Related papers: Substrate-assisted 2D DNA lattices and algorithmic…
Bottom-up fabrication of inorganic nanostructures is emerging as an alternative to classical top-down approaches, offering precise nanometer-scale control at relatively low cost and effort. In particular, DNA nanostructures provide…
By exploring a recent model [Palmeri, J., M. Manghi, and N. Destainville. 2007. Phys. Rev. Lett. 99:088103] where DNA bending elasticity, described by the wormlike chain model, is coupled to base-pair denaturation, we demonstrate that small…
We show that atomically thin molybdenum disulfide (MoS2) crystals can grow without any underlying substrates into free-standing atomically-thin layers, maintaining their planar 2D form. Using this property, we present a new mechanism for 2D…
To increase the training speed of distributed learning, recent years have witnessed a significant amount of interest in developing both synchronous and asynchronous distributed stochastic variance-reduced optimization methods. However, all…
Formation of random network of DNA strands is simulated on a two-dimensional triangular lattice. We investigate the size distribution of pores in the network. The results are interpreted within theory of percolation on Bethe lattice.
In this work, we show that by varying the experimental conditions, the driving amplitude, a dynamic force microscope allows DNA properties to be selectively imaged. The substrate on which the DNA is fixed is a silica surface grafted with…
We propose the use of two-dimensional photonic crystals with engineered defects for the generation of an arbitrary-profile beam from a focused input beam. The cylindrical harmonics expansion of complex-source beams is derived and used to…
Organic capping ligands can selectively bind to crystal facets to modulate growth kinetics and are important in chemical synthesis of inorganic nanocrystals. Using the capping ligands for shape-controlled growth of colloidal crystals is…
Strongly correlated materials exhibit exotic electronic states arising from the strong correlation between electrons. Dimensionality provides a tuning knob because thinning down to atomic thickness reduces screening effects and enhances…
Robot-assisted 3D printing has drawn a lot of attention by its capability to fabricate curved layers that are optimized according to different objectives. However, the support generation algorithm based on a fixed printing direction for…
In this work, we investigate a challenging problem, which has been considered to be an important criterion in designing codewords for DNA computing purposes, namely secondary structure avoidance in single-stranded DNA molecules. In short,…
The interaction between light and matter can be controlled efficiently by structuring materials at a length scale shorter than the wavelength of interest. With the goal to build optical devices that operate at the nanoscale, plasmonics has…
We propose a lattice-theoretic framework for modulo sampling of multidimensional bandlimited signals. Standard modulo analog-to-digital converters (ADCs) fold the signal component-wise into a square domain, reducing the recovery problem to…
Crystal generative models have shown rapid progress for accelerating the discovery of bulk, periodic materials. However, many material systems such as 2D superconductors, thin film semiconductors, and catalytic surfaces are diperiodic,…
DNA-coated colloids can self-assemble into an incredible diversity of crystal structures, but applications of this technology are limited by poor understanding and control over the dynamical crystallization pathways. To address this…
Two-dimensional (2D) materials are poised to revolutionize current solid-state technology with their extraordinary properties. Yet, the primary challenge remains their scalable production. While there have been significant advancements,…
We devise a new 1D atomistic scale model of vicinal growth based on Cellular Automaton. In it the step motion is realized by executing the automaton rule prescribing how adatoms incorporate into the vicinal crystal. Time increases after…
Spiking neural networks (SNNs) with a lattice architecture are introduced in this work, combining several desirable properties of SNNs and self-organized maps (SOMs). Networks are trained with biologically motivated, unsupervised learning…
This work presents a novel lattice-based methodology for incorporating multidimensional constraints into continuous decision variables within a genetic algorithm (GA) framework. The proposed approach consolidates established transcription…
A chemical-free technique for fabricating submicron complex oxide structures has been developed based on selective epitaxial growth. The crystallinity and hence the conductivity of the complex oxide is inhibited by amorphous SrTiO3 (STO).…