Dmitriy V. Melnikov

Enzymatic AND Logic Gates Operated Under Conditions Characteristic of Biomedical Applications

Experimental and theoretical analyses of the lactate dehydrogenase and glutathione reductase based enzymatic AND logic gates in which the enzymes and their substrates serve as logic inputs are performed. These two systems are examples of the novel, previously unexplored class of biochemical logic gates that illustrate potential biomedical applications of biochemical logic. They are characterized by input concentrations at logic 0 and 1 states corresponding to normal and pathophysiological conditions. Our analysis shows that the logic gates under investigation have similar noise characteristics. Both significantly amplify random noise present in inputs; however, we establish that for realistic widths of the input noise distributions, it is still possible to differentiate between the logic 0 and 1 states of the output. This indicates that reliable detection of pathophysiological conditions is indeed possible with such enzyme logic systems.

Pores with Longitudinal Irregularities Distinguish Objects by Shape

The resistive-pulse technique has been used to detect and size objects which pass through a single pore. The amplitude of the ion current change observed when a particle is in the pore is correlated with the particle volume. Up to date, however, the resistive-pulse approach has not been able to distinguish between objects of similar volume but different shapes. In this manuscript, we propose using pores with longitudinal irregularities as a sensitive tool capable of distinguishing spherical and rod-shaped particles with different lengths. The ion current modulations within resulting resistive pulses carry information on the length of passing objects. The performed experiments also indicate the rods rotate while translocating, and displace an effective volume that is larger than their geometrical volume, and which also depends on the pore diameter.

Slowing down and stretching DNA with an electrically tunable nanopore in a p–n semiconductor membrane

We have studied single-stranded DNA translocation through a semiconductor membrane consisting of doped p and n layers of Si forming a p-n-junction. Using Brownian dynamics simulations of the biomolecule in the self-consistent membrane-electrolyte potential obtained from the Poisson-Nernst-Planck model, we show that while polymer length is extended more than when its motion is constricted only by the physical confinement of the nanopore. The biomolecule elongation is particularly dramatic on the n-side of the membrane where the lateral membrane electric field restricts (focuses) the biomolecule motion more than on the p-side. The latter effect makes our membrane a solid-state analog of the α-hemolysin biochannel. The results indicate that the tunable local electric field inside the membrane can effectively control dynamics of a DNA in the channel to either momentarily trap, slow down or allow the biomolecule to translocate at will.

Filtering of Nanoparticles with Tunable Semiconductor Membranes

Translocation dynamics of nanoparticles permeating through the nanopore in an n-Si semiconductor membrane is studied. With the use of Brownian Dynamics to describe the motion of the charged nanoparticles in the self-consistent membrane-electrolyte electrostatic potential, we asses the possibility of using our voltage controlled membrane for the macroscopic filtering of the charged nanoparticles. The results indicate that the tunable local electric field inside the membrane can effectively control interaction of a nanoparticle with the nanopore by either blocking its passage or increasing the translocation rate. The effect is particularly strong for larger nanoparticles due to their stronger interaction with the membrane while in the nanopore. By extracting the membrane permeability from our microsopic simulations, we compute the macroscopic sieving factors and show that the size selectivity of the membrane can be tuned by the applied voltage.

Charged particle separation by an electrically tunable nanoporous membrane

We study the applicability of an electrically tunable nanoporous semiconductor membrane for the separation of nanoparticles by charge. We show that this type of membrane can overcome one of the major shortcomings of nanoporous membrane applications for particle separation: the compromise between membrane selectivity and permeability. The computational model that we have developed describes the electrostatic potential distribution within the system and tracks the movement of the filtered particle using Brownian dynamics while taking into consideration effects from dielectrophoresis, fluid flow, and electric potentials. We found that for our specific pore geometry, the dielectrophoresis plays a negligible role in the particle dynamics. By comparing the results for charged and uncharged particles, we show that for the optimal combination of applied electrolyte and membrane biases the same membrane can effectively separate same-sized particles based on charge with a difference of up to 3 times in membrane permeability.

