This model was supported by HDX investigations that demonstrated the stabilization of four, non-overlapping peptides within helix α2 of the TOP subdomain for wt-h12-LOX, consistent with the dimer interface. Most importantly, our data reveal that the dimer and monomer of h12-LOX have distinct biochemical properties, suggesting that the structural changes due to dimerization have allosteric effects on active site catalysis and inhibitor binding.The localized surface plasmon resonance of plasmonic nanoparticles (NPs) can be coupled with a noble metal substrate (S) to induce a localized augmented electric field (E-field) concentrated at the NP-S gap. Herein, we analyzed the fundamental near-field properties of metal NPs on diverse substrates numerically (using the 3D finite-difference time-domain method) and experimentally [using surface-enhanced Raman scattering (SERS)]. We systematically examined the effects of plasmonic NPs on noble metals (Ag and Au), non-noble metals (Al, Ti, Cu, Fe, and Ni), semiconductors (Si and Ge), and dielectrics (TiO2, ZnO, and SiO2) as substrates. For the AgNPs, the Al (11,664 times) and Si (3969 times) substrates produced considerable E-field enhancements, with Al in particular generating a tremendous E-field enhancement comparable in intensity to that induced by a Ag (28,224 times) substrate. Notably, we found that a superior metallic character of the substrate gave rise to easier induction of image charges within the metal substrate, resulting in a greater E-field at the NP-S gap; on the other hand, the larger the permittivity of the nonmetal substrate, the greater the ability of the substrate to store an image charge distribution, resulting in stronger coupling to the charges of localized surface plasmon resonance oscillation on the metal NP. Furthermore, we measured the SERS spectra of rhodamine 6G (a commonly used Raman spectral probe), histamine (a biogenic amine used as a food freshness indicator), creatinine (a kidney health indicator), and tert-butylbenzene [an extreme ultraviolet (EUV) lithography contaminant] on AgNP-immobilized Al and Si substrates to demonstrate the wide range of potential applications. Finally, the NP-S gap hotspots appear to be widely applicable as an ultrasensitive SERS platform (∼single-molecule level), especially when used as a powerful analytical tool for the detection of residual contaminants on versatile substrates.Exsolution phenomena are highly debated as efficient synthesis routes for nanostructured composite electrode materials for the application in solid oxide cells (SOCs) and the development of next-generation electrochemical devices for energy conversion. Utilizing the instability of perovskite oxides, doped with electrocatalytically active elements, highly dispersed nanoparticles can be prepared at the perovskite surface under the influence of a reducing heat treatment. For the systematic study of the mechanistic processes governing metal exsolution, epitaxial SrTi0.9Nb0.05Ni0.05O3-δ thin films of well-defined stoichiometry are synthesized and employed as model systems to investigate the interplay of defect structures and exsolution behavior. Spontaneous phase separation and the formation of dopant-rich features in the as-synthesized thin film material is revealed by high-resolution transmission electron microscopy (HR-TEM) investigations. RGD peptide mw The resulting nanostructures are enriched by nickel and serve as preformed nuclei for the subsequent exsolution process under reducing conditions, which reflects a so far unconsidered process drastically affecting the understanding of nanoparticle exsolution phenomena. Using an approach of combined morphological, chemical, and structural analysis of the exsolution response, a limitation of the exsolution dynamics for nonstoichiometric thin films is found to be correlated to a distortion of the perovskite host lattice. Consequently, the incorporation of defect structures results in a reduced particle density at the perovskite surface, presumably by trapping of nanoparticles in the oxide bulk.Fully solution-processed, large-area, electrical double-layer transistors (EDLTs) are presented by employing lead sulfide (PbS) colloidal quantum dots (CQDs) as active channels and Ti3C2Tx MXene as electrical contacts (including gate, source, and drain). The MXene contacts are successfully patterned by standard photolithography and plasma-etch techniques and integrated with CQD films. The large surface area of CQD film channels is effectively gated by ionic gel, resulting in high performance EDLT devices. A large electron saturation mobility of 3.32 cm2 V-1 s-1 and current modulation of 1.87 × 104 operating at low driving gate voltage range of 1.25 V with negligible hysteresis are achieved. The relatively low work function of Ti3C2Tx MXene (4.42 eV) compared to vacuum-evaporated noble metals such as Au and Pt makes them a suitable contact material for n-type transport in iodide-capped PbS CQD films with a LUMO level of ∼4.14 eV. Moreover, we demonstrate that the negative surface charges of MXene enhance the accumulation of cations at lower gate bias, achieving a threshold voltage as low as 0.36 V. The current results suggest a promising potential of MXene electrical contacts by exploiting their negative surface charges.The rational design of highly antifouling materials is crucial for a wide range of fundamental research and practical applications. The immense variety and complexity of the intrinsic physicochemical properties of materials (i.e., chemical structure, hydrophobicity, charge distribution, and molecular weight) and their surface coating properties (i.e., packing density, film thickness and roughness, and chain conformation) make it challenging to rationally design antifouling materials and reveal their fundamental structure-property relationships. In this work, we developed a data-driven machine learning model, a combination of factor analysis of functional group (FAFG), Pearson analysis, random forest (RF) and artificial neural network (ANN) algorithms, and Bayesian statistics, to computationally extract structure/chemical/surface features in correlation with the antifouling activity of self-assembled monolayers (SAMs) from a self-construction data set. The resultant model demonstrates the robustness of QCV2 = 0.