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This article presents a conveyor belt fire classification model that allows for the determination of the most effective firefighting strategy. In addition, the effect of belt design parameters on the fire classification was determined. A methodology that involves the use of numerical simulations and artificial neural networks was implemented. An approach previously proposed for modeling fires over conveyor belts was used. With the objective of obtaining some required modeling input parameter and verifying the capacity of this approach to get realistic results, computational fluid dynamics model calibration and validation were carried out using experimental test results available in the literature. Results indicated that scenarios with belt positions closer to the mine roof and greater tunnel heights require a higher longitudinal air velocity to be attacked directly. Furthermore, the belt fire classification model provided by the artificial neural network had an accuracy around 95% when test scenarios were classified.

Satellite measurements of lake surface temperature can benefit several environmental applications such as estimation of lake evaporation, predictions of lake overturning, and meteorological forecasts. Using a one-dimensional lake simulation that incorporates satellite measurements of lake surface temperature, the average diurnal variation in lake surface temperature was obtained. The satellite measurements were obtained from the MODIS instrument aboard the Aqua and Terra satellites. Herein the functional form for the diurnal variation in surface temperature is presented for each of the five major lakes in the Savannah River Basin, which are located in South Carolina and Georgia: Lakes Jocassee, Keowee, Hartwell, Russell, and Thurmond. Differences in the diurnal variation in surface temperature between each of these lakes are identified and potential explanations for these differences are presented.

Firebrands are known to cause ignition of structures far from the primary fire front, resulting in significant damage to structures before firefighting can be attempted. To make structures more resilient to firebrand ignition, a better understanding of the heat transfer from firebrands to surfaces is needed. This paper provides a statistical assessment of different factors expected to have an impact on the heat flux from firebrand piles to a flat surface. The factors included in the study were wood moisture content, wood type (hardwood or softwood), wood density, wood state (live, dead, or artificial), wind speed, pile mass, firebrand diameter, and firebrand length. Using design of experiments, test matrices were developed that permitted a statistical analysis to be performed on the data. This statistical analysis was used to quantify which factors had a statistically significant impact on the heat flux from the pile as well as ranking the importance of the different factors. Artificial firebrands were found to have statistically higher heat fluxes compared with natural firebrands. Other factors that had a statistically significant impact on the heat flux were wind speed, firebrand length, and firebrand length-diameter interaction. Firebrand aspect ratio (related to the firebrand length-diameter interaction) is directly related to the pile porosity, which is a measure of the volume of air in the pile. Increasing the aspect ratio (which increases the pile porosity) results in higher heat fluxes across a larger region of the pile and was found to be an important factor. Firebrand diameter and pile mass were found to affect the burning duration but not as significantly as other parameters. The number of firebrands in the pile was also observed to potentially affect the heat flux, with a critical number required to reach the highest heat flux for a given firebrand geometry. National Institute of Standards and Technology (NIST)National Institute of Standards & Technology (NIST) - USA [70NANB19H052] Published version This research was funded by the National Institute of Standards and Technology (NIST) under contractNISTGrant No. 70NANB19H052.

The computational cost of predicting wildland fire spread across large, diverse landscapes is significant using current models, which limits the ability to use simulations to develop mitigation strategies or perform forecasting. This paper presents a machine learning approach to estimate the time-resolved spatial evolution of a wildland fire front using a deep convolutional inverse graphics network (DCIGN). The DCIGN was trained and tested for wildland fire spread across simple homogeneous landscapes as well as heterogeneous landscapes having complex terrain. Data sets for training, validation, and testing were created using computational models. The model for homogeneous landscapes was based on a rate of spread from the model of Rothermel, while heterogeneous spread was modeled using FARSITE. Over 10,000 model predictions were made to determine burn maps in 6 h increments up to 24 h after ignition. Overall the predicted burn maps from the DCIGN-based approach agreed with simulation results, with mean precision, sensitivity, F-measure, and Chan–Vese similarity of 0.97, 0.92, 0.93, and 0.93, respectively. Noise in the input parameters was found to not significantly impact the DCIGN-based predictions. The computational cost of the method was found to be significantly better than the computational model for heterogeneous spatial conditions where a reduction in simulation time of $$10^{2}{-}10^{5}$$ was observed. In addition, the DCIGN-based approach was shown to be capable of predicting burn maps further in the future by recursively using previous predictions as inputs to the DCIGN. The machine learning DCIGN approach was able to provide fire spread predictions at a computational cost three orders of magnitude less than current models.

