Polysaccharides have key biological functions and can be harnessed for therapeutic roles, such as the anticoagulant heparin. Their complexity—e.g., >100 monosaccharides with variety in linkage and branching structure—significantly complicates analysis compared to other biopolymers such as DNA and proteins. More, and improved, analysis tools have been called for, and here we demonstrate that solid-state silicon nitride nanopore sensors and tuned sensing conditions can be used to reliably detect native polysaccharides and enzymatic digestion products, differentiate between different polysaccharides in straightforward assays, provide new experimental insights into nanopore electrokinetics, and uncover polysaccharide properties. We show that nanopore sensing allows us to easily differentiate between a clinical heparin sample and one spiked with the contaminant that caused deaths in 2008 when its presence went undetected by conventional assays. The work reported here lays a foundation to further explore polysaccharide characterization and develop assays using thin-film solid-state nanopore sensors.

Silicon nitride is a ubiquitous and well-established nanofabrication material with a host of favourable properties for creating nanofluidic devices with a range of compelling designs that offer extraordinary discovery potential. Nanochannels formed between two thin silicon nitride windows can open up vistas for exploration by freeing transmission electron microscopy to interrogate static structures and structural dynamics in liquid-based samples. Nanopores present a strikingly different architecture—nanofluidic channels through a silicon nitride membrane—and are one of the most promising tools to emerge in biophysics and bioanalysis, offering outstanding capabilities for single molecule sensing. The constrained environments in such nanofluidic devices make surface chemistry a vital design and performance consideration. Silicon nitride has a rich and complex surface chemistry that, while too often formidable, can be tamed with new, robust surface functionalization approaches. We will explore how a simple structural element—a ∼100 nm-thick silicon nitride window—can be used to fabricate devices to wrest unprecedented insights from the nanoscale world. We will detail the intricacies of native silicon nitride surface chemistry, present surface chemical modification routes that leverage the richness of available surface moieties, and examine the effect of engineered chemical surface functionality on nanofluidic device character and performance.

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Solid-state nanopores are nanoscale channels through otherwise impermeable membranes. Single molecules or particles can be passed through electrolyte-filled nanopores by, e.g. electrophoresis, and then detected through the resulting physical displacement of ions within the nanopore. Nanopore size, shape, and surface chemistry must be carefully controlled, and on extremely challenging <10 nm-length scales. We previously developed a framework to characterize nanopores from the time-dependent changes in their conductance as they are being formed through solution-phase nanofabrication processes with the appeal of ease and accessibility. We revisited this simulation work, confirmed the suitability of the basic conductance equation using the results of time-dependent experimental conductance measurements during nanopore fabrication by Yanagi et al., and then deliberately relaxed the model constraints to allow for (i) the presence of defects; and (ii) the formation of two small pores instead of one larger one. Our simulations demonstrated that the time-dependent conductance formalism supports the detection and characterization of defects, as well as the determination of pore number, but with implementation performance depending on the measurement context and results. In some cases, the ability to discriminate numerically between the correct and incorrect nanopore profiles was slight, but with accompanying differences in candidate nanopore dimensions that could yield to post-fabrication conductance profiling, or be used as convenient uncertainty bounds. Time-dependent nanopore conductance thus offers insight into nanopore structure and function, even in the presence of fabrication defects.

Dynamical disorder motivates fluctuating rate coefficients in phenomenological, mass-action rate equations. The reaction order in these rate equations is the fixed exponent controlling the dependence of the rate on the number of species. Here we clarify the relationship between these notions of (dis)order in irreversible decay, n A → B, n = 1, 2, 3, . . ., by extending a theoretical measure of fluctuations in the rate coefficient. The measure, J n − L 2 n ≥ 0, is the magnitude of the inequality between J n , the time-integrated square of the rate coefficient multiplied by the time interval of interest, and L 2 n , the square of the time-integrated rate coefficient. Applying the inequality to empirical models for non-exponential relaxation, we demonstrate that it quantifies the cumulative deviation in a rate coefficient from a constant, and so the degree of dynamical disorder. The equality is a bound satisfied by traditional kinetics where a single rate constant is sufficient. For these models, we show how increasing the reaction order can increase or decrease dynamical disorder and how, in either case, the inequality J n − L 2 n ≥ 0 can indicate the ability to deduce the reaction order in dynamically disordered kinetics.