Dynamic behaviour of the silica-water-bio electrical double layer in the presence of a divalent electrolyte.

Electronic devices are becoming increasingly used in chemical- and bio-sensing applications and therefore understanding the silica-electrolyte interface at the atomic scale is becoming increasingly important. For example, field-effect biosensors (BioFETs) operate by measuring perturbations in the electric field produced by the electrical double layer due to biomolecules binding on the surface. In this paper, explicit-solvent atomistic calculations of this electric field are presented and the structure and dynamics of the interface are investigated in different ionic strengths using molecular dynamics simulations. Novel results from simulation of the addition of DNA molecules and divalent ions are also presented, the latter of particular importance in both physiological solutions and biosensing experiments. The simulations demonstrated evidence of charge inversion, which is known to occur experimentally for divalent electrolyte systems. A strong interaction between ions and DNA phosphate groups was demonstrated in mixed electrolyte solutions, which are relevant to experimental observations of device sensitivity in the literature. The bound DNA resulted in local changes to the electric field at the surface; however, the spatial- and temporal-mean electric field showed no significant change. This result is explained by strong screening resulting from a combination of strongly polarised water and a compact layer of counterions around the DNA and silica surface. This work suggests that the saturation of the Stern layer is an important factor in determining BioFET response to increased salt concentration and provides novel insight into the interplay between ions and the EDL.

Molecular dynamics simulation of potentiometric sensor response: the effect of biomolecules, surface morphology and surface charge.

The silica-water interface is critical to many modern technologies in chemical engineering and biosensing. One technology used commonly in biosensors, the potentiometric sensor, operates by measuring the changes in electric potential due to changes in the interfacial electric field. Predictive modelling of this response caused by surface binding of biomolecules remains highly challenging. In this work, through the most extensive molecular dynamics simulation of the silica-water interfacial potential and electric field to date, we report a novel prediction and explanation of the effects of nano-morphology on sensor response. Amorphous silica demonstrated a larger potentiometric response than an equivalent crystalline silica model due to increased sodium adsorption, in agreement with experiments showing improved sensor response with nano-texturing. We provide proof-of-concept that molecular dynamics can be used as a complementary tool for potentiometric biosensor response prediction. Effects that are conventionally neglected, such as surface morphology, water polarisation, biomolecule dynamics and finite-size effects, are explicitly modelled.

Dissociation dynamics of ethylene molecules on a Ni cluster using ab initio molecular dynamics simulations.

The atomistic mechanism of dissociative adsorption of ethylene molecules on a Ni cluster is investigated by ab initio molecular-dynamics simulations. The activation free energy to dehydrogenate an ethylene molecule on the Ni cluster and the corresponding reaction rate is estimated. A remarkable finding is that the adsorption energy of ethylene molecules on the Ni cluster is considerably larger than the activation free energy, which explains why the actual reaction rate is faster than the value estimated based on only the activation free energy. It is also found from the dynamic simulations that hydrogen molecules and an ethane molecule are formed from the dissociated hydrogen atoms, whereas some exist as single atoms on the surface or in the interior of the Ni cluster. On the other hand, the dissociation of the C-C bonds of ethylene molecules is not observed. On the basis of these simulation results, the nature of the initial stage of carbon nanotube growth is discussed.