Firebrands are an important mechanism of fire spread and one of the primary ways in which wildland fires ignite structures. Inverse heat transfer using thin steel plates has been shown to be an effective method for measuring heat transfer distributions from firebrands. To fully understand the dynamic process of heat transfer from firebrands to surfaces; however, it is necessary to view the underside of the firebrands, which is not possible through a steel plate. This work develops a method of inverse heat transfer using a visually transparent quartz plate and a long-wave (7.5–14.0 μm) infrared camera to facilitate visual access to the firebrands from all angles. The heat flux measurements using a quartz plate were compared with heat flux measurements using a steel plate and finite element heat transfer simulations for radiation-dominant tests using heater panels. Additionally, heat transfer measurements using cuboidal oak firebrands were conducted using both the quartz and steel plates. A corrective factor was developed based on the ratio of the effective emissivity of the quartz and stainless-steel plates at typical firebrand temperatures. The measured heat fluxes were within 1–6% after correcting for radiant energy transmitted through the quartz which was absorbed by the stainless-steel plate.

Understanding the parameters that affect firebrand burning conditions is needed to quantify and model heat transfer from firebrands to combustible surfaces. In this research, an experimental and analytical effort was conducted to determine the variable relationships that control firebrand burning. A series of experiments were performed to quantify the mass loss rate, temperature, and char diameter change with time for single and arrays of cylindrical firebrands. An analytical model was developed to predict the time dependent burning of firebrands including ash accumulation in forced flow conditions. Six different methods for predicting char oxidation were included in the model to identify the best approach for predicting firebrand burning. Based on the simulation results, the model with char oxidation determined using the heat and mass transfer Reynolds analogy provided the best results with predicted temperatures, char diameter, and mass loss rates within 5%, 4%, and 29% of the single firebrand test data, respectively. Higher differences were predicted with arrays of firebrands, which was attributed to the complex flow field that develops around the firebrands. Analysis of the analytical equations was used to identify the variable relationships affecting firebrand temperature, mass loss rate, char diameter, and burning duration.

Inverse heat transfer analysis (IHT) was used to measure the full-field heat fluxes on a small scale (0.9 m×0.9 m×0.9 m) stainless steel SS304 compartment exposed to a 100 kW diffusion flame. The measured heat fluxes were then used in a thermo-mechanical finite element model in Abaqus to predict the response of an aluminum 6061-T6 compartment to the same exposure. Coupled measurements of deflection and temperature using Thermographic Digital Image Correlation (TDIC) were obtained of an aluminum compartment tested until collapse. Two convective heat transfer coefficients, h =35 W/m2-K and h =10 W/m2-K were examined for the thermal model using the experimentally measured heat fluxes. Predictions of the thermal and structural response of the same compartment were generated by coupling Fire Dynamics Simulator (FDS) and Abaqus using the two values for h, h =35 W/m2-K and h from convection correlations. Predictions of deflection and temperature using heat fluxes from IHT and FDS with h=35 W/m2-K agreed with experimental measurements along the back wall. The temperature predictions from the IHT-Abaqus model were independent of h, whereas the temperature predictions from the FDS-Abaqus model were dependent on h.

Firebrands are known to cause spot fires and structure ignition far from the fire front, but there is a limited understanding of the heat transfer from firebrands to surfaces. In this work, high resolution heat flux distributions were measured for single firebrands with different geometries using IR thermography and inverse heat transfer analysis. Localized heat fluxes from a single firebrand were measured to be 30–105 kW/m2, which is 2–6 times higher than previous work with heat flux gauges and energy balance methods that spatially average the heat transfer from the firebrand. Firebrand geometry, wind speed, and wind speed orientation relative to the firebrand affect the heat flux magnitude and duration of the exposure.

