Identifying SARS-CoV-2 Variants Using Single-Molecule Conductance Measurements.

The global COVID-19 pandemic has highlighted the need for rapid, reliable, and efficient detection of biological agents and the necessity of tracking changes in genetic material as new SARS-CoV-2 variants emerge. Here, we demonstrate that RNA-based, single-molecule conductance experiments can be used to identify specific variants of SARS-CoV-2. To this end, we (i) select target sequences of interest for specific variants, (ii) utilize single-molecule break junction measurements to obtain conductance histograms for each sequence and its potential mutations, and (iii) employ the XGBoost machine learning classifier to rapidly identify the presence of target molecules in solution with a limited number of conductance traces. This approach allows high-specificity and high-sensitivity detection of RNA target sequences less than 20 base pairs in length by utilizing a complementary DNA probe capable of binding to the specific target. We use this approach to directly detect SARS-CoV-2 variants of concerns B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and B.1.1.529 (Omicron) and further demonstrate that the specific sequence conductance is sensitive to nucleotide mismatches, thus broadening the identification capabilities of the system. Thus, our experimental methodology detects specific SARS-CoV-2 variants, as well as recognizes the emergence of new variants as they arise.

Performance analysis of DNA crossbar arrays for high-density memory storage applications.

Deoxyribonucleic acid (DNA) has emerged as a promising building block for next-generation ultra-high density storage devices. Although DNA has high durability and extremely high density in nature, its potential as the basis of storage devices is currently hindered by limitations such as expensive and complex fabrication processes and time-consuming read-write operations. In this article, we propose the use of a DNA crossbar array architecture for an electrically readable read-only memory (DNA-ROM). While information can be 'written' error-free to a DNA-ROM array using appropriate sequence encodings its read accuracy can be affected by several factors such as array size, interconnect resistance, and Fermi energy deviations from HOMO levels of DNA strands employed in the crossbar. We study the impact of array size and interconnect resistance on the bit error rate of a DNA-ROM array through extensive Monte Carlo simulations. We have also analyzed the performance of our proposed DNA crossbar array for an image storage application, as a function of array size and interconnect resistance. While we expect that future advances in bioengineering and materials science will address some of the fabrication challenges associated with DNA crossbar arrays, we believe that the comprehensive body of results we present in this paper establishes the technical viability of DNA crossbar arrays as low power, high-density storage devices. Finally, our analysis of array performance vis-à-vis interconnect resistance should provide valuable insights into aspects of the fabrication process such as proper choice of interconnects necessary for ensuring high read accuracies.

A machine learning approach for accurate and real-time DNA sequence identification.

BACKGROUND: The all-electronic Single Molecule Break Junction (SMBJ) method is an emerging alternative to traditional polymerase chain reaction (PCR) techniques for genetic sequencing and identification. Existing work indicates that the current spectra recorded from SMBJ experimentations contain unique signatures to identify known sequences from a dataset. However, the spectra are typically extremely noisy due to the stochastic and complex interactions between the substrate, sample, environment, and the measuring system, necessitating hundreds or thousands of experimentations to obtain reliable and accurate results. RESULTS: This article presents a DNA sequence identification system based on the current spectra of ten short strand sequences, including a pair that differs by a single mismatch. By employing a gradient boosted tree classifier model trained on conductance histograms, we demonstrate that extremely high accuracy, ranging from approximately 96 % for molecules differing by a single mismatch to 99.5 % otherwise, is possible. Further, such accuracy metrics are achievable in near real-time with just twenty or thirty SMBJ measurements instead of hundreds or thousands. We also demonstrate that a tandem classifier architecture, where the first stage is a multiclass classifier and the second stage is a binary classifier, can be employed to boost the single mismatched pair's identification accuracy to 99.5 %. CONCLUSIONS: A monolithic classifier, or more generally, a multistage classifier with model specific parameters that depend on experimental current spectra can be used to successfully identify DNA strands.

An Investigation of a (Vinylbenzyl) Trimethylammonium and N-Vinylimidazole-Substituted Poly (Vinylidene Fluoride-Co-Hexafluoropropylene) Copolymer as an Anion-Exchange Membrane in a Lignin-Oxidising Electrolyser.

