We present a quantitatively accurate machine-learning (ML) model for the computational prediction of core-electron binding energies, from which X-ray photoelectron spectroscopy (XPS) spectra can be readily obtained. Our model combines density functional theory (DFT) with GW and uses kernel ridge regression for the ML predictions. We apply the new approach to disordered materials and small molecules containing carbon, hydrogen, and oxygen and obtain qualitative and quantitative agreement with experiment, resolving spectral features within 0.1 eV of reference experimental spectra. The method only requires the user to provide a structural model for the material under study to obtain an XPS prediction within seconds. Our new tool is freely available online through the XPS Prediction Server.

Glass-transition and cold-crystallization of a sugar alcohol phase change material dispersed within ionic citrate cross-linked polyvinyl alcohol enable long-term heat storage.

In clinical settings, the dosing and differential diagnosis of the poisoning of morphine (MO) and codeine (CO) is challenging due to interindividual variations in metabolism. However, direct electrochemical detection of these analytes from biological matrices is inherently challenging due to interference from large concentrations of anions, such as ascorbic acid (AA) and uric acid (UA), as well as fouling of the electrode by proteins. In this work, a disposable Nafion-coated single-walled carbon nanotube network (SWCNT) electrode was developed. We show facile electron transfer and efficient charge separation between the interfering anions and positively charged MO and CO, as well as significantly reduced matrix effect in human plasma. The Nafion coating alters the voltammetric response of MO and CO, enabling simultaneous detection. With this SWCNT/Nafion electrode, two linear ranges of 0.05–1 and 1–10 μM were found for MO and one linear range of 0.1–50 μM for CO. Moreover, the selective and simultaneous detection of MO and CO was achieved in large excess of AA and UA, as well as, for the first time, in unprocessed human plasma. The favorable properties of this electrode enabled measurements in plasma with only mild dilution and without the precipitation of proteins.

The understanding of microbial growth dynamics during in situ fermentation and production of bacterial cellulose (BC) with impressive properties mimicking artificial nacre, suitable for commodity applications remains fundamentally challenging. Fabrication of BC/graphene films through a single step in situ fermentation with improved properties provides a sustainable replacement to the conventional chemical-based modification using toxic compounds. This work reports the effect of reduced graphene oxide (RGO) on in situ fermentation kinetics and demonstrates the formation of percolated-network in BC/RGO nanostructures. The evaluation of kinetic parameters shows that the specific growth rate reaches optimal values at 3 wt % RGO loadings, with mixed growth associated BC production behavior. The two-dimensional graphene sheets uniformly dispersed into a three-dimensional matrix of BC nanofibers via hydrogen-bonded interactions along with in situ reductions of RGO sheets, as confirmed from spectroscopic studies. This study also demonstrates the presence of percolated network-like structures between BC fibers and RGO platelets, which resulted in the formation of nanostructures with exceptional mechanical robustness and electrical conductivity. The physicochemical and structural properties of fabricated BC/RGO films were found to significantly depend upon the RGO compositions as well as fermentation conditions. We envision that the proposed ecofriendly and scalable technology for the formation of BC/RGO films with excellent inherent properties and performance will attract great interest for its prospective applications in flexible electronics.