Satellite measurements of water surface temperature can benefit several environmental applications such as predictions of lake evaporation, meteorological forecasts, and predictions of lake overturning events, among others. Limitations on the temporal resolution of satellite measurements can restrict these improvements. A model of the diurnal variation in lake surface temperature could potentially increase the effective temporal resolution of satellite measurements of surface temperature, thereby enhancing the utility of these measurements in the above applications. As a step in this direction, herein a one-dimensional thermal model of a lake is used in combination with surface temperature measurements from the moderate resolution imaging spectroradiometer instrument aboard the Aqua and Terra satellites, along with ambient atmospheric conditions from local weather stations, to calculate the diurnal surface temperature variation for Lake Hartwell in South Carolina. The calculated solutions are used to obtain a functional form for the diurnal surface temperature variation of this lake, a result which has not been obtained heretofore. This functional form was obtained by averaging over several years worth of data and, therefore, represents the diurnal variation of surface temperature of the average day. Accordingly, attempts to use this averaged function to predict surface temperature in between satellite overpasses on any given day did not perform well due to day-to-day variations in cloud cover, wind speed, and other factors. It is possible that use of this averaged function combined with daily meteorological data may enable better performance.

© 2018 IEEE. This paper presents a framework for engaging a target while approaching it from a long distance, using observation from sensors on-board a mobile robot. The proposed framework consists of two multi-stage Bayesian approaches to reliably detect and accurately engage with the target under uncertainties. The multi-stage localization approach localizes the robot and the target in a global coordinate frame. Their locations are estimated sequentially when the robot is at a long distance from the target, whereas they are localized simultaneously when the target is in the close vicinity. In the multi-stage target observation approach, a level of confidence and the associated probability of detection of the sensor are defined to make the target detectable in maximal occasions. This allows the extended Kalman filter to be implemented for the target engagement. The proposed framework was implemented on an unmanned ground vehicle equipped with multiple sensors. Results show the effectiveness of the proposed framework in solving real-world problems.

This paper presents a data-driven approach to predict spatially resolved temperatures and velocities within a compartment based on zero-dimensional zone fire modeling using a transpose convolutional neural network (TCNN). A total of 1333 Fire Dynamics Simulator (FDS) simulations of simple two-compartment configurations with different fire locations, fire sizes, ventilation configurations, and compartment geometries were used in training and testing the model. In the two-compartment test cases 95% of TCNN predicted temperatures and velocities were within ± 17.2 % and ± 0.30 m/s of FDS predictions. Although the model was trained and tested using a simple two-compartment configuration, the TCNN approach was validated with two more complex multi-compartment FDS simulations by processing each compartment individually. Overall, the flow fields in the multi-compartment validation tests agreed well with FDS predictions with 95% of TCNN predicted temperatures and velocities within ± 11 % and ± 0.25 m/s of FDS predictions. Coupling a zone fire model with the TCNN approach presented in this work can provide spatially resolved temperature and velocity predictions without significantly increasing the computational requirements. Since the approach is based on a zone fire model, the TCNN approach presented in this work is limited to simplified geometries which can be sufficiently modeled using a zone fire model.

We demonstrate a planar ion-exfoliation/dry etching fabrication-process for high-optical-quality single-crystal-diamond membranes. The process allows patterning of an array of 200 nm-thick membranes with millimeter-to-micrometer dimensions and exfoliation of the thin films from a single-crystal diamond sample via a parallel fabrication process. The optical properties of the films are measured using transmission microscopy, Raman and fluorescence spectroscopy. The process yields a measured nitrogen-vacancy emission spectra having the zero-phonon line (ZPL) peak of negatively charged centers in an unshifted spectral position suggesting high quality crystalline material.

Semiconductor nanoparticles host a number of paramagnetic point defects and impurities, many of them adjacent to the surface, whose response to external stimuli could help probe the complex dynamics of the particle and its local, nanoscale environment. Here, we use optically detected magnetic resonance in a nitrogen-vacancy (NV) center within an individual diamond nanocrystal to investigate the composition and spin dynamics of the particle-hosted spin bath. For the present sample, a ∼45 nm diamond crystal, NV-assisted dark-spin spectroscopy reveals the presence of nitrogen donors and a second, yet-unidentified class of paramagnetic centers. Both groups share a common spin lifetime considerably shorter than that observed for the NV spin, suggesting some form of spatial clustering, possibly on the nanoparticle surface. Using double spin resonance and dynamical decoupling, we also demonstrate control of the combined NV center-spin bath dynamics and attain NV coherence lifetimes comparable to those reported for bulk, Type Ib samples. Extensions based on the experiments presented herein hold promise for applications in nanoscale magnetic sensing, biomedical labeling, and imaging.

