Nanoparticle manipulation by thermal gradient

A method was proposed to manipulate nanoparticles through a thermal gradient. The motion of a fullerene molecule enclosed inside a (10, 10) carbon nanotube with a thermal gradient was studied by molecular dynamics simulations. We created a one-dimensional potential valley by imposing a symmetrical thermal gradient inside the nanotube. When the temperature gradient was large enough, the fullerene sank into the valley and became trapped. The escaping velocities of the fullerene were evaluated based on the relationship between thermal gradient and thermophoretic force. We then introduced a new way to manipulate the position of nanoparticles by translating the position of thermostats with desirable thermal gradients. Compared to nanomanipulation using a scanning tunneling microscope or an atomic force microscope, our method for nanomanipulation has a great advantage by not requiring a direct contact between the probe and the object

Intact glycopeptide analysis of recombinant protein from CHO cells

The quality of recombinant glycoproteins including antibodies and other biologics is dictated by their glycan profiles. What is missing is how to analyze these glycans rapidly for process improvement and control applications. Conventional glycan analysis involves the release of glycans, which rarely captures the glycan site-specific information. Intact glycopeptide analysis in which glycans are retained on the peptide provides insights into the glycan structure and the glycosylation site information simultaneously. This information can reveal additional details about site occupancy and cellular glycosylation of proteins. Avoiding glycan release and some modifications and labeling steps in our intact glycopeptide analysis can result in a shorter sample preparation time than conventional glycan analysis methods. Compared to peptide mapping using LC-MS to decipher protein amino acid sequence in proteomics, this analysis focuses on glycopeptide profiling following protease-digestion. With the aid of LC-MS/MS, we are able to obtain targeted glycoprotein sequence information, glycan profiles and glycan distribution at specific sites. Here we present the application of glycopeptide analysis for model AMBIC and other proteins from CHO-GS and CHO-K1 cells. The site-specific glycosylation patterns of our model proteins EPO-Fc and EPO are characterized. Further, we examine the impact of media formulation and additives on the glycan profiles for these proteins. Please click Additional Files below to see the full abstract

Structural and electronic properties of Al nanowires: an ab initio pseudopotential study

The stability and electronic structure of a single monatomic Al wire has been studied using the ab initio pseudopotential method. The Al wire undergoes two structural rearrangements under compression, i.e., zigzag configurations at angles of $140^o$ and $60^o$. The evolution of electronic structures of the Al chain as a function of structural phase transition has been investigated. The relationship between electronic structure and geometric stability is also discussed. The 2p bands in the Al nanowire are shown to play a critical role in its stability. The effects of density functionals (GGA and LDA) on cohesive energy and bond length of Al nanostructures (dimmer, chains, and monolayers) are also examined. The link between low dimensional 0D structure (dimmer) to high dimensional 3D bulk Al is estimated. An example of optimized tip-suspended finite atomic chain is presented to bridge the gap between hypothetical infinite chains and experimental finite chains.Comment: 11 pages, 5 figure

Advances of Machine Learning in Materials Science: Ideas and Techniques

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field, in both the computational and experimental departments. With the advent of machine learning-based techniques, there has been a paradigm shift: materials can now be screened quickly using ML models and even generated based on materials with similar properties; ML has also quietly infiltrated many sub-disciplinary under materials science. However, ML remains relatively new to the field and is expanding its wing quickly. There are a plethora of readily-available big data architectures and abundance of ML models and software; The call to integrate all these elements in a comprehensive research procedure is becoming an important direction of material science research. In this review, we attempt to provide an introduction and reference of ML to materials scientists, covering as much as possible the commonly used methods and applications, and discussing the future possibilities.Comment: 80 pages; 22 figures. To be published in Frontiers of Physics, 18, xxxxx, (2023

Interfacial properties between CoO (100) and Fe(3)O(4) (100)

Using molecular beam epitaxy 1-20 ML thick CoO (100) films were grown monolayer by monolayer on Fe(3)O(4) (100) substrates. The stoichiometry of the films was verified by low-energy-electron diffraction and reflection-high-energy-electron diffraction patterns, as well as x-ray photoelectron spectroscopy. Auger measurements as a function of CoO film thickness indicated a layer-by-layer growth mode. Ultraviolet photoelectron spectroscopy (UPS) was used to monitor the thin film electronic properties. The evolution of the density of states in the O 2p/Fe 3d and O 2p/Co 3d bands exhibits a shift in the position of the CoO valence band for ultrathin films relative to bulklike thick films. The measured spectra (when aligned to cancel the band shift) are compared to models of the spectra that would be expected based on the bulk compounds, with and without additional interfacial electronic states. Electronic states at the Fe(3)O(4)-CoO interface have been identified, and their UPS spectrum has been determined

Transitional care for patients with chronic obstructive pulmonary disease

AbstractObjectivesTo observe the effects of transitional care on the quality of life of chronic obstructive pulmonary disease (COPD) patients.MethodsA total of 114 COPD patients were recruited from the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China and divided equally into an intervention group and control group. Following