Protein permeation through an electrically tunable membrane

Protein filtration is important in many fields of science and technology such as medicine, biology, chemistry, and engineering. Recently, protein separation and filtering with nanoporous membranes has attracted interest due to the possibility of fast separation and high throughput volume. This, however, requires understanding of the proteins dynamics inside and in the vicinity of the nanopore. In this work, we utilize a Brownian dynamics approach to study the motion of the model protein insulin in the membrane-electrolyte electrostatic potential. We compare the results of the atomic model of the protein with the results of a coarse-grained and a single-bead model, and find that the coarse-grained representation of protein strikes the best balance between the accuracy of the results and the computational effort required. Contrary to common belief, we find that to adequately describe the protein, a single-bead model cannot be utilized without a significant effort to tabulate the simulation parameters. Similar to results for nanoparticle dynamics, our findings also indicate that the electric field and the electro-osmotic flow due to the applied membrane and electrolyte biases affect the capture and translocation of the biomolecule by either attracting or repelling it to or from the nanopore. Our computational model can also be applied to other types of proteins and separation conditions.

Exchange interaction and stability diagram of coupled quantum dots in magnetic fields

The charge stability diagram for two coupled quantum dots containing up to two electrons is computed in magnetic fields. One- and two-particle Schroedinger equations are solved by exact diagonalization to obtain the chemical potentials and exchange energy in these systems. By analyzing the chemical potentials variation with external biases and magnetic fields, it is possible to distinguish between the weak and strong inter-dot couplings. The variation of the chemical potential curvatures and the double-triple point separations in the stability diagrams confirms the inter-dot coupling decrease with increasing magnetic fields. The computed exchange energies are also found to be significantly smaller than the values estimated from the stability diagram.

Electro-osmotic flow through nanopores in thin and ultrathin membranes

We theoretically study how the electro-osmotic fluid velocity in a charged cylindrical nanopore in a thin solid state membrane depends on the pores geometry, membrane charge, and electrolyte concentration. We find that when the pores length is comparable to its diameter, the velocity profile develops a concave shape with a minimum along the pore axis unlike the situation in very long nanopores with a maximum velocity along the central pore axis. This effect is attributed to the induced pressure along the nanopore axis due to the fluid flow expansion and contraction near the exit or entrance to the pore and to the reduction of electric field inside the nanopore. The induced pressure is maximal when the pores length is about equal to its diameter while decreasing for both longer and shorter nanopores. A model for the fluid velocity incorporating these effects is developed and shown to be in a good agreement with numerically computed results.

Non-monotonic variation of the exchange energy in double elliptic quantum dots

We study the properties of a few-electron system confined in coupled elongated quantum dots (QDs) using a model Gaussian potential and the numerical exact diagonalization technique. In the absence of magnetic fields, as the aspect ratio r between the QD extensions in the directions perpendicular and parallel to the coupling directions increases, the exchange energy exhibits a sharp variation at the specific value r = 3.9, before (after) which the exchange energy increases (declines). The sharp variation occurs because of a sudden change in the single-particle configuration of the triplet state. The stability region with one electron in each of the QDs is found to shrink, and finally vanishes as it becomes progressively easier to localize both electrons into the QD with the lower electron potential energy. For r>3.9, the first singlet-triplet transition shifts to a small magnetic field.

Nanopore gating with an anchored polymer in a switching electrolyte bias

In this work, we theoretically study the interaction between a solid state membrane equipped with a nanopore and a tethered, negatively charged polymer chain subjected to a time-dependent applied electrolyte bias. In order to describe the movement of the chain in the biomolecule-membrane system immersed in an electrolyte solution, Brownian dynamics is used. We show that we can control the polymers equilibrium position with various applied electrolyte biases: for a sufficiently positive bias, the chain extends inside the pore, and the removal of the bias causes the polymer to leave the pore. Corresponding to a driven process, we find that the time it takes for a biomolecular chain to enter and extend into a nanopore in a positive bias almost increases linearly with chain length while the amount of time it takes for a polymer chain to escape the nanopore is mainly governed by diffusion.