A variety of substituted pentadiynols, -diynals, and -diynones have been prepared en route to precursors to dialkynyl carbenes (R(1)-C≡C-C-C≡C-R(2)). In light of the marginal stability associated with these simple systems, several strategies were required to assemble the carbon backbones. The requisite five-carbon skeletons were prepared using 4 + 1, 3 + 2, 2 + 2 + 1, and 2 + 1 + 1 + 1 coupling methodologies. The Dess-Martin periodinane serves as an excellent method for the oxidation of pentadiynols to diynals and diynones, although many of the oxidized products are sufficiently reactive that they were not isolated; rather, they were generated in situ and intercepted with nucleophiles such as tosylhydrazide or trisylhydrazide. The hydrazone derivatives are generally reliable precursors to diazo compounds and carbenes, although cyclization of the hydrazone to afford a pyrazole can be a complicating factor in certain instances.

Extending Quantum Memory Quantum information processing and communication relies on the ability to store, retrieve, and manipulate information stored in quantum memories. In most practical instances, however, the stored quantum information is fragile and susceptible to loss during readout. Jiang et al. (p. 267 , published online 10 September) used a combination of quantum logic operations on the electronic spin of a nitrogen vacancy center in diamond to control its interactions with a nearby set of proximal nuclear spins of the carbon network. In this setup, the quantum memory of the electron spin could be made more robust. Extending the lifetime and allowing multiple readouts of the quantum memory should prove a useful technique for quantum information processing.

Mechanistic and spectroscopic investigations of reactive C3H2 hydrocarbons necessitated the preparation of diazopropyne isotopomers bearing mono-13C substitution at each of the three unique positions. The diazo compounds and their tosylhydrazone precursors were prepared from the mono-13C isotopomers of propynal (in the form of either the aldehyde or the diethyl acetal). The introduction of 13C-labeling at either alkyne position in propynal utilized the Corey–Fuchs procedure for chain homologation.

Decoherence-free subspaces protect quantum information from the effects of noise that is correlated across the physical qubits used to implement them. Given the ability to impose suitable Hamiltonians upon such a multi-qubit system, one can also implement a set of logical gates which enables universal computation on this information without compromising this protection. Real physical systems, however, seldom come with the correct Hamiltonians built-in, let alone the ability to turn them off and on at will. In the course of our development of quantum information processing devices based on liquid-state NMR, we have found the task of operating on quantum information encoded in decoherence-free subspaces rather more challenging than is commonly assumed. This contribution presents an overview of these challenges and the methods we have developed for overcoming them in practice. These methods promise to be broadly applicable to many of the physical systems proposed for the implementation of quantum information processing devices.

1-Diazo-2,4-pentadiyne (6a), along with both monodeuterio isotopomers 6b and 6c, has been synthesized via a route that proceeds through diacetylene, 2,4-pentadiynal, and 2,4-pentadiynal tosylhydrazone. Photolysis of diazo compounds 6a-c (lambda > 444 nm; Ar or N2, 10 K) generates triplet carbenes HC5H (1) and HC5D (1-d), which have been characterized by IR, EPR, and UV/vis spectroscopy. Although many resonance structures contribute to the resonance hybrid for this highly unsaturated carbon-chain molecule, experiment and theory reveal that the structure is best depicted in terms of the dominant resonance contributor of penta-1,4-diyn-3-ylidene (diethynylcarbene, H-C[triple bond]C-:C-C[triple bond]C-H). Theory predicts an axially symmetric (D(infinity h)) structure and a triplet electronic ground state for 1 (CCSD(T)/ANO). Experimental IR frequencies and isotope shifts are in good agreement with computed values. The triplet EPR spectrum of 1 (absolute value(D/hc) = 0.6157 cm(-1), absolute value(E/hc) = 0.0006 cm(-1)) is consistent with an axially symmetric structure, and the Curie law behavior confirms that the triplet state is the ground state. The electronic absorption spectrum of 1 exhibits a weak transition near 400 nm with extensive vibronic coupling. Chemical trapping of triplet HC5H (1) in an O2-doped matrix affords the carbonyl oxide 16 derived exclusively from attack at the central carbon.

