The chemical dynamics of nanosensors capable of single-molecule detection

Single-Molecule Methane Sensing Using Palladium-Functionalized nIR Fluorescent Single-Walled Carbon Nanotubes

There has been considerable interest in detecting atmospheric and process-associated methane (CH4) at low concentrations due to its potency as a greenhouse gas. Nanosensor technology, particularly fluorescent single-walled carbon nanotube (SWCNT) arrays, is promising for such applications because of their chemical sensitivities at single-molecule detection limits. However, the methodologies for connecting the stochastic molecular fluctuations from gas impingement on such sensors require further development. In this work, we synthesize Pd-conjugated ss(GT)15-DNA-wrapped SWCNTas near-infrared (nIR) fluorescent, single-molecule sensors of CH4. The complexes are characterized using X-ray photoelectron spectroscopy (XPS) and spectrophotometry, demonstrating spectral changes between the Pd2+ and Pd0 oxidation states. The nIR fluctuations generated upon exposure from 8 to 26 ppb of CH4 were separated into high- and low-frequency components. Aggregating the low-frequency components for an array of sensors showed the most consistent levels of detection with a limit of 0.7 ppb. These results advance the hardware and computational methods necessary to apply this approach to the challenge of environmental methane sensing.

Stochastic Formation of Quantum Defects in Carbon Nanotubes

Small perturbations in the structure of materials significantly affect their properties. One example is single wall carbon nanotubes (SWCNTs), which exhibit chirality-dependent near-infrared (NIR) fluorescence. They can be modified with quantum defects through the reaction with diazonium salts, and the number or distribution of these defects determines their photophysics. However, the presence of multiple chiralities in typical SWCNT samples complicates the identification of defect-related emission features. Here, we show that quantum defects do not affect aqueous two-phase extraction (ATPE) of different SWCNT chiralities into different phases, which suggests low numbers of defects. For bulk samples, the bandgap emission (E11) of monochiral (6,5)-SWCNTs decreases, and the defect-related emission feature (E11*) increases with diazonium salt concentration and represents a proxy for the defect number. The high purity of monochiral samples from ATPE allows us to image NIR fluorescence contributions (E11 = 986 nm and E11* = 1140 nm) on the single SWCNT level. Interestingly, we observe a stochastic (Poisson) distribution of quantum defects. SWCNTs have most likely one to three defects (for low to high (bulk) quantum defect densities). Additionally, we verify this number by following single reaction events that appear as discrete steps in the temporal fluorescence traces. We thereby count single reactions via NIR imaging and demonstrate that stochasticity plays a crucial role in the optical properties of SWCNTs. These results show that there can be a large discrepancy between ensemble and single particle experiments/properties of nanomaterials.

Quantum yield in polymer wrapped single walled carbon nanotubes: a computational model

Quantum yield in polymer wrapped single walled carbon nanotubes (SWCNTs) has been computationally investigated using a 2D model of exciton decay with non-radiative channels due to the diffusive motion across the nanotube surface. Beside the role of SWCNT's ends as the exciton quenchers, we have considered the influence of the wrapping polymer through its chemistry and wrapping angle. The model has been solved exactly for zero-angle wrapping, a particular case when the polymer interfaces the nanotube along its axis. The general case has been treated numerically and it has been concluded that the wrapping angle has no relevant influence upon the quantum yield values which are of experimental interest. A wide range of quantum yield values computed in the present contribution can be helpful in understanding potentially available photoluminescence data of SWCNTs wrapped with a variety of polymer families.

Nanosensor Technology Applied to Living Plant Systems

An understanding of plant biology is essential to solving many long-standing global challenges, including sustainable and secure food production and the generation of renewable fuel sources. Nanosensor platforms, sensors with a characteristic dimension that is nanometer in scale, have emerged as important tools for monitoring plant signaling pathways and metabolism that are nondestructive, minimally invasive, and capable of real-time analysis. This review outlines the recent advances in nanotechnology that enable these platforms, including the measurement of chemical fluxes even at the single-molecule level. Applications of nanosensors to plant biology are discussed in the context of nutrient management, disease assessment, food production, detection of DNA proteins, and the regulation of plant hormones. Current trends and future needs are discussed with respect to the emerging trends of precision agriculture, urban farming, and plant nanobionics.

Kinetic Requirements for Spatiotemporal Chemical Imaging with Fluorescent Nanosensors

Fluorescent nanosensors are powerful tools for basic research and bioanalytical applications. Individual nanosensors are able to detect single molecules, while ensembles of nanosensors can be used to measure the bulk concentration of an analyte. Collective imaging of multiple nanosensors could provide both spatial and temporal chemical information from the nano- to the microscale. This type of chemical imaging with nanosensors would be very attractive to study processes such as chemical signaling between cells (e.g., neurons). So far, it is not understood what processes are resolvable (concentration, time, space) and how optimal sensors should be designed. Here, we develop a theoretical framework to simulate the fluorescence image of arrays of nanosensors in response to a concentration gradient. For that purpose, binding and unbinding of the analyte is simulated for each single nanosensor by using a Monte Carlo simulation and varying rate constants (k_on, k_off). Multiple nanosensors are arranged on a surface and exposed to a concentration pattern c_A(x,y,t) of an analyte. We account for the resolution limit of light microscopy (Abbe limit) and the acquisition speed and resolution of optical setups and determine the resulting response images ΔI(x,y,t). Consequently, we introduce terms for the spatial and temporal resolution and simulate phase diagrams for different rate constants that allow us to predict how a sensor should be designed to provide a desired spatial and temporal resolution. Our results show, for example, that imaging of neurotransmitter release requires rate constants of k_on = 10⁶ M^-1 s^-1and k_off = 10² s^-1 in many scenarios, which corresponds to high dissociation constants of K_d > 100 μM. This work predicts if a given fluorescent nanosensor array (rate constants, size, shape, geometry, density) is able to resolve fast concentration changes such as neurotransmitter release from cells. Additionally, we provide rational design principles to engineer nanosensors for chemical imaging.

