Explore the vast range of titles available.

Chemical design of multicomponent nanocrystals requires atomic-level understanding of reaction kinetics. Here, we apply single-particle imaging coupled with atomistic simulation to study reaction pathways and rates of Pd@Au and Cu@Au core-shell nanocubes undergoing oxidative dissolution. Quantitative analysis of etching kinetics using in situ transmission electron microscopy (TEM) imaging reveals that the dissolution mechanism changes from predominantly edge-selective to layer-by-layer removal of Au atoms as the reaction progresses. Dissolution of the Au shell slows down when both metals are exposed, which we attribute to galvanic corrosion protection. Morphological transformations are determined by intrinsic anisotropy due to coordination-number-dependent atom removal rates and extrinsic anisotropy induced by the graphene window. Our work demonstrates that bimetallic core-shell nanocrystals are excellent probes for the local physicochemical conditions inside TEM liquid cells. Furthermore, single-particle TEM imaging and atomistic simulation of reaction trajectories can inform future design strategies for compositionally and architecturally sophisticated nanocrystals. Rational design of multicomponent nanocrystals requires atomic-level understanding of reaction kinetics. Here, the authors apply single-particle liquid-cell electron microscopy imaging coupled with atomistic simulations to understand pathways and rates of bimetallic core-shell nanocubes undergoing oxidative dissolution.

Workpiece quality prediction is very important in modern manufacturing industry. However, traditional machine learning methods are very sensitive to their hyperparameters, making the tuning of the machine learning methods essential to improve the prediction performance. Hyperparameter optimization (HPO) approaches are applied attempting to tune hyperparameters, such as grid search and random search. However, the hyperparameters space for workpiece quality prediction model is high dimension and it consists with continuous, combinational and conditional types of hyperparameters, which is difficult to be tuned. In this article, a new automatic machine learning based HPO, named adaptive Tree Pazen Estimator (ATPE), is proposed for workpiece quality prediction in high dimension. In the proposed method, it can iteratively search the best combination of hyperparameters in the automatic way. During the warm-up process for ATPE, it can adaptively adjust the hyperparameter interval to guide the search. The proposed ATPE is tested on sparse stack autoencoder based MNIST and XGBoost based WorkpieceQuality dataset, and the results show that ATPE provides the state-of-the-art performances in high-dimensional space and can search the hyperparameters in reasonable range by comparing with Tree Pazen Estimator, annealing, and random search, showing its potential in the field of workpiece quality prediction.

Metal-oxide nanocrystals doped with aliovalent atoms can exhibit tunable infrared localized surface plasmon resonances (LSPRs). Yet, the range of dopant types and concentrations remains limited for many metal-oxide hosts, largely because of the difficulty in establishing reaction kinetics that favors dopant incorporation by using the co-thermolysis method. Here we develop cation-exchange reactions to introduce p-type dopants (Cu + , Ag + , etc.) into n-type metal-oxide nanocrystals, producing programmable LSPR redshifts due to dopant compensation. We further demonstrate that enhanced n-type doping can be realized via sequential cation-exchange reactions mediated by the Cu + ions. Cation-exchange transformations add a new dimension to the design of plasmonic nanocrystals, allowing preformed nanocrystals to be used as templates to create compositionally diverse nanocrystals with well-defined LSPR characteristics. The ability to tailor the doping profile postsynthetically opens the door to a multitude of opportunities to deepen our understanding of the relationship between local structure and LSPR properties. Doping semiconductor nanocrystals with impurity atoms is a key pathway for tuning their plasmonic properties. Here, the authors use a cation exchange strategy to dope p-type or n-type metal ions into n-type metal-oxide nanocrystals, post-synthetically tailoring their localized surface plasmon resonances in the infrared region.

