Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive

Atomistic molecular simulations are a powerful way to make quantitative predictions, but the accuracy of these predictions depends entirely on the quality of the forcefield employed. While experimental measurements of fundamental physical properties offer a straightforward approach for evaluating forcefield quality, the bulk of this information has been tied up in formats that are not machine-readable. Compiling benchmark datasets of physical properties from non-machine-readable sources require substantial human effort and is prone to accumulation of human errors, hindering the development of reproducible benchmarks of forcefield accuracy. Here, we examine the feasibility of benchmarking atomistic forcefields against the NIST ThermoML data archive of physicochemical measurements, which aggregates thousands of experimental measurements in a portable, machine-readable, self-annotating format. As a proof of concept, we present a detailed benchmark of the generalized Amber small molecule forcefield (GAFF) using the AM1-BCC charge model against measurements (specifically bulk liquid densities and static dielectric constants at ambient pressure) automatically extracted from the archive, and discuss the extent of available data. The results of this benchmark highlight a general problem with fixed-charge forcefields in the representation low dielectric environments such as those seen in binding cavities or biological membranes

Nucleobase-functionalized graphene nanoribbons for accurate high-speed DNA sequencing

We propose a water-immersed nucleobase-functionalized suspended graphene nanoribbon as an intrinsically selective device for nucleotide detection. The proposed sensing method combines Watson-Crick selective base pairing with graphene's capacity for converting anisotropic lattice strain to changes in an electrical current at the nanoscale. Using detailed atomistic molecular dynamics simulations, we study sensor operation at ambient conditions. We combine simulated data with theoretical arguments to estimate the levels of measurable electrical signal variation in response to strains and determine that the proposed sensing mechanism shows significant promise for realistic DNA sensing devices without the need for advanced data processing, or highly restrictive operational conditions

Improvement of Quality in Publication of Experimental Thermophysical Property Data: Challenges, Assessment Tools, Global Implementation, and Online Support

Article on the improvement of quality in the publication of experimental thermophysical property data

A MoS2-Based Capacitive Displacement Sensor for DNA Sequencing

We propose an aqueous functionalized molybdenum disulfide nanoribbon suspended over a solid electrode as a capacitive displacement sensor aimed at determining the DNA sequence. The detectable sequencing events arise from the combination of Watson Click base-pairing, one of nature's most basic lock-and-key binding mechanisms, with the ability of appropriately sized atomically thin membranes to flex substantially in response to subnanonewton forces. We employ carefully designed numerical simulations and theoretical estimates to demonstrate excellent (79% to 86%) raw target detection accuracy at similar to 70 million bases per second and electrical measurability of the detected events. In addition, we demonstrate reliable detection of repeated DNA motifs. Finally, we argue that the use of a nanoscale opening (nanopore) is not requisite for the operation of the proposed sensor and present a simplified sensor geometry without the nanopore as part of the sensing element. Our results, therefore, potentially suggest a realistic inherently base-specific, high throughput electronic DNA sequencing device as a cost-effective de novo alternative to the existing methods