Collagen is the most abundant protein in animals. The protein consists of a helix of three strands, each with sequence X-Y-Gly. Natural collagen is most stable when X is (2S)-proline (Pro) and Y is (2S,4R)-4-hydroxyproline (4R-Hyp). We had shown previously that triple helices in which X is (2S,4S)-4-fluoroproline (4S-Flp) or Y is (2S,4R)-4-fluoroproline (4R-Flp) display hyperstability. This hyperstability arises from stereoelectronic effects that preorganize the main-chain dihedral angles in the conformation found in the triple helix. Here, we report the synthesis of strands containing both 4S-Flp in the X-position and 4R-Flp in the Y-position. We find that these strands do not form a stable triple helix, presumably because of an unfavorable steric interaction between fluoro groups on adjacent strands. Density functional theory calculations indicate that (2S,3S)-3-fluoroproline (3S-Flp), like 4S-Flp, should preorganize the main chain properly for triple-helix formation but without a steric conflict. Synthetic strands containing 3S-Flp in the X-position and 4R-Flp in the Y-position do form a triple helix. This helix is, however, less stable than one with Pro in the X-position, presumably because of an unfavorable inductive effect that diminishes the strength of the interstrand 3S-FlpC=O...H-NGly hydrogen bond. Thus, other forces can counter the benefits derived from the proper preorganization. Although (Pro-Pro-Gly)7 and (4S-Flp-4R-Flp-Gly)7 do not form stable homotrimeric helices, mixtures of these two peptides form stable heterotrimeric helices containing one (Pro-Pro-Gly)7 strand and two (4S-Flp-4R-Flp-Gly)7 strands. This stoichiometry can be understood by considering the cross sections of the two possible heterotrimeric helices. This unexpected finding portends the development of a "code" for the self-assembly of determinate triple helices from two or three strands.

The electronic spectrum of singlet propadienylidene (H2C=C=C:) matrix isolated in neon at 6 K was measured. Propadienylidene is the only member of the homologous series of neutral carbon chain molecules H2C(=C)n to be observed by electronic spectroscopy. The spectrum displays three electronic transitions: two in the visible ( 1A2 ← 1A1 and 1B1 ← 1A1) and one in the UV ( 1A1 ← 1A1). The longest wavelength transition ( 1A2 ← 1A1) is symmetry forbidden but is weakly seen in the spectrum via vibronic coupling with the 1B1 state. The other two transitions exhibit well-resolved vibrational progressions. The high density of absorptions in the visible region confirms earlier suggestions that the H2C(=C)n family of cumulene carbenes merits careful consideration as potential carriers of diffuse interstellar bands.

Frequency standards based on atomic states, such as Rb or Cs vapors, or single-trapped ions, are the most precise measures of time. Here we propose and analyze a precision oscillator approach based upon spins in a solid-state system, in particular, the nitrogen-vacancy defect in single-crystal diamond. We show that this system can have stability approaching portable atomic standards and is readily incorporable as a chip-scale device. Using a pulsed spin-echo technique, we anticipate an Allan deviation of ${\ensuremath{\sigma}}_{y}={10}^{\ensuremath{-}7}{\ensuremath{\tau}}^{\ensuremath{-}1/2}$ limited by thermally-induced strain variations; in the absence of such thermal fluctuations, the system is limited by spin dephasing and harbors an Allan deviation nearing $\ensuremath{\sim}{10}^{\ensuremath{-}12}{\ensuremath{\tau}}^{\ensuremath{-}1/2}$. Potential improvements based upon advanced diamond material processing, temperature stabilization, and nanophotonic engineering are discussed.

Photonic entanglement interconversion between time-bin and polarization bases has application to quantum communication, computation and memories. We characterize hybrid-basis entanglement between a pair photons obtained through such interconversion and show that non-classical correlations persist.

