Single-Molecule Lysozyme Dynamics Monitored by an Electronic Circuit

Choi, Yongki; Moody, Issa S.; Sims, Patrick C.; Hunt, Steven R.; Corso, Brad L.; Pérez, Israel; Weiss, Gregory A.; Collins, Philip G.

doi:10.1126/science.1214824

Cited by 218 publications

(329 citation statements)

References 72 publications

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“…506 Recently, single molecule level lysosome dynamics have also been detected in single CNT FETs. 507 Additional research has focused on detecting DNA hybridization with an eye towards DNA sequencing. The first report of DNA hybridization on CNT TFTs showed specific detection of complementary DNA sequences via conductance modulation as shown in Fig.…”

Section: 500mentioning

confidence: 99%

Carbon nanomaterials for electronics, optoelectronics, photovoltaics, and sensing

et al. 2013

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In the last three decades, zero-dimensional, one-dimensional, and two-dimensional carbon nanomaterials (i.e., fullerenes, carbon nanotubes, and graphene, respectively) have attracted significant attention from the scientific community due to their unique electronic, optical, thermal, mechanical, and chemical properties. While early work showed that these properties could enable high performance in selected applications, issues surrounding structural inhomogeneity and imprecise assembly have impeded robust and reliable implementation of carbon nanomaterials in widespread technologies. However, with recent advances in synthesis, sorting, and assembly techniques, carbon nanomaterials are experiencing renewed interest as the 2 basis of numerous scalable technologies. Here, we present an extensive review of carbon nanomaterials in electronic, optoelectronic, photovoltaic, and sensing devices with a particular focus on the latest examples based on the highest purity samples. Specific attention is devoted to each class of carbon nanomaterial, thereby allowing comparative analysis of the suitability of fullerenes, carbon nanotubes, and graphene for each application area. In this manner, this article will provide guidance to future application developers and also articulate the remaining research challenges confronting this field.Deep Jariwala is currently working as a graduate student under supervision of Prof. Mark

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Section: 500mentioning

confidence: 99%

Carbon nanomaterials for electronics, optoelectronics, photovoltaics, and sensing

et al. 2013

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“…For example, the peak value of n min for the packaging motor of φ29 is approximately 4.5, which is approximately equal to the sum of the two asymptotic limits, N L + N s = 1.6 AE 3.3 = 4.9. Recall that a controls the value of the local extremum of n min and its position along the substrate axis via Eqns (27,28). A peak that is comparable to the sum of the two asymptotic limits indicates a small, potentially zero value for a.…”

Section: What Do the New Kinetic Parameters Reveal About The Enzymatimentioning

confidence: 99%

Extracting signal from noise: kinetic mechanisms from a Michaelis–Menten‐like expression for enzymatic fluctuations

2013

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Enzyme-catalyzed reactions are naturally stochastic, and precision measurements of these fluctuations, made possible by single-molecule methods, promise to provide fundamentally new constraints on the possible mechanisms underlying these reactions. We review some aspects of statistical kinetics: a new field with the goal of extracting mechanistic information from statistical measures of fluctuations in chemical reactions. We focus on a widespread and important statistical measure known as the randomness parameter. This parameter is remarkably simple in that it is the squared coefficient of variation of the cycle completion times, although it places significant limits on the minimal complexity of possible enzymatic mechanisms. Recently, a general expression has been introduced for the substrate dependence of the randomness parameter that is for rate fluctuations what the Michaelis-Menten expression is for the mean rate of product generation. We discuss the information provided by the new kinetic parameters introduced by this expression and demonstrate that this expression can simplify the vast majority of published models.

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“…Furthermore, the different configurations in which CNTs can be arranged broaden their versatility and allow custom design of devices for specific applications. Individual single-walled carbon nanotubes (SWNTs) (9), 2D networks (10)(11)(12), and 3D nanostructures (13) have all been employed successfully.…”

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confidence: 99%

Quantitative nanoscale visualization of heterogeneous electron transfer rates in 2D carbon nanotube networks

Güell¹,

Ebejer²,

Snowden³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

113

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Carbon nanotubes have attracted considerable interest for electrochemical, electrocatalytic, and sensing applications, yet there remains uncertainty concerning the intrinsic electrochemical (EC) activity. In this study, we use scanning electrochemical cell microscopy (SECCM) to determine local heterogeneous electron transfer (HET) kinetics in a random 2D network of single-walled carbon nanotubes (SWNTs) on an Si∕SiO 2 substrate. The high spatial resolution of SECCM, which employs a mobile nanoscale EC cell as a probe for imaging, enables us to sample the responses of individual portions of a wide range of SWNTs within this complex arrangement. Using two redox processes, the oxidation of ferrocenylmethyl trimethylammonium and the reduction of ruthenium (III) hexaamine, we have obtained conclusive evidence for the high intrinsic EC activity of the sidewalls of the large majority of SWNTs in networks. Moreover, we show that the ends of SWNTs and the points where two SWNTs cross do not show appreciably different HET kinetics relative to the sidewall. Using finite element method modeling, we deduce standard rate constants for the two redox couples and demonstrate that HET based solely on characteristic defects in the SWNT side wall is highly unlikely. This is further confirmed by the analysis of individual line profiles taken as the SECCM probe scans over an SWNT. More generally, the studies herein demonstrate SECCM to be a powerful and versatile method for activity mapping of complex electrode materials under conditions of high mass transport, where kinetic assignments can be made with confidence.W ithin the family of nanostructured materials, carbon nanotubes (CNTs) have attracted particular attention because they are readily synthesised at low cost, have exceptional electronic properties, exhibit chemical and mechanical stability, and are amenable to a wide range of simple chemical functionalization routes (1-3). These characteristics have led to CNTs being considered ideal substrates for electronics (4), sensing systems (5, 6), electrocatalytic supports (7), and batteries (8). Furthermore, the different configurations in which CNTs can be arranged broaden their versatility and allow custom design of devices for specific applications. Individual single-walled carbon nanotubes (SWNTs) (9), 2D networks (10-12), and 3D nanostructures (13) have all been employed successfully.Understanding heterogeneous electron transfer (HET) at CNTs is of considerable importance, due to the wide range of electroanalytical and electrocatalytic systems based on CNTs (14-17), and also because electrochemistry provides an attractive route to functionalize and tailor the properties of . Probing HET in 1D electrode materials is interesting fundamentally, given their inherent electronic structure and properties (21,22). However, as we highlight herein, despite many studies aimed at characterizing HET at CNTs, substantial questions remain unanswered, such as the location and rate of HET.A popular approach for studying electrochemistry at CNT...

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Single-Molecule Lysozyme Dynamics Monitored by an Electronic Circuit

Cited by 218 publications

References 72 publications

Carbon nanomaterials for electronics, optoelectronics, photovoltaics, and sensing

Carbon nanomaterials for electronics, optoelectronics, photovoltaics, and sensing

Extracting signal from noise: kinetic mechanisms from a Michaelis–Menten‐like expression for enzymatic fluctuations

Quantitative nanoscale visualization of heterogeneous electron transfer rates in 2D carbon nanotube networks

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