4,3-LI(1,2-HOPO), showing these structures to be capable of converting absorbed UV light into luminescence from Eu 3+ and Tb 3+ ions. Our results suggest such a use of the ligand sensitization as a tool of choice to overcome the constraints of UV solar spectrum/semiconductor band-gap mismatch and low absorption cross sections in solid-state lanthanide systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Sum over Histories Representation for Kinetic Sensitivity Analysis: How Chemical Pathways Change When Reaction Rate Coefficients Are Varied

The sensitivity of kinetic observables is analyzed using a newly developed sum over histories representation of chemical kinetics. In the sum over histories representation, the concentrations of the chemical species are decomposed into the sum of probabilities for chemical pathways that follow molecules from reactants to products or intermediates. Unlike static flux methods for reaction path analysis, the sum over histories approach includes the explicit time dependence of the pathway probabilities. Using the sum over histories representation, the sensitivity of an observable with respect to a kinetic parameter such as a rate coefficient is then analyzed in terms of how that parameter affects the chemical pathway probabilities. The method is illustrated for species concentration target functions in H-2 combustion where the rate coefficients are allowed to vary over their associated uncertainty ranges. It is found that large sensitivities are often associated with rate limiting steps along important chemical pathways or by reactions that control the branching of reactive flux

chemical kinetics↗
DOE OSTI2020

Peptoid-Based Programmable 2D Nanomaterial Sensor for Selective and Sensitive Detection of H 2 S in Live Cells

During the past decades, a variety of two-dimensional (2D) nanosheets have been developed through supramolecular self-assembly. Among them, those assembled from sequence-defined molecules have received particularly attention because they enable a precise displaying of functional groups, including fluorescent dyes, within nanosheet surfaces. On the other hand, due to the fluorescence self-quenching, synthesis of organic 2D nanosheets exhibiting high fluorescence quantum yields is a significant challenge. Herein, we report the utilization of H 2 S-responsive probes as peptoid sidechains to design and synthesize crystalline 2D nanomembranes (2DNMs) as selective and sensitive H 2 S sensors. These 2DNM sensors exhibit a high quantum yield as a result of high crystallinity and tunable probe density. Compared with amorphous state of peptoid assembly and pre-assembled peptoid-probe conjugates, these crystalline 2DNM sensors exhibit a significantly strong fluorescence intensity and a high sensitivity (~ 0.36 nM). By sonication-cutting these 2DNM sensors into a colloidal form in aqueous solution, we further demonstrated the use of colloidal 2DNMs for detecting both exogenous and endogenous H 2 S inside cells or targeted cell organelles. As far as we know, this is the first example of using sequence-defined 2D nanomaterials for selective and sensitive detection of H 2 S. Because peptoids are biocompatible and peptoid-based 2DNMs are highly programmable, we expect that this new class of 2DNM sensors offer great potentials for detecting H 2 S and for biological applications.

2D nanomaterials↗
DOE OSTI2016

Perovskite nanoparticle-sensitized Ga 2 O 3 nanorod arrays for CO detection at high temperature

Here, noble metal nanoparticles are extensively used for sensitizing metal oxide chemical sensors through the catalytic spillover mechanism. However, due to earth-scarcity and high cost of noble metals, finding replacements presents a great economic benefit. Besides, high temperature and harsh environment sensor applications demand material stability under conditions approaching thermal and chemical stability limits of noble metals. In this study, we employed thermally stable perovskite-type La 0.8 Sr 0.2 FeO 3 (LSFO) nanoparticle surface decoration on Ga 2 O 3 nanorod array gas sensors and discovered an order of magnitude enhanced sensitivity to carbon monoxide at 500 °C. The LSFO nanoparticle catalysts was of comparable performance to that achieved by Pt nanoparticles, with a much lower weight loading than Pt. Detailed electron microscopy and X-ray photoelectron spectroscopy studies suggested the LSFO nanoparticle sensitization effect is attributed to a spillover-like effect associated with the gas-LSFO-Ga 2 O 3 triple-interfaces that spread the negatively charged surface oxygen ions from LSFO nanoparticles surfaces over to β-Ga 2 O 3 nanorod surfaces with faster surface CO oxidation reactions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Enhanced Stability and Sensitivity for CA-125 Detection Under Microfluidic Shear Flow Using Polyethylene Glycol-Coated Biosensor

