Less is More: How Compressed Sensing is Transforming Metrology in Chemistry

Holland, Daniel J.; Gladden, Lynn F.

doi:10.1002/anie.201400535

Cited by 32 publications

(26 citation statements)

References 96 publications

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“…Extensive efforts have been devoted in the spatial localization, [155,156] long-/short-range ordering, [130,157] defect identification, [108,158] and precise compositional differentiation. Even though extensive efforts have been devoted in the advanced reconstruction methods including discrete tomography [39] and compressed sensing, [41] simple, easy-accessible, and user-friendly technical strategies are greatly favored for material scientists. Moreover, the quantified information in current literature reports is mostly derived from direct measurement of 2D tomograms (e.g., size and distance).…”

Section: Discussionmentioning

confidence: 99%

“…[35,36] Until early this century, this technique was employed to explore delicate features of nanomaterials, pioneered by de Jong and co-workers and Midgley and co-workers. [20,23] The great advances of this technique have been well summarized with a main focus on the technological aspect (e.g., discrete tomography, [39,40] compressed sensing, [41,42] cryogenic analysis, [43,44] and analytical detections [25,26] ) or specific materials categories (including catalysts, [45] particle assemblies, [46] and ordered porous nanomaterials [47] ). [20,23] The great advances of this technique have been well summarized with a main focus on the technological aspect (e.g., discrete tomography, [39,40] compressed sensing, [41,42] cryogenic analysis, [43,44] and analytical detections [25,26] ) or specific materials categories (including catalysts, [45] particle assemblies, [46] and ordered porous nanomaterials [47] ).…”

Section: Introductionmentioning

confidence: 99%

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Electron Tomography: A Unique Tool Solving Intricate Hollow Nanostructures

et al. 2018

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Innovations in nanofabrication have expedited advances in hollow-structured nanomaterials with increasing complexity, which, at the same time, set challenges for the precise determination of their intriguing and complicated 3D configurations. Conventional transmission electron microscopy (TEM) analysis typically yields 2D projections of 3D objects, which in some cases is insufficient to reflect the genuine architectures of these 3D nano-objects, providing misleading information. Advanced analytical approaches such as focused ion beam (FIB) and ultramicrotomy enable the real slicing of nanomaterials, realizing the direct observation of inner structures but with limited spatial discrimination. Electron tomography (ET) is a technique that retrieves spatial information from a series of 2D electron projections at different tilt angles. As a unique and powerful tool kit, this technique has experienced great advances in its application in materials science, resolving the intricate 3D nanostructures. Here, the exceptional capability of the ET technique in the structural, chemical, and quantitative analysis of hollow-structured nanomaterials is discussed in detail. The distinct information derived from ET analysis is highlighted and compared with conventional analysis methods. Along with the advances in microscopy technologies, the state-of-the-art ET technique offers great opportunities and promise in the development of hollow nanomaterials.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electron Tomography: A Unique Tool Solving Intricate Hollow Nanostructures

et al. 2018

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“…The growing interest in CS can be attributed to its successful broad applicability in several areas of research and engineering such as imaging using a single-pixel detector, 37,38 nuclear-magnetic resonance imaging, 39 NMR spectroscopy, 40,41 and more. 42 In general, CS can be used to recover certain signals with a significantly reduced number of sampling points. A necessary condition for the successful reconstruction of undersampled data is the existence of a transform domain in which the signal has a sparse representation, i.e., in which only a small percentage of basis coefficients is non-zero.…”

Section: Introductionmentioning

confidence: 99%

Optimizing sparse sampling for 2D electronic spectroscopy

Roeding

Klimovich

Brixner

2017

The Journal of Chemical Physics

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We present a new data acquisition concept using optimized non-uniform sampling and compressed sensing reconstruction in order to substantially decrease the acquisition times in action-based multidimensional electronic spectroscopy. For this we acquire a regularly sampled reference data set at a fixed population time and use a genetic algorithm to optimize a reduced non-uniform sampling pattern. We then apply the optimal sampling for data acquisition at all other population times. Furthermore, we show how to transform two-dimensional (2D) spectra into a joint 4D time-frequency von Neumann representation. This leads to increased sparsity compared to the Fourier domain and to improved reconstruction. We demonstrate this approach by recovering transient dynamics in the 2D spectrum of a cresyl violet sample using just 25% of the originally sampled data points.

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“…By implementing additional compressed sensing / sparse sampling algorithms, the size of the files containing the collected data can be made significantly smaller, to enable use of networks with low speeds. This capability is required in the developing world 30,31 .…”

Section: Recording and Analysis Of Respiratory Signalsmentioning

confidence: 99%

Paper‐Based Electrical Respiration Sensor

et al. 2016

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Breathing is one of the primary vital signs used to diagnose the health status of patients; it is related to many common disorders and diseases, ranging from pulmonary and cardiovascular diseases to sleep-related disorders. Current methods of monitoring breathing require cumbersome, inconvenient and often expensive devices; this requirement sets practical limitations on the frequency and duration of measurements. This article describes a paper-based moisture sensor that uses the hygroscopic character of paper (i.e. the ability of paper to adsorb water reversibly from the surrounding environment) to measure patterns and rate of respiration by converting the changes in humidity caused by cycles of inhalation and exhalation to electrical signals. The changing levels of humidity that occur in a cycle causes a corresponding change in the ionic conductivity of the sensor, which can be measured electrically. By combining the paper sensor with conventional electronics, data concerning respiration can be transmitted to a nearby smartphone or tablet computer for post-processing, and subsequently stored on a cloud server, or they can be further analysed by a healthcare professional remotely. This means of sensing provides a new and practical solution to the problem of recording and analysing patterns of breathing.3

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Less is More: How Compressed Sensing is Transforming Metrology in Chemistry

Cited by 32 publications

References 96 publications

Electron Tomography: A Unique Tool Solving Intricate Hollow Nanostructures

Electron Tomography: A Unique Tool Solving Intricate Hollow Nanostructures

Optimizing sparse sampling for 2D electronic spectroscopy

Paper‐Based Electrical Respiration Sensor

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