Analysis of rates of tunneling across self-assembled monolayers (SAMs) of n-alkanethiolates SC n (with n = number of carbon atoms) incorporated in junctions having structure Ag TS -SAM//Ga 2 O 3 /EGaIn leads to a value for the injection tunnel current density J 0 (i.e., the current flowing through an ideal junction with n = 0) of 10 3.6±0.3 A·cm −2 (V = +0.5 V). This estimation of J 0 does not involve an extrapolation in length, because it was possible to measure current densities across SAMs over the range of lengths n = 1−18. This value of J 0 is estimated under the assumption that values of the geometrical contact area equal the values of the effective electrical contact area. Detailed experimental analysis, however, indicates that the roughness of the ). A comparison of the characteristics of conical Ga 2 O 3 / EGaIn tips with the characteristics of other top-electrodes suggests that the EGaIn-based electrodes provide a particularly attractive technology for physical-organic studies of charge transport across SAMs. ■ INTRODUCTIONMeasurements, using a number of techniques, of rates of charge transport by tunneling across self-assembled monolayers (SAMs) of n-alkanethiolates on silver and gold substrates show an interesting, puzzling, and unresolved mixture of consistency and inconsistency. Rates of tunneling across these SAMs follow the simplified Simmons equation,( 1) with the falloff in current density J(V) (A·cm ). Using mercury drops as top-electrodes, measurements of rates of tunneling across n-alkanes anchored to heavily doped silicon surfaces led to β = 0.9 ± 0.2 nC −1 , similar to the values observed for nalkanethiolates on Au and Ag substrates. , observed in large-area junctions using, as top-electrodes, conductive polymers, 13 Hg-drops supporting an insulating organic film (Hg-SAM), 14−16 and Ga 2 O 3 /EGaIn tips. 17−20 Why is there high consistency in values of β, but broad inconsistency in values of J 0 (V) within these systems?A priori, at least four factors might contribute to differences in J 0 (V) among methods of measurements:(i) In large-area junctions, assuming that the effective electrical contact area (A elec )the area through which current actually passescoincides with the geometrical contact area (A geo ) estimated by optical microscopy could result in errors in the conversions of values of current into current densities. Contact between surfaces occurs only through asperities distributed on the surfaces, which are always rough to some extent; in addition, only a fraction of the true, physical contact area is conductive.21−24 Estimations of the effective contact area from measurements of adhesion and friction between surfaces indicate that values of A elec /A geo vary in the range 10 −2 −10 −4 , depending on the hardness of the materials, the heights, widths, and number of asperities on both surfaces, and loads applied to the contacts. 22,23,25−27

This paper describes a method of fabrication that generates small arrays of tunneling junctions based on self-assembled monolayers (SAMs); these junctions have liquid-metal top-electrodes stabilized in microchannels and ultraflat (template-stripped) bottom-electrodes. The yield of junctions generated using this method is high (70-90%). The junctions examined incorporated SAMs of alkanethiolates having ferrocene termini (11-(ferrocenyl)-1-undecanethiol, SC 11 Fc); these junctions rectify currents with large rectification ratios (R), the majority of which fall within the range of 90-180. These values are larger than expected (theory predicts R e 20) and are larger than previous experimental measurements. SAMs of n-alkanethiolates without the Fc groups (SC n-1 CH 3 , with n ) 12, 14, 16, or 18) do not rectify (R ranged from 1.0 to 5.0). These arrays enable the measurement of the electrical characteristics of the junctions as a function of chemical structure, voltage, and temperature over the range of 110-293 K, with statistically large numbers of data (N ) 300-800). The mechanism of rectification with Fc-terminated SAMs seems to be charge transport processes that change with the polarity of bias: from tunneling (at one bias) to hopping combined with tunneling (at the opposite bias).

This paper compares charge transport across self-assembled monolayers (SAMs) of nalkanethiol containing odd and even numbers of methylenes. Ultraflat template-stripped silver (Ag TS ) surfaces supported the SAMs, while top-electrodes of eutectic galliumindium (EGaIn) contacted the SAMs to form metal/SAM//oxide/EGaIn junctions. TheEGaIn spontaneously reacts with ambient oxygen to form a thin (~ 2 nm) oxide layer.This oxide layer enabled EGaIn to maintain a stable, conical shape (convenient for forming microcontacts to SAMs) while retaining the ability to deform and flow upon contacting a hard surface. Conical electrodes of EGaIn conform (at least partially) to 2 SAMs, and generate high yields of working junctions. Ga 2 O 3 /EGaIn top electrodes enable the collection of statistically significant numbers of data in convenient periods of time. The observed difference in charge transport between n-alkanethiols with odd-and even-numbers of methylenes -the "odd-even effect" -is statistically discernable using these junctions, and demonstrates that this technique is sensitive to small differences in the structure and properties of the SAM. Alkanethiols with an even number of methylenes exhibit the expected exponential decrease in current density (J) with increasing chain length, as do alkanethiols with an odd number of methylenes. This trend disappears, however, when the two datasets are analyzed together; alkanethiols with an even number of methylenes typically show higher J than homologous alkanethiols with an odd number of methylenes. The precision of the present measurements, and the statistical power of the present analysis, were only sufficient to identify, with statistical confidence, the difference between an odd and even number of methylenes with respect to J, but not with respect to the tunneling decay constant, β, or the pre-exponential factor, J 0 .3

Here, recent significant developments are reviewed in manipulating soft matter systems through the use of magnetic torque. Magnetic torque enables the orientation, assembly, and manipulation of thermally fluctuating systems in broad material fields including biomaterials, ceramic and composite precursor suspensions, polymer solutions, fluids, foams, and gels. Magnetism offers an effective, safe, and massively parallel manufacturing approach. By exploiting magnetic torque, leading soft matter researchers have demonstrated new technologies in rheology, life sciences, optics, and structural materials. Specifically, magnetic torque has been used to assemble particle suspensions, to fabricate and actuate composite materials, and to control and manipulate biological materials. In each of these applications, there are energetic limitations to magnetic torque that need to be understood and characterized. However, magnetic torque offers a promising remote‐controlled approach to creating and enabling new soft matter technologies.

This paper applies statistical methods to analyze the large, noisy datasets produced in measurements of tunneling current density (J) through self-assembled monolayers (SAMs) in large-area junctions. It describes and compares the accuracy and precision of procedures for summarizing data for individual SAMs, for comparing two or more SAMs, and for determining the parameters of the Simmons model (β and J 0). For data that contain significant numbers of outliers (i.e. most measurements of charge transport), commonly used statistical techniques-e.g. summarizing data with arithmetic mean and standard deviation, and fitting data using a linear, least-squares algorithm-are prone to large errors. The paper recommends statistical methods that distinguish between real data and artifacts, subject to the assumption that real data (J) are independent and log-normally distributed. Selecting a precise and accurate (conditional on these assumptions) method yields updated values of β and J 0 for charge transport across both odd and even n-alkanethiols (with 99% confidence intervals), and explains that the socalled odd-even effect (for n-alkanethiols on Ag) is largely due to a difference in J 0 between odd and even n-alkanethiols. This conclusion is provisional, in that it depends to some extent on the statistical model assumed, and these assumptions must be tested by future experiments.