57,706 research outputs found
Nano-scale reservoir computing
This work describes preliminary steps towards nano-scale reservoir computing
using quantum dots. Our research has focused on the development of an
accumulator-based sensing system that reacts to changes in the environment, as
well as the development of a software simulation. The investigated systems
generate nonlinear responses to inputs that make them suitable for a physical
implementation of a neural network. This development will enable
miniaturisation of the neurons to the molecular level, leading to a range of
applications including monitoring of changes in materials or structures. The
system is based around the optical properties of quantum dots. The paper will
report on experimental work on systems using Cadmium Selenide (CdSe) quantum
dots and on the various methods to render the systems sensitive to pH, redox
potential or specific ion concentration. Once the quantum dot-based systems are
rendered sensitive to these triggers they can provide a distributed array that
can monitor and transmit information on changes within the material.Comment: 8 pages, 9 figures, accepted for publication in Nano Communication
Networks, http://www.journals.elsevier.com/nano-communication-networks/. An
earlier version was presented at the 3rd IEEE International Workshop on
Molecular and Nanoscale Communications (IEEE MoNaCom 2013
Microfluidic-based Bacterial Molecular Computing on a Chip
Biocomputing systems based on engineered bacteria can lead to novel tools for environmental monitoring and detection of metabolic diseases. In this paper, we propose a Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. The computing can be flexibly integrated into the chip, but we focus on engineered bacterial AND Boolean logic gate and ON-OFF switch sensors that produces secondary signals to change the pH and dissolved oxygen concentrations. We present a prototype with experimental results that shows the electrochemical sensors can detect small pH and dissolved oxygen concentration changes created by the engineered bacterial populations’ molecular signals. Additionally, we present a theoretical model analysis of the BMCoC computation reliability when subjected to unwanted effects, i.e., molecular signal delays and noise, and electrochemical sensors threshold settings that are based on either standard or blind detectors. Our numerical analysis found that the variations in the production delay and the molecular output signal concentration can impact on the computation reliability for the AND logic gate and ON-OFF switch. The molecular communications of synthetic engineered cells for logic gates integrated with sensing systems can lead to a new breed of biochips that can be used for numerous diagnostic applications
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Digital Sensing and Molecular Computation by an Enzyme-Free DNA Circuit.
DNA circuits form the basis of programmable molecular systems capable of signal transduction and algorithmic computation. Some classes of molecular programs, such as catalyzed hairpin assembly, enable isothermal, enzyme-free signal amplification. However, current detection limits in DNA amplification circuits are modest, as sensitivity is inhibited by signal leakage resulting from noncatalyzed background reactions inherent to the noncovalent system. Here, we overcome this challenge by optimizing a catalyzed hairpin assembly for single-molecule sensing in a digital droplet assay. Furthermore, we demonstrate digital reporting of DNA computation at the single-molecule level by employing ddCHA as a signal transducer for simple DNA logic gates. By facilitating signal transduction of molecular computation at pM concentration, our approach can improve processing density by a factor of 104 relative to conventional DNA logic gates. More broadly, we believe that digital molecular computing will broaden the scope and efficacy of isothermal amplification circuits within DNA computing, biosensing, and signal amplification in general
Application of compressed sensing to the simulation of atomic systems
Compressed sensing is a method that allows a significant reduction in the
number of samples required for accurate measurements in many applications in
experimental sciences and engineering. In this work, we show that compressed
sensing can also be used to speed up numerical simulations. We apply compressed
sensing to extract information from the real-time simulation of atomic and
molecular systems, including electronic and nuclear dynamics. We find that for
the calculation of vibrational and optical spectra the total propagation time,
and hence the computational cost, can be reduced by approximately a factor of
five.Comment: 7 pages, 5 figure
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