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Nagashima G.,Harvard University | Levine E.V.,Harvard University | Hoogerheide D.P.,Harvard University | Burns M.M.,Rowland Institute at Harvard | Golovchenko J.A.,Harvard University
Physical Review Letters | Year: 2014

We demonstrate extreme superheating and single bubble nucleation in an electrolyte solution within a nanopore in a thin silicon nitride membrane. The high temperatures are achieved by Joule heating from a highly focused ionic current induced to flow through the pore by modest voltage biases. Conductance, nucleation, and bubble evolution are monitored electronically and optically. Temperatures near the thermodynamic limit of superheat are achieved just before bubble nucleation with the system at atmospheric pressure. Bubble nucleation is homogeneous and highly reproducible. This nanopore approach more generally suggests broad application to the excitation, detection, and characterization of highly metastable states of matter. © 2014 American Physical Society.


Hoch J.C.,University of Connecticut Health Center | Maciejewski M.W.,University of Connecticut Health Center | Mobli M.,University of Queensland | Schuyler A.D.,University of Connecticut Health Center | Stern A.S.,Rowland Institute at Harvard
Accounts of Chemical Research | Year: 2014

NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for characterizing complex biomolecules. However, it suffers from well-known limitations: chiefly the difficulty in obtaining high-resolution spectral estimates from short data records. Because the time required to perform an experiment is proportional to the number of data samples, this problem imposes a sampling burden for multidimensional NMR experiments. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT must either sacrifice resolution in order to be completed in reasonable time or use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets.Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis that can provide high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that occur with the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include the careful design of the sampling scheme and special methods for computing the spectrum. Researchers now routinely report that they can complete an N-dimensional NMR experiment 3N-1 times faster (a 3D experiment in one ninth of the time). As a result, high-resolution three- and four-dimensional experiments that were prohibitively time consuming are now practical. Conversely, tailored sampling in the indirect dimensions has led to improved sensitivity.Further advances in nonuniform sampling strategies could enable further reductions in sampling requirements for high resolution NMR spectra, and the combination of these strategies with robust non-Fourier methods of spectrum analysis (such as MaxEnt) represent a profound change in the way researchers conduct multidimensional experiments. The potential benefits will enable more advanced applications of multidimensional NMR spectroscopy to study biological macromolecules, metabolomics, natural products, dynamic systems, and other areas where resolution, sensitivity, or experiment time are limiting. Just as the development of multidimensional NMR methods presaged multidimensional methods in other areas of spectroscopy, we anticipate that nonuniform sampling approaches will find applications in other forms of spectroscopy. © 2014 American Chemical Society.


Wilson L.G.,University of Edinburgh | Wilson L.G.,Rowland Institute at Harvard | Poon W.C.K.,University of Edinburgh
Physical Chemistry Chemical Physics | Year: 2011

We introduce active, probe-based microrheological techniques for measuring the flow and deformation of complex fluids. These techniques are ideal for mechanical characterization either when little sample is available, or when samples show significant spatial heterogeneity. We review recent results, paying particular attention to comparing and contrasting rheological parameters obtained from micro- and macro-rheological techniques. © the Owner Societies 2011.


Martinez V.A.,University of Edinburgh | Schwarz-Linek J.,University of Edinburgh | Reufer M.,University of Edinburgh | Wilson L.G.,University of York | And 3 more authors.
Proceedings of the National Academy of Sciences of the United States of America | Year: 2014

It is widely believed that the swimming speed, v, of many flagellated bacteria is a nonmonotonic function of the concentration, c, of high-molecular-weight linear polymers in aqueous solution, showing peaked v(c) curves. Pores in the polymer solution were suggested as the explanation. Quantifying this picture led to a theory that predicted peaked v(c) curves. Using high-throughput methods for characterizing motility, we measured v and the angular frequency of cell body rotation, Ω, of motile Escherichia coli as a function of polymer concentration in polyvinylpyrrolidone (PVP) and Ficoll solutions of different molecular weights. We find that nonmonotonic v(c) curves are typically due to low-molecular-weight impurities. After purification by dialysis, the measured v(c) and Ω(c) relations for all but the highest-molecular-weight PVP can be described in detail by Newtonian hydrodynamics. There is clear evidence for non-Newtonian effects in the highest-molecular-weight PVP solution. Calculations suggest that this is due to the fast-rotating flagella seeing a lower viscosity than the cell body, so that flagella can be seen as nano-rheometers for probing the non-Newtonian behavior of high polymer solutions on a molecular scale.


Buchanan S.M.,Rowland Institute at Harvard | Kain J.S.,Rowland Institute at Harvard | De Bivorta B.L.,Rowland Institute at Harvard | De Bivorta B.L.,Harvard University
Proceedings of the National Academy of Sciences of the United States of America | Year: 2015

Genetically identical individuals display variability in their physiology, morphology, and behaviors, even when reared in essentially identical environments, but there is little mechanistic understanding of the basis of such variation. Here, we investigated whether Drosophila melanogaster displays individual-to-individual variation in locomotor behaviors. We developed a new high-throughout platform capable of measuring the exploratory behavior of hundreds of individual flies simultaneously. With this approach, we find that, during exploratory walking, individual flies exhibit significant bias in their left vs. right locomotor choices, with some flies being strongly left biased or right biased. This idiosyncrasy was present in all genotypes examined, including wild-derived populations and inbred isogenic laboratory strains. The biases of individual flies persist for their lifetime and are non-heritable: i.e., mating two left-biased individuals does not yield left-biased progeny. This locomotor handedness is uncorrelated with other asymmetries, such as the handedness of gut twisting, leg-length asymmetry, and wing-folding preference. Using transgenics and mutants, we find that the magnitude of locomotor handedness is under the control of columnar neurons within the central complex, a brain region implicated in motor planning and execution. When these neurons are silenced, exploratory laterality increases, with more extreme leftiness and rightiness. This observation intriguingly implies that the brain may be able to dynamically regulate behavioral individuality. © 2015, National Academy of Sciences. All rights reserved.

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