ObjectivesThe significance of the systemic inflammation response index (SIRI) for predicting prognostic outcomes in patients with non-small cell lung cancer (NSCLC) has been analysed in previous studies, but no consistent conclusions have been obtained. Consequently, the present meta-analysis was performed to identify the significance of SIRI in predicting the prognosis of NSCLC.DesignThis study followed the PRISMA guidelines.Data sourcesPubMed, Web of Science and Embase databases were searched between their inception and 26 November 2023.Eligibility criteria for selecting studiesStudies investigating the relationship between SIRI and survival outcomes of patients with NSCLC were included.Data extraction and synthesisThe value of SIRI in predicting prognosis in NSCLC cases was predicted using combined hazard ratios (HRs) and 95% CIs.ResultsNine articles with 3728 cases were enrolled in this study. Based on our combined data, a higher SIRI value was markedly linked with poor overall survival (OS) (HR=2.08, 95% CI 1.68 to 2.58, p<0.001) and inferior progression-free survival (PFS) (HR=1.74, 95% CI 1.47 to 2.07, p<0.001) of NSCLC. According to the subgroup analysis, country, history and cut-off value did not affect the significance of SIRI in predicting OS and PFS in NSCLC (p<0.05).ConclusionsA higher SIRI value was significantly associated with both OS and PFS in patients with NSCLC. Moreover, SIRI had a stable prognostic efficiency for NSCLC in various subgroups.

Multicomponent nanocrystal superlattices represent an interesting class of material that derives emergent properties from mesoscale structure, yet their programmability can be limited by the alkyl-chain-based ligands decorating the surfaces of the constituent nanocrystals. Polymeric ligands offer distinct advantages, as they allow for more precise tuning of the effective size and ‘interaction softness’ through changes to the polymer’s molecular weight, chemical nature, architecture, persistence length and surrounding solvent. Here we show the formation of 10 different binary nanocrystal superlattices (BNSLs) with both two- and three-dimensional order through independent adjustment of the core size of spherical nanocrystals and the molecular weight of densely grafted polystyrene ligands. These polymer-brush-based ligands introduce new energetic contributions to the interparticle potential that stabilizes various BNSL phases across a range of length scales and interparticle spacings. Our study opens the door for nanocrystals to become modular elements in the design of functional particle brush solids with controlled nanoscale interfaces and mesostructures. Binary nanocrystal superlattice metamaterials are arousing significant interest due to their potential for use in functional devices. Here, the authors endow the nanoparticles with polymer brushes which enable control over their spacings and thus mesoscale structure and properties.

Synthetic methods produce libraries of colloidal nanocrystals with tunable physical properties by tailoring the nanocrystal size, shape, and composition. Here, we exploit colloidal nanocrystal diversity and design the materials, interfaces, and processes to construct all-nanocrystal electronic devices using solution-based processes. Metallic silver and semiconducting cadmium selenide nanocrystals are deposited to form high-conductivity and high-mobility thin-film electrodes and channel layers of field-effect transistors. Insulating aluminum oxide nanocrystals are assembled layer by layer with polyelectrolytes to form high—dielectric constant gate insulator layers for low-voltage device operation. Metallic indium nanocrystals are codispersed with silver nanocrystals to integrate an indium supply in the deposited electrodes that serves to passivate and dope the cadmium selenide nanocrystal channel layer. We fabricate all-nanocrystal field-effect transistors on flexible plastics with electron mobilities of 21.7 square centimeters per volt-second.

Chemists have developed mechanistic insight into numerous chemical reactions by thoroughly characterizing nonequilibrium species. Although methods to probe these processes are well established for molecules, analogous techniques for understanding intermediate structures in nanomaterials have been lacking. We monitor the shape evolution of individual anisotropic gold nanostructures as they are oxidatively etched in a graphene liquid cell with a controlled redox environment. Short-lived, nonequilibrium nanocrystals are observed, structurally analyzed, and rationalized through Monte Carlo simulations. Understanding these reaction trajectories provides important fundamental insight connecting high-energy nanocrystal morphologies to the development of kinetically stabilized surface features and demonstrates the importance of developing tools capable of probing short-lived nanoscale species at the single-particle level.

The aim was to analyze the factors influencing the psychological status and cognitive function in postoperative head and neck tumor (HNT) patients. 170 patients, including 90 benign HNT (BHNT) patients and 80 malignant HNT (MHNT) patients, were included in this study. Psychological status was evaluated using the distress thermometer. Cognitive function was evaluated using the Multiple Ability Self-Reported Questionnaire. The psychological status and cognitive function were both statistically significantly better in BHNT patients than in MHNT patients ( P  < 0.001 and P  < 0.001, respectively). MHNT patients in the moderate and severe appearance defect groups had a higher incidence of psychological distress than those in the no facial appearance defect group ( P  = 0.006 and P  = 0.011, respectively). Both BHNT and MHNT patients in the group under the age of 60 had a higher incidence of psychological distress than those in the group over the age of 60 ( P  = 0.017 and P  = 0.017, respectively). Educational level of both BHNT and MHNT patients was negatively correlated with the extent of cognitive impairment ( P  = 0.012 and P  = 0.004, respectively). The influence of postoperative time on the psychological condition varied in different groups. Postoperative time of both BHNT and MHNT patients was negatively correlated with the extent of cognitive impairment ( P  = 0.027 and P  < 0.001, respectively).