We present a mass fabrication method of diamond nanoscale slabs by alternating plasma etching and mask deposition. These slabs support NV− spins with long coherence times and are suitable for a range of nanophotonic devices.

To promote healing of many orthopedic injuries, tissue engineering approaches are being developed that combine growth factors such as Bone Morphogenetic Proteins (BMP) with biomaterial carriers. Although these technologies have shown great promise, they still face limitations. We describe a generalized approach to create target-specific modular peptides that bind growth factors to implantable biomaterials. These bifunctional peptide coatings provide a novel way to modulate biology on the surface of an implant. Using phage display techniques, we have identified peptides that bind with high affinity to BMP-2. The peptides that bind to BMP-2 fall into two different sequence clusters. The first cluster of peptide sequences contains the motif W-X-X-F-X-X-L (where X can be any amino acid) and the second cluster contains the motif F-P-L-K-G. We have synthesized bifunctional peptide linkers that contain BMP-2 and collagen-binding domains. Using a rat ectopic bone formation model, we have injected rhBMP-2 into a collagen matrix with or without a bifunctional BMP-2: collagen peptide (BC-1). The presence of BC-1 significantly increased osteogenic cellular activity, the area of bone formed, and bone maturity at the site of injection. Our results suggest that bifunctional peptides that can simultaneously bind to a growth factor and an implantable biomaterial can be used to control the delivery and release of growth factors at the site of implantation.

We investigate the sensitivity of a recently proposed method for precision measurement [Phys. Rev. Lett. 106, 140502 (2011)], focusing on an implementation based on solid-state spin systems. The scheme amplifies a quantum sensor response to weak external fields by exploiting its coupling to spin impurities in the environment. We analyze the limits to the sensitivity due to decoherence and propose dynamical decoupling schemes to increase the spin coherence time. The sensitivity is also limited by the environment spin polarization; therefore we discuss strategies to polarize the environment spins and present a method to extend the scheme to the case of zero polarization. The coherence time and polarization determine a figure of merit for the environment's ability to enhance the sensitivity compared to echo-based sensing schemes. This figure of merit can be used to engineer optimized samples for high-sensitivity nanoscale magnetic sensing, such as diamond nanocrystals with controlled impurity density., 9 pages, 6 figures

We describe a scheme for interconverting photonic entanglement between time-bin and polarization bases. This scheme makes entangled pairs insensitive to birefringement effects and thus has application in fiber-based quantum memories.

Optical nanocavities enable a strong interaction between single photons and single emitters. An appealing application is the construction of a quantum interface for photonic and solid state qubits. Since the material of the solid state qubit is often dierent from the nanocavity, there has been considerable interest in combining the two in a hybrid architecture. We describe our recent development of such a hybrid interface based a Gallium Phosphide photonic crystal nanocavity that is scanned and deterministically coupled to single emitters on a surface. The technique is used to couple the cavity to the nitrogen vacancy center in diamond, an emitter system with optically accessible electron spins and the ability to transfer electronic spin states to nuclear spins.

New schemes that exploit the unique properties of Nitrogen-Vacancy (NV) centers in diamond are presently being explored as a platform for high-resolution magnetic sensing. Here we focus on the ability of a NV center to monitor an adjacent mesoscopic nuclear spin bath. For this purpose, we conduct comparative experiments where the NV spin evolves under the influence of surrounding 13C nuclei or, alternatively, in the presence of asynchronous AC fields engineered to emulate bath fluctuations. Our study reveals substantial differences that underscore the limitations of the semi-classical picture when interpreting and predicting the outcome of experiments designed to probe small nuclear spin ensembles. In particular, our study elucidates the NV center response to bath fluctuations under common pulse sequences, and explores a detection protocol designed to probe time correlations of the nuclear spin bath dynamics. Further, we show that the presence of macroscopic nuclear spin order is key to the emergence of semi-classical spin magnetometry., Comment: 30 pages, 4 figures