State Estimation of the Time-Varying and Spatially Localized Concentration of Signal Molecules from the Stochastic Adsorption Dynamics on the Carbon Nanotube-Based Sensors and Its Application to Tumor Cell Detection

This paper addresses a problem of estimating time-varying, local concentrations of signal molecules with a carbon-nanotube (CNT)-based sensor array system, which sends signals triggered by monomolecular adsorption/desorption events of proximate molecules on the surfaces of the sensors. Such sensors work on nano-scale phenomena and show inherently stochastic non-Gaussian behavior, which is best represented by the chemical master equation (CME) describing the time evolution of the probabilities for all the possible number of adsorbed molecules. In the CME, the adsorption rate on each sensor is linearly proportional to the local concentration in the bulk phase. State estimators are proposed for these types of sensors that fully address their stochastic nature. For CNT-based sensors motivated by tumor cell detection, the particle filter, which is nonparametric and can handle non-Gaussian distributions, is compared to a Kalman filter that approximates the underlying distributions by Gaussians. In addition, the second-order generalized pseudo Bayesian estimation (GPB2) algorithm and the Markov chain Monte Carlo (MCMC) algorithm are incorporated into KF and PF respectively, for detecting latent drift in the concentration affected by different states of a cell.

Spatiotemporal intracellular nitric oxide signaling captured using internalized, near-infrared fluorescent carbon nanotube nanosensors

Fluorescent nanosensor probes have suffered from limited molecular recognition and a dearth of strategies for spatial-temporal operation in cell culture. In this work, we spatially imaged the dynamics of nitric oxide (NO) signaling, important in numerous pathologies and physiological functions, using intracellular near-infrared fluorescent single-walled carbon nanotubes. The observed spatial-temporal NO signaling gradients clarify and refine the existing paradigm of NO signaling based on averaged local concentrations. This work enables the study of transient intracellular phenomena associated with signaling and therapeutics.

Carbon nanotubes as optical biomedical sensors

Biosensors are important tools in biomedical research. Moreover, they are becoming an essential part of modern healthcare. In the future, biosensor development will become even more crucial due to the demand for personalized-medicine, point-of care devices and cheaper diagnostic tools. Substantial advances in sensor technology are often fueled by the advent of new materials. Therefore, nanomaterials have motivated a large body of research and such materials have been implemented into biosensor devices. Among these new materials carbon nanotubes (CNTs) are especially promising building blocks for biosensors due to their unique electronic and optical properties. Carbon nanotubes are rolled-up cylinders of carbon monolayers (graphene). They can be chemically modified in such a way that biologically relevant molecules can be detected with high sensitivity and selectivity. In this review article we will discuss how carbon nanotubes can be used to create biosensors. We review the latest advancements of optical carbon nanotube based biosensors with a special focus on near-infrared (NIR)-fluorescence, Raman-scattering and fluorescence quenching.

Stochastic mapping of first order reaction networks: a systematic comparison of the stochastic and deterministic kinetic approaches

Stochastic maps are developed and used for first order reaction networks to decide whether the deterministic kinetic approach is appropriate for a certain evaluation problem or the use of the computationally more demanding stochastic approach is inevitable. On these maps, the decision between the two approaches is based on the standard deviation of the expectation of detected variables: when the relative standard deviation is larger than 1%, the use of the stochastic method is necessary. Four different systems are considered as examples: the irreversible first order reaction, the reversible first order reaction, two consecutive irreversible first order reactions, and the unidirectional triangle reaction. Experimental examples are used to illustrate the practical use of the theoretical results. It is shown that the maps do not only depend on particle numbers, but the influence of parameters such as time, rate constants, and the identity of the detected target variable is also an important factor.

Three-dimensional tracking of carbon nanotubes within living cells

Three-dimensional tracking of single-walled carbon nanotubes (SWNT) with an orbital tracking microscope is demonstrated. We determine the viscosity regime (above 250 cP) at which the rotational diffusion coefficient can be used for length estimation. We also demonstrate SWNT tracking within live HeLa cells and use these findings to spatially map corral volumes (0.27-1.32 μm(3)), determine an active transport velocity (455 nm/s), and calculate local viscosities (54-179 cP) within the cell. With respect to the future use of SWNTs as sensors in living cells, we conclude that the sensor must change the fluorescence signal by at least 4-13% to allow separation of the sensor signal from fluctuations due to rotation of the SWNT when measuring with a time resolution of 32 ms.