Electrolysis is seen as a promising route for the production of hydrogen from water, as part of a move to a wider "hydrogen economy". The electro-oxidation of renewable feedstocks offers an alternative anode couple to the (high-overpotential) electrochemical oxygen evolution reaction for developing low-voltage electrolysers. Meanwhile, the exploration of new membrane materials is also important in order to try and reduce the capital costs of electrolysers. In this work, we synthesise and characterise a previously unreported anion-exchange membrane consisting of a fluorinated polymer backbone grafted with imidazole and trimethylammonium units as the ion-conducting moieties. We then investigate the use of this membrane in a lignin-oxidising electrolyser. The new membrane performs comparably to a commercially-available anion-exchange membrane (Fumapem) for this purpose over short timescales (delivering current densities of 4.4 mA cm-2 for lignin oxidation at a cell potential of 1.2 V at 70 °C during linear sweep voltammetry), but membrane durability was found to be a significant issue over extended testing durations. This work therefore suggests that membranes of the sort described herein might be usefully employed for lignin electrolysis applications if their robustness can be improved.

Cation-Exchange Membrane with Low Frictional Coefficient and High Limiting Current Density for Energy-Efficient Water Desalination.

A sulfonated poly(ether ether ketone) (SPEEK) and phosphorylated graphene oxide (PGO) composite of a cation-exchange membrane with low frictional coefficient and high limiting current density has been reported for water desalination by rapid electrodialysis. The incorporation of PGO in the membrane matrix showed a significant impact on the macroscopic properties, counterion frictional coefficient, and performance of the membrane. A well-optimized SPEEK/PGO-8 (8% PGO content, w/w) membrane showed improved conductivity (4.15 × 10-2 S cm-1) and permselectivity (87%), and excellent stabilities (thermal, mechanical, and chemical) because of cherished polymer-PGO (filler) interaction via H-bonding. The efficiency of the SPEEK/PGO-8 membrane was also evaluated for the desalination of brackish water near limiting current density (I lim). Ion concentration polarization (ICP) was assessed by i-V curves, and below I lim, water splitting or change in product water pH was ruled out. While above I lim (10.5 mA cm-2), ICP was significant and could be finally tuned with applied current density for producing desalinated water with a desired pH. Furthermore, improved I lim, high current efficiency (82.9%), and low energy consumption (7.9 kWh kg-1 of the salt removed) of the SPEEK/PGO-8 membrane during electrodialysis provide a broad current window for efficient and rapid water desalination/purification.

2-Acrylamido-2-methyl-1-propanesulfonic Acid Grafted Poly(vinylidene fluoride-co-hexafluoropropylene)-Based Acid-/Oxidative-Resistant Cation Exchange for Membrane Electrolysis.

For developing acid-/oxidative-resistant aliphatic-polymer-based cation-exchange membrane (CEM), macromolecular modification of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) was carried out by controlled chemical grafting of 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS). To introduce the unsaturation suitable for chemical grafting, dehydrofluorination of commercially available PVDF-co-HFP was achieved under alkaline medium. Sulfonated copolymer (SCP) was prepared by the free radical copolymerization of dehydofluorinated PVDF-co-HFP (DHPVDF-co-HFP) and AMPS in the presence of free radical initiator. Prepared SCP-based CEMs were analyzed for their morphological characteristics, ion-exchange capacity (IEC), water uptake, conductivity, and stabilities (mechanical, chemical, and thermal) in comparison with state-of-art Nafion117 membrane. High bound water content avoids the membrane dehydration, and most optimal (SCP-1.33) membrane exhibited about ∼2.5-fold high bound water content in comparison with that of Nafion117 membrane. Bunsen reaction of iodine-sulfur (I-S) was successfully performed by direct-contact-mode membrane electrolysis in a two-compartment electrolytic cell using different SCP membranes. High current efficiency (83-99%) confirmed absence of any side reaction and 328.05 kJ mol-H2(-1) energy was required for to produce 1 mol of H2 by electrolytic cell with SCP-1.33 membrane. In spite of low conductivity for reported SCP membrane in comparison with that of Nafion117 membrane, SCP-1.33 membrane was assessed as suitable candidate for electrolysis because of its low-cost nature and excellent stabilities in highly acidic environment may be due to partial fluorinated segments in the membrane structure.