A Sticker-Based Model for DNA Computation

Vve introduce a new model of molecular computation that we call the sticker model.Like many previous proposals it makes use of DNA strands as the physical substrate in which information is represented and of separation by hybridization as a central mechanism.However , unlike previous models, the stickers model has a random access memory that requires no strand extension, uses no enzymes, and (at least in theory) its materials are reusable.The paper describes computation under the stickers model and discusses possible means for physically implementing each operation.We go on to propose a specific machine architecture for implementing the stickers model as a microprocessor-controlled parallel robotic workstation.Finally, we discuss several methods for achieving acceptable overall error rates for a computation using basic operations that are error prone.In t he course of this development a number of previous general concerns about molecular computation [36, 2 0 , 24 ) are addressed.First, it is clear that general-purpose algorithms can be implemented by DNA-based computers, potentially solving a " .. •ide class of search problems.Second, we find that there are challenging problems, for which only modest volumes of DNA should suffice.Third, we demonstrate that the formation and breaking of covalent bonds is not intrinsic to DNA-based computation.This means that costly and short-lived materials such as enzymes are not necessary, nor are energetically costly processes such as PCR.Fourth , \ .... e show that a single essential biotechnology, sequence-specific separation , suffices for constructing a general-purpose molecular computer.Fifth, we illustrate that separation errors can theoretically be reduced to tolerable levels by invoking a trade-off between time, space, and error rates at the level of algorithm design; we also outline several specific ways in which this can be done and present numerical calculations of their per formance.Despite these encouraging theoretical advances , we emphasize that sub-stantial engineering challenges remain at almost all stages and that the ultimate success or failure of DNA computing will certainly depend on whether t.hese challenges can be met in laboratory investigations.

The ability to manipulate crystal structures using kinetic control is of broad interest because it enables the design of materials with structures, compositions, and morphologies that may otherwise be unattainable. Herein, we report the low-temperature structural transformation of bulk inorganic crystals driven by hard-soft acid-base (HSAB) chemistry. We show that the three-dimensional framework K2Sb8Q13 and layered KSb5Q8 (Q = S, Se, and Se/S solid solutions) compounds transform to one-dimensional Sb2Q3 nano/microfibers in N2H4·H2O solution by releasing Q2- and K+ ions. At 100 °C and ambient pressure, a transformation process takes place that leads to significant structural changes in the materials, including the formation and breakage of covalent bonds between Sb and Q. Despite the insolubility of the starting crystals in N2H4·H2O under the given conditions, the mechanism of this transformation can be rationalized by applying the HSAB principle. By adjusting factors such as the reactants' acid/base properties, temperature, and pressure, the process can be controlled, allowing for the achievement of a wide range of optical band gaps (ranging from 1.14 to 1.59 eV) while maintaining the solid solution nature of the anion sublattice in the Sb2Q3 nanofibers.

DNA computing, or more generally molecular computing, is an exciting research area at the intersection of mathematics, computer science and molecular biology. Research in DNA computing can be roughly divided in two streams: DNA computing in vitro and in vivo. The former is concerned with building (specialized) DNA-based computers in test tubes, while the latter is concerned with implementing some computational components in living cells, as well as with studying the computational processes taking place in the living cells.

In the past few years since Adleman’s pioneering work on solving the HPP(Hamiltonian Path Problem) with a DNA-based computer [1], many algorithms have been designed on solving NP problems. Most of them are in the solution bases and need some error correction or tolerance technique in order to get good and correct results [3] [7] [9] [11] [21] [22]. The advantage of surface-based DNA computing technique, with very low error rate, has been shown many times [12] [18] [17] [20] over the solution based DNA computing, but this technique has not been widely used in the DNA computer algorithms design. This is mainly due to the restriction of the surface-based technique comparing with those methods using the DNA strands in solutions. In this paper, we introduce a surface-based DNA computing algorithm for solving a hard computation problem: expansion of symbolic determinants given their patterns of zero entries. This problem is well-known for its exponential difficulty. It is even more difficult than evaluating determinants whose entries are merely numerical [15]. We will show how this problem can be solved with the low error rate surface-based DNA computer using our naive algorithm.

Edible films derived from starch have been proposed as packaging materials. However, they may suffer physicochemical changes due to a variety of factors, such as pulsed light (PL) treatments. In this study, the effect of PL treatment as a crosslinking method on films made from cassava (Manihot esculenta C.) and taro (Colocasia esculenta L. Schott) starch, plasticized with glycerol was evaluated. The average molecular weight, contact angle, moisture content, X-ray diffraction pattern, color, and mechanical and microstructural properties were evaluated. Films subjected to PL showed deterioration compared with control films as demonstrated by an increase in the contact angle, surface roughness, and crystallinity, and a decrease in the tensile strength, transparency, and water content, independent of the amylose content of the starches evaluated. Finally, the surface properties of these materials are defined by intermolecular interactions such as van der Waals-type force interactions (hydrogen bond), new bonds (crosslinking) formed between the biopolymeric chains (starch), and by breakage of covalent bonds.

