Cobalt hydroxide, cobalt oxyhydroxide, and cobalt oxide nanomaterials were synthesized through simple soft chemistry. The cobalt hydroxide displays hexagonal morphology with clear edges 20 nm long. This morphology and nanosize is retained through to cobalt oxide Co3O4 through a topotactical relationship. Cobalt oxyhydroxide and cobalt oxide nanomaterials were synthesized through oxidation and low-temperature calcination from the as-prepared cobalt hydroxide. Characterization of these cobalt-based nanomaterials was fully developed, including X-ray diffraction, transmission electron microscopy combined with selected area electron diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermal gravimetric analysis. Bonding of the divalent cobalt hydroxide from the oxyhydroxide and oxides by studying their high-resolution XPS spectra for Co 2p3/2 and O 1s. Raman spectroscopy of the as-prepared Co(OH)2, CoO(OH), and Co3O4 nanomaterials characterized each material. The thermal stability of the materials Co(OH)2 and CoO(OH) was established. This research has developed methodology for the synthesis of cobalt oxide and cobalt oxyhydroxide nanodiscs at low temperatures.

Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100-400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

In this work, the early stage aggregation kinetics of manganese dioxide (MnO2) colloids in aqueous solution and the effects of constituents of natural organic matter (i.e., Suwannee River fulvic acid (SRFA), Suwannee River humic acid (SRHA), alginate, and bovine serum albumin (BSA)) were investigated by time-resolved dynamic light scattering. MnO2 colloids were significantly aggregated in the presence of monovalent and divalent cations. The critical coagulation concentrations were 28, 0.8, and 0.45 mM for NaNO3, Mg(NO3)2, and Ca(NO3)2, respectively. The Hamaker constant of MnO2 colloids in aqueous solution was 7.84 × 10(-20) J. All the macromolecules tested slowed MnO2 colloidal aggregation rates greatly. The steric repulsive forces, originated from organic layers adsorbed on MnO2 colloidal surfaces, may be mainly responsible for their stabilizing effects. However, the complexes formed by alginate and Ca(2+) (>5 mM) might play a bridging role and thus enhanced MnO2 colloidal aggregation instead. These results may be important for assessing the fate and transport of MnO2 colloids and associated contaminants.

The selected-control synthesis of uniform α-Fe2O3 nanoparticles with morphologies of rhombohedra, rods, and cubes was successfully achieved in large quantities by the capping agent–cationic surfactant–CTAB-mediated hydrolysis of FeCl3. The nanoparticles were obtained when the concentration of FeCl3 ranged from 0.01 to 0.05 M at 120 °C. The growth mechanisms of α-Fe2O3 nanorhombohedra, nanorods, and nanocubes were analysed in detail, based on the topotactic transformation of the precursor β-FeOOH with different morphologies under the capping agent mediation. The concentration of FeCl3, the reaction temperature, and the concentration of CTAB are all responsible for the final crystalline morphologies of the α-Fe2O3 nanoparticles. This result may facilitate not only the exploration of controlled approaches of preparing α-Fe2O3 nanoparticles for potential technical applications but also a deeper understanding of the fundamental physical and chemical processes of hydrothermal methods. X-ray powder diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and field-emission scanning electron microscopy (FE-SEM) were used to characterize the products.