A fundamental limit to existing optical techniques for measurement and manipulation of spin degrees of freedom is set by diffraction, which does not allow spins separated by less than about a quarter of a micrometre to be resolved using conventional far-field optics. Here, we report an efficient far-field optical technique that overcomes the limiting role of diffraction, allowing individual electronic spins to be detected, imaged and manipulated coherently with nanoscale resolution. The technique involves selective flipping of the orientation of individual spins, associated with nitrogen-vacancy centres in room-temperature diamond, using a focused beam of light with intensity vanishing at a controllable location, which enables simultaneous single-spin imaging and magnetometry at the nanoscale with considerably less power than conventional techniques. Furthermore, by inhibiting spin transitions away from the laser intensity null, selective coherent rotation of individual spins is realized. This technique can be extended to subnanometre dimensions, thus enabling applications in diverse areas ranging from quantum information science to bioimaging.

The development of material-processing techniques that can be used to generate optical diamond nanostructures containing a single-color center is an important problem in quantum science and technology. In this work, we present the combination of ion implantation and top-down diamond nanofabrication in two scenarios: diamond nanopillars and diamond nanowires. The first device consists of a 'shallow' implant (~20 nm) to generate nitrogen-vacancy (NV) color centers near the top surface of the diamond crystal prior to device fabrication. Individual NV centers are then mechanically isolated by etching a regular array of nanopillars in the diamond surface. Photon anti-bunching measurements indicate that a high yield (>10%) of the devices contain a single NV center. The second device demonstrates 'deep' (~1 μm) implantation of individual NV centers into diamond nanowires as a post-processing step. The high single-photon flux of the nanowire geometry, combined with the low background fluorescence of the ultrapure diamond, allowed us to observe sustained photon anti-bunching even at high pump powers., United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship), National Science Foundation (U.S.) (NSF Graduate Research Fellowship), Alfred P. Sloan Foundation

We describe a method to enhance the sensitivity of precision measurements that takes advantage of a quantum sensor's environment to amplify its response to weak external perturbations. An individual qubit is used to sense the dynamics of surrounding ancillary qubits, which are in turn affected by the external field to be measured. The resulting sensitivity enhancement is determined by the number of ancillas that are coupled strongly to the sensor qubit; it does not depend on the exact values of the coupling strengths and is resilient to many forms of decoherence. The method achieves nearly Heisenberg-limited precision measurement, using a novel class of entangled states. We discuss specific applications to improve clock sensitivity using trapped ions and magnetic sensing based on electronic spins in diamond., Comment: 4 pages, 3 figures

Magnetic Resonance Imaging (MRI) can characterize and discriminate among tissues using their diverse physical and biochemical properties. Unfortunately, submicrometer screening of biological specimens is presently not possible, mainly due to lack of detection sensitivity. Here we analyze the use of a nitrogen-vacancy center in diamond as a magnetic sensor for nanoscale nuclear spin imaging and spectroscopy. We examine the ability of such a sensor to probe the fluctuations of the "classical" dipolar field due to a large number of neighboring nuclear spins in a densely protonated sample. We identify detection protocols that appropriately take into account the quantum character of the sensor and find a signal-to-noise ratio compatible with realistic experimental parameters. Through various example calculations we illustrate different kinds of image contrast. In particular, we show how to exploit the comparatively long nuclear spin correlation times to reconstruct a local, high-resolution sample spectrum., Comment: 10 pages, 4 figures

The ability to sense nanotelsa magnetic fields with nanoscale spatial resolution is an outstanding technical challenge relevant to the physical and biological sciences. For example, detection of such weak localized fields will enable sensing of magnetic resonance signals from individual electron or nuclear spins in complex biological molecules and the readout of classical or quantum bits of information encoded in an electron or nuclear spin memory. Here we present a novel approach to nanoscale magnetic sensing based on coherent control of an individual electronic spin contained in the Nitrogen-Vacancy (NV) center in diamond. At room temperature, using an ultra-pure diamond sample, we achieve shot-noise-limited detection of 3 nanotesla magnetic fields oscillating at kHz frequencies after 100 seconds of signal averaging. Furthermore, we experimentally demonstrate nanoscale resolution using a diamond nanocrystal of 30 nm diameter for which we achieve a sensitivity of 0.5 microtesla / Hz 1/2 .