The microfluidic-based point-of-care (POC) diagnostic tool has garnered significant interest in recent years, offering rapid and cost-effective disease detection. There is a growing trend toward integrating microfluidic platforms with biosensors, aligning lab-on-a-chip technologies with POC diagnostic devices. Despite numerous efforts to incorporate biosensors into microfluidic systems, researchers have performed very limited investigations on the stability of biomarker detection when biosensors operate under microfluidic shear flow conditions. Gold nanoparticles (AuNPs) are a widely employed material in capacitive biosensors for antibody immobilization and sensitivity enhancement. However, AuNPs have limitations in providing stable detection of biomarkers within microfluidic shear flow due to their agglomeration nature. This study addresses these limitations by employing 2 kDa polyethylene glycol (PEG) as an intermediate biofunctional layer to immobilize CA-125 antibodies on gold-interdigitated electrodes for the stable and accurate detection of CA-125 antigens. The stabilities and sensitivities of AuNPs and PEG-coated biosensors are evaluated under both static drop and microfluidic shear flow conditions for CA-125 antigen detection. The experimental results demonstrate a capacitive signal response (5660 pF at 10 kHz) 2.2 times higher using the PEG-coated biosensor than the signal (2551 pF at 10 kHz) measured by the AuNP-coated biosensor in the detection of CA-125 antigen–antibody conjugation under static drop conditions, indicating the higher sensitivity of the PEG-coated biosensor. Additionally, the PEG-coated biosensor exhibits better consistency for the CA-125 antigen detection between static drop and microfluidic shear flow conditions (Cp decrease in percentage (ΔCp%↓) = 2.9% at 10 kHz) compared to the electrical signals measured using the AuNP-coated biosensor (ΔCp%↓ = 32.4% at 10 kHz), which suggests that the PEG-coated biosensor demonstrates higher stability for CA-125 antigen detection under microfluidic shear flow conditions. With these significant improvements brought by the PEG-coated biosensor, especially under microfluidic conditions, a substantial hurdle in developing electrical biosensors for POC diagnostic applications has been overcome, expediting further advancements in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Electrochemical Deposition of Conformal Semiconductor Layers in Nanoporous Oxides for Sensitized Photoelectrodes

Nanoporous photoelectrodes with photoactive semiconductors have been investigated for various energy applications such as solar cells and photoelectrochemical cells, but the deposition of the semiconducting materials on the nanoporous electrodes has been very challenging due to pore clogging or complete pore filling. Here, we propose a band alignment model that explains the morphology of the electrochemically deposited semiconductor layer on the semiconducting nanoporous oxide electrode. Briefly, the coating material with a conduction band edge higher (i.e., more negative) than that of the electrode material forms a conformal coating, which maintains the initial nanoporous structure. As a result, a conformal CdSe layer can be electrodeposited onto TiO 2 nanotubes, which can be used as a photoelectrode of a sensitized solar cell. The electron dynamics studies revealed that the CdSe-sensitized TiO 2 nanotube electrode exhibited faster charge transport and slower charge recombination than its dye-sensitized counterpart, which has been ascribed to the passivation of surface traps and the physically blocked back-electron transfer by the CdSe layer as well as the higher conduction band of CdSe.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Topological Engineering of Interfacial Optical Tamm States for Highly Sensitive Near-Singular-Phase Optical Detection

Here, we developed planar multilayered photonic-plasmonic structures, which support topologically protected optical states on the interface between metal and dielectric materials, known as optical Tamm states. Coupling of incident light to the Tamm states can result in perfect absorption within one of several narrow frequency bands, which is accompanied by a singular behavior of the phase of electromagnetic field. In the case of near-perfect absorptance, very fast local variation of the phase can still be engineered. In this research, we theoretically and experimentally demonstrate how these drastic phase changes can improve sensitivity of optical sensors. A planar Tamm absorber was fabricated and used to demonstrate remote near-singular-phase temperature sensing with an over an order of magnitude improvement in sensor sensitivity and over two orders of magnitude improvement in the figure of merit over the standard approach of measuring shifts of resonant features in the reflectance spectra of the same absorber. Our experimentally demonstrated phase-to-amplitude detection sensitivity improvement nearly doubles that of state-of-the-art nano-patterned plasmonic singular-phase detectors, with further improvements possible via more precise fabrication. Tamm perfect absorbers form the basis for robust planar sensing platforms with tunable spectral characteristics, which do not rely on low-throughput nano-patterning techniques.

