pH-Controlled enzymatic computing for digital circuits and neural networks.

Unconventional computing paradigms explore new methods for processing information beyond the capabilities of traditional electronic architectures. In this work, we present our approach to digital computation through enzymatic reactions in chemically buffered environments. A key aspect of this approach is its reliance on pH-sensitive enzymatic reactions, with the direction of the reaction controlled by maintaining pH levels within a specific range. When the pH crosses a defined threshold, the reaction moves forward and vice versa, akin to the switching action of electronic switches in digital circuits. The binary signals (0 and 1) are encoded as different concentrations of strong acids or bases, offering a bio-inspired method for computation. The final readout is done using UV-vis spectroscopy after applying detection reactions to indicate whether the output is 1 (indicated by the presence of the enzymatic reaction's product) or 0 (indicated by the absence of the enzymatic reaction's product). We build and evaluate a set of digital circuits in the lab using our proposed methodology to model the circuits using chemical reactions. In addition, we demonstrate the implementation of a neural network classifier using our framework.

Cross-shelf processes of terrigenous organic matter drive mercury speciation on the east siberian shelf in the Arctic Ocean.

The cross-shelf distributions of total mercury (THg), methylmercury (MeHg) and organic and inorganic matter, as well as the presence of the hgcA gene were investigated on the East Siberian Shelf (ESS) to understand the processes underlying the speciation of sedimentary Hg. Samples were collected from 12 stations grouped into four zones based on water depth: inner shelf (5 stations), mid-shelf (3 stations), outer shelf (2 stations), and slope (2 stations). The THg concentration in the surface sediment increased from the inner shelf (0.25 ± 0.023 nmol g-1) toward the slope (0.52 nmol g-1), and, when normalized to total organic carbon content, the THg showed a positive correlation with the clay-to-sand ratio (r2 = 0.48, p = 0.012) and degree of chemical weathering (r2 = 0.79, p = 0.0001). The highest MeHg concentrations (3.0 ± 1.8 pmol g-1), as well as peaks in the S/C ratio (0.012 ± 0.002) of sediment-leached organic matter, were found on the mid-shelf, suggesting that the activities of sulfate reducers control the net Hg(II) methylation rates in the sediment. This was supported by results from a principal component analysis (PCA) performed with Hg species concentrations and sediment-leached organic matter compositions. The site-specific variation in MeHg showed the highest similarity with that of CHONS compounds in the PCA, where Deltaproteobacteria were projected to be putative Hg(II) methylators in the gene analysis. In summary, the hydrodynamic sorting of lithogenic particles appears to govern the cross-shelf distribution of THg, and in situ methylation is considered a major source of MeHg in the ESS sediment.