Construction of sacrificial bonds and hybrid networks in EPDM rubber towards mechanical performance enhancement

A new polarizable water model is developed for molecular dynamics (MD) simulations of the proton transport process. The interatomic potential model has three important submodels corresponding to electrostatic interactions, making and breaking of covalent bonds, and treatment of electron exchange and correlation through a van der Waals potential. A polarizable diffuse charge density function was used to describe Coulombic interactions between atoms. Most of the model parameters were obtained from ab initio data for a lone water molecule. Molecules respond realistically to their electrochemical environment by the use of coupled fluctuating charge and fluctuating dipole dynamics, which controlled the charge density. The main purpose of the work is to develop a general model and framework for future studies, though some validation work was performed here. We applied the model to a MD simulation study of bulk properties of liquid water at room temperature and model gave good agreement with thermodynamic and transport properties at the same conditions. The model was then applied to a preliminary study of proton transfer, in which multiple proton transfer events were observed, though the rate of proton transfer was under-predicted by a factor of 5.

All biochemical reactions directly involve structural changes that may occur over a very wide range of timescales from femtoseconds to seconds. Understanding the mechanism of action thus requires determination of both the static structures of the macromolecule involved and short-lived intermediates between reactant and product. This requires either freeze-trapping of intermediates, for example by cryo-electron microscopy, or direct determination of structures in active systems at near-physiological temperature by time-resolved X-ray crystallography. Storage ring X-ray sources effectively cover the time range down to around 100 ps that reveal tertiary and quaternary structural changes in proteins. The briefer pulses emitted by hard X-ray free electron laser sources extend that range to femtoseconds, which covers critical chemical reactions such as electron transfer, isomerization, breaking of covalent bonds, and ultrafast structural changes in light-sensitive protein chromophores and their protein environment. These reactions are exemplified by the time-resolved X-ray studies by two groups of the FAD-based DNA repair enzyme, DNA photolyase, over the time range from 1 ps to 100 μs.

The chemistry of Sr 2+ in association with propanol clusters

In flatly deposited a‐Se films photoexpansion has been found due to covalent bond breaking during the electron excitation process, and simultaneously photocontraction due to inter‐chain bond formation in the case of hole creation. Determination and explanation of the microscopic photoinduced changes in amorphous selenium structure was the purpose of this investigation. For this purpose Raman spectra measurements have been carried out on flatly amorphous selenium (a‐Se). Reversible covalent bond breaking process was found as a consequence of band gap light illumination in the experiments. Our bond breaking model obtained using Molecular Dynamics simulations has been confirmed experimentally by Raman spectroscopy (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

The process of designing a set of good DNA sequences is an essential problem and one of the most practical and important research topics in DNA-based computing. In this field of research, a DNA sequence design problem is defined as a multi-objective problem, and it is evaluated using four objective functions, which are h-measure, similarity, continuity, and hairpin. In addition, two constraints, GC content and melting temperature, are used to maintain uniform chemical characteristics of the sequences. In the authors' previous research, ant colony system (ACS) was proposed to solve the DNA sequence design problem and the Watson-Crick base pair ÄGo37 was used as the distance between nodes in the computational model of DNA sequence design. In the current study, the use of other parameters, namely, unified near estneighbour thermodynamic parameters, are investigated and the result is compared with the previous work.

On the computational power of DNA

The process of designing a set of good DNA sequences is an essential problem and one of the most practical and important research topics in DNA-based computing. In this field of research, a DNA sequence design problem is defined as a multi-objective problem, and it is evaluated using four objective functions, which are h-measure, similarity, continuity, and hairpin. In addition, two constraints, GC content and melting temperature, are used to maintain uniform chemical characteristics of the sequences. In the authors' previous research, ant colony system (ACS) was proposed to solve the DNA sequence design problem and the Watson-Crick base pair ΔGo37 was used as the distance between nodes in the computational model of DNA sequence design. In the current study, the use of other parameters, namely, Breslauer nearest-neighbour thermodynamic parameters are investigated and the result is compared with the previous work.

Exact exchange contributions significantly affect electronic states, influencing covalent bond formation and breaking. Hybrid density functional approximations, which average exact exchange admixtures empirically, have achieved success but fall short of high-level quantum chemistry accuracy due to delocalization errors. We propose adaptive hybrid functionals, generating optimal exact exchange admixture ratios on the fly using data-efficient quantum machine learning models with negligible overhead. The adaptive Perdew-Burke-Ernzerhof hybrid density functional (aPBE0) improves energetics, electron densities, and HOMO-LUMO gaps in QM9, QM7b, and GMTKN55 benchmark datasets. A model uncertainty-based constraint reduces the method smoothly to PBE0 in extrapolative regimes, ensuring general applicability with limited training. By tuning exact exchange fractions for different spin states, aPBE0 effectively addresses the spin gap problem in open-shell systems such as carbenes. We also present a revised QM9 (revQM9) dataset with more accurate quantum properties, including stronger covalent binding, larger bandgaps, more localized electron densities, and larger dipole moments.

In the Mooser-Pearson diagram, binary ionic compoundss form into nonpolar symmetrical structures with high coordination numbers, while wurtzite structures should appear in the covalent region. Their tetrahedral bonding configurations break the inversion symmetry, with polarizations almost unswitchable due to the high barriers of abrupt breaking and reformation of covalent bonds. Here, through first-principles calculations, we find some exceptional cases of highly ionic ferroelectric binary salts such as lithium halides, which may form into wurtzite structures with covalent-like sp3 bondings, and the origin of these abnormal formations is clarified. Their high polarizations induced by symmetry breaking are switchable, with much smoother switching pathway refrained from abrupt bond breaking due to the long-range feature of Coulomb interactions. These covalent-like ionic bondings do reduce not only their ferroelectric switching barriers but also the phase transition barriers between polar and nonpolar phases, rendering high performance in applications such as nonvolatile memory and energy storage.