Well-connected quasicrystals Quasicrystals are unique materials combining long-range order with 'impossible' packing symmetries like fivefold rotation, forbidden in periodic structures. Until now, they have been found only in specific systems such as intermetallic compounds, block copolymers, or colloidal particles under the action of a laser standing-wave pattern. Now Talapin et al . have self-assembled colloidal nanoparticles into aperiodic quasicrystalline lattices by carefully tailoring their sizes and using a novel packing motif. They can obtain quasicrystals with nanoparticles made of several different combinations of materials, pointing to the fact that only sphere packing and simple inter-particle potentials are important for their formation, and not specific interactions between the components These quasicrystals can also connect to the ordinary (crystalline) world through a thin 'wetting' layer with structures resembling the classic Archimedean tiling pattern. Quasicrystals are ordered structures that lack any translational symmetry, challenging the classic conception of ordered solids as periodic structures. So far, they have been reported in certain systems and can, for example, form from intermetallic compounds and organic dendrimers. Here it is shown that colloidal inorganic nanoparticles from several materials can self-assemble into binary aperiodic superlattices with quasicrystalline order. The discovery of quasicrystals in 1984 changed our view of ordered solids as periodic structures 1 , 2 and introduced new long-range-ordered phases lacking any translational symmetry 3 , 4 , 5 . Quasicrystals permit symmetry operations forbidden in classical crystallography, for example five-, eight-, ten- and 12-fold rotations, yet have sharp diffraction peaks. Intermetallic compounds have been observed to form both metastable and energetically stabilized quasicrystals 1 , 3 , 5 ; quasicrystalline order has also been reported for the tantalum telluride phase with an approximate Ta 1.6 Te composition 6 . Later, quasicrystals were discovered in soft matter, namely supramolecular structures of organic dendrimers 7 and tri-block copolymers 8 , and micrometre-sized colloidal spheres have been arranged into quasicrystalline arrays by using intense laser beams that create quasi-periodic optical standing-wave patterns 9 . Here we show that colloidal inorganic nanoparticles can self-assemble into binary aperiodic superlattices. We observe formation of assemblies with dodecagonal quasicrystalline order in different binary nanoparticle systems: 13.4-nm Fe 2 O 3 and 5-nm Au nanocrystals, 12.6-nm Fe 3 O 4 and 4.7-nm Au nanocrystals, and 9-nm PbS and 3-nm Pd nanocrystals. Such compositional flexibility indicates that the formation of quasicrystalline nanoparticle assemblies does not require a unique combination of interparticle interactions, but is a general sphere-packing phenomenon governed by the entropy and simple interparticle potentials. We also find that dodecagonal quasicrystalline superlattices can form low-defect interfaces with ordinary crystalline binary superlattices, using fragments of (3 3 .4 2 ) Archimedean tiling as the ‘wetting layer’ between the periodic and aperiodic phases.

We report a one-pot chemical approach for the synthesis of highly monodisperse colloidal nanophosphors displaying bright upconversion luminescence under 980 nm excitation. This general method optimizes the synthesis with initial heating rates up to 100°C/minute generating a rich family of nanoscale building blocks with distinct morphologies (spheres, rods, hexagonal prisms, and plates) and upconversion emission tunable through the choice of rare earth dopants. Furthermore, we employ an interfacial assembly strategy to organize these nanocrystals (NCs) into superlattices over multiple length scales facilitating the NC characterization and enabling systematic studies of shape-directed assembly. The global and local ordering of these superstructures is programmed by the precise engineering of individual NC's size and shape. This dramatically improved nanophosphor synthesis together with insights from shape-directed assembly will advance the investigation of an array of emerging biological and energy-related nanophosphor applications.