42 ENGINEERING↗
DOE OSTI2015

Visible Light Sensitized CO 2 Activation by the Tetraaza [Co II N 4 H(MeCN)] 2+ Complex Investigated by FT-IR Spectroscopy and DFT Calculations

In situ FT-IR measurements and electronic structure calculations are reported for the reduction of CO 2 catalyzed by the macrocyclic complex [Co II N 4 H] 2+ (N 4 H = 2,12-dimethyl-3,7,11,17-tetraazabicyclo-[11.3.1]-heptadeca-1(17),2,11,13,15-pentaene). Beginning from the [Co II N 4 H] 2+ resting state of the complex in wet acetonitrile solution, two different visible light sensitizers with substantially different reducing power are employed to access reduced states. Accessing reduced states of the complex with a [Ru(bpy) 3 ] 2+ sensitizer yields an infrared band at 1670 cm -1 attributed to carboxylate, which is also observed for an authentic sample of the one-electron reduced complex [CoN 4 H(MeCN)] + in CO 2 saturated acetonitrile solution. The results are interpreted based on calculations using the pure BP86 functional that correctly reproduces experimental geometries. Continuum solvation effects are also included. The calculations show that Co is reduced to CoIin the first reduction, which is consistent with experimental d-d spectra of square Co(I) macrocycle complexes. The energy of the CO 2 adduct of the one-electron reduced catalyst complex is essentially the same as for [CoN 4 H(MeCN)] + , which implies that only a fraction of the latter forms an adduct with CO 2 . By contrast, the calculations indicate a crucial role for redox noninnocence of the macrocyclic ligand in the doubly reduced state, [Co I (N 4 H) -• ], and show that [Co I (N 4 H) -• ] binds partially reduced CO 2 fairly strongly. Experimentally accessing [Co I (N 4 H)-•] with an Ir(bpy) 3 sensitizer with greater reducing power closes the catalytic cycle as FT-IR spectroscopy shows CO production. Use of isotopically substituted C 18 O 2 also shows clear evidence for 18 O-substituted byproducts from CO 2 reduction to CO.

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

Estimating the Acute Health Impacts of Fire-Originated PM 2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM 2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM 2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM 2.5 . Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.

58 GEOSCIENCES↗
DOE OSTI2022

The FastEddy® Resident-GPU Accelerated Large-Eddy Simulation Framework: Moist Dynamics Extension, Validation and Sensitivities of Modeling Non-Precipitating Shallow Cumulus Clouds

Herein we describe the moist dynamics formulation implemented within the graphics processing unit-resident large-eddy simulation FastEddy® model, which includes a simple saturation adjustment scheme for condensation and evaporation processes. Two LES model intercomparison exercises for non-precipitating shallow cumulus clouds are simulated in order to validate this model extension, including a static forcing and a time-dependent forcing case. Overall, we find our dynamical, thermodynamical and microphysical quantities, along with turbulence variability and fluxes, to be commensurate with the corresponding model intercomparison results. In addition, sensitivities to specific model settings are investigated. Among these settings, it is shown that boundary layer and cloud layer structure and characteristics are sensitive to use of higher-order advection schemes impacting the vertical distribution of cloud content and associated turbulence statistics. Increasing the timescale of the saturation scheme leads to enhanced liquid water presence and decreases vertical velocity variance within the cloud deck. In some cases, these sensitivities agree with the model-to-model variability reported in the intercomparison exercises, highlighting the important role of specific model implementation choices in the context of shallow cumulus convection simulations. These analyses and findings also provide the basis for future extensions and applications of FastEddy® for modeling moist convection and precipitation scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sensitivity Analysis of Wind and Turbulence Predictions With Mesoscale‐Coupled Large Eddy Simulations Using Ensemble Machine Learning

Abstract Coupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Horizontal Resolution Sensitivity of the Simple Convection-Permitting E3SM Atmosphere Model in a Doubly-Periodic Configuration

We develop a doubly periodic version of the Simple Convection-Permitting E3SM Atmosphere Model (SCREAM) to provide an efficient configuration for this global convection permitting model (GCPM), akin to a single column model often found in conventional general circulation models. The design details are explained, in addition to the extensive case library associated with the doubly periodic SCREAM (DP-SCREAM) configuration. We demonstrate that doubly periodic cloud resolving models are useful tools to explore the horizontal resolution sensitivity of GCPMs, in addition to replicating biases seen in the global models. Using DP-SCREAM, we show that SCREAM exhibits behaviors of a scale aware model as it is able to naturally partition between sub-grid scale (SGS) and resolved vertical transport across the gray zone of turbulence. We show that SCREAM is reasonably scale insensitive when run at resolutions from 1 to 5 km, but can exhibit sensitivity, particularly for the shallow convective regime, when run at resolutions approaching that of large eddy simulations. We conclude that SGS parameterization improvements are likely needed to reduce this scale sensitivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

On the Links Between Ice Nucleation, Cloud Phase, and Climate Sensitivity in CESM2

Ice nucleation in mixed-phase clouds has been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. However, with present-day global mean cloud phase adjusted to replicate satellite retrievals, similar total cloud feedback is attained whether ice nucleation is simulated as aerosol-sensitive, insensitive, or absent. These model experiments all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings indicate that this update reduced global cloud phase bias, with CESM2's high climate sensitivity reflecting improved mixed-phase cloud representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗
DOE OSTI2015

Optogenetic Vision Restoration Using Rhodopsin for Enhanced Sensitivity

Retinal disease is one of the most active areas of gene therapy, with clinical trials ongoing in the United States for five diseases. There are currently no treatments for patients with late-stage disease in which photoreceptors have been lost. Optogenetic gene therapies are in development, but, to date, have suffered from the low light sensitivity of microbial opsins, such as channelrhodopsin and halorhodopsin, and azobenzene-based photoswitches. Several groups have shown that photoreceptive G-protein-coupled receptors (GPCRs) can be expressed heterologously, and photoactivate endogenous G i/o signaling. We hypothesized such a GPCR could increase sensitivity due to endogenous signal amplification. We targeted vertebrate rhodopsin to retinal ON-bipolar cells of blind rd1 mice and observed restoration of: (i) light responses in retinal explants, (ii) visually-evoked potentials in visual cortex in vivo , and (iii) two forms of visually-guided behavior: innate light avoidance and discrimination of temporal light patterns in the context of fear conditioning. Importantly, both the light responses of the retinal explants and the visually-guided behavior occurred reliably at light levels that were two to three orders of magnitude dimmer than required for channelrhodopsin. Thus, gene therapy with native light-gated GPCRs presents a novel approach to impart light sensitivity for visual restoration in a useful range of illumination.

Biotechnology & Applied Microbiology↗
DOE OSTI2015

Electronic Raman scattering as an ultra-sensitive probe of strain effects in semiconductors

Semiconductor strain engineering has become a critical feature of high-performance electronics because of the significant device performance enhancements that it enables. These improvements, which emerge from strain-induced modifications to the electronic band structure, necessitate new ultra-sensitive tools to probe the strain in semiconductors. Here, we demonstrate that minute amounts of strain in thin semiconductor epilayers can be measured using electronic Raman scattering. We also applied this strain measurement technique to two different semiconductor alloy systems using coherently strained epitaxial thin films specifically designed to produce lattice-mismatch strains as small as 10 -4 . Thus, comparing our strain sensitivity and signal strength in Al x Ga 1-x As with those obtained using the industry-standard technique of phonon Raman scattering, we found that there was a sensitivity improvement of 200-fold and a signal enhancement of 4 × 10 3 , thus obviating key constraints in semiconductor strain metrology.

14 SOLAR ENERGY↗
DOE OSTI2015

Reaching the quantum limit of sensitivity in electron spin resonance

The detection and characterization of paramagnetic species by electron spin resonance (ESR) spectroscopy is widely used throughout chemistry, biology and materials science, from in vivo imaging to distance measurements in spin-labelled proteins. ESR relies on the inductive detection of microwave signals emitted by the spins into a coupled microwave resonator during their Larmor precession. However, such signals can be very small, prohibiting the application of ESR at the nanoscale (for example, at the single-cell level or on individual nanoparticles). Here in this work, using a Josephson parametric microwave amplifier combined with high-quality-factor superconducting microresonators cooled at millikelvin temperatures, we improve the state-of-the-art sensitivity of inductive ESR detection by nearly four orders of magnitude. We demonstrate the detection of 1,700 bismuth donor spins in silicon within a single Hahn echo with unit signal-to-noise ratio, reduced to 150 spins by averaging a single Carr-Purcell-Meiboom-Gill sequence. This unprecedented sensitivity reaches the limit set by quantum fluctuations of the electromagnetic field instead of thermal or technical noise, which constitutes a novel regime for magnetic resonance. In conclusion, the detection volume of our resonator is ~0.02nl, and our approach can be readily scaled down further to improve sensitivity, providing a new versatile toolbox for ESR at the nanoscale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