Adsorption of dissolved molecules onto solid surfaces can be extremely sensitive to the atomic-scale properties of the solute and surface, causing difficulties for the design of fluidic systems in industrial, medical and technological applications. In this communication, we show that the Langmuir isotherm for adsorption of a small molecule to a realistic, heterogeneous surface can be predicted from atomic structures of the molecule and surface through molecular dynamics (MD) simulations. We highlight the method by studying the adsorption of dimethyl-methylphosphonate (DMMP) to amorphous silica substrates and show that subtle differences in the atomic-scale surface properties can have drastic effects on the Langmuir isotherm. The sensitivity of the method presented is sufficient to permit the optimization of fluidic devices and to determine fundamental design rules for controlling adsorption at the nanoscale.

Reducing the size of a nanofluidic channel not only creates new opportunities for high-precision manipulation of biological macromolecules, but also makes the performance of the entire nanofluidic system more susceptible to undesirable interactions between the transported biomolecules and the walls of the channel. In this manuscript, we report molecular dynamics simulations of a pressure-driven flow through a silica nanochannel that characterized, with atomic resolution, adsorption of a model protein to its surface. Although the simulated adsorption of the proteins was found to be nonspecific, it had a dramatic effect on the rate of the protein transport. To determine the relative strength of the protein–silica interactions in different adsorbed states, we simulated flow-induced desorption of the proteins from the silica surface. Our analysis of the protein conformations in the adsorbed states did not reveal any simple dependence of the adsorption strength on the size and composition of the protein–silica contact, suggesting that the heterogeneity of the silica surface may be a important factor.

Modeling the transport of solutes through fluidic systems that have adsorbing surfaces is challenging due to the range of length and time scales involved. The components of such systems typically have dimensions from hundreds of nanometers to microns, whereas adsorption of solutes is sensitive to the atomic-scale structure of the solutes and surfaces. Here, we describe an atomic-resolution Brownian dynamics method for modeling the transport of solutes through sticky nanofluidic channels. Our method can fully recreate the results of all-atom molecular dynamics simulations at a fraction of the computational cost of the latter, which makes simulations of micron-size channels at a millisecond time scale possible without losing information about the atomic-scale features of the system. We demonstrate the capability of our method by simulating the rise and fall of solute concentration in sub-micron-long sticky nanochannels, showing that the atomic-scale features of the channels’ surfaces have a dramatic effect on the kinetics of solute transport in and out of the channel. We expect our method to find applications in design and optimization of micro and nanofluidic systems for solute-specific transport and to complement existing approaches to modeling lab-on-a-chip devices by providing atomic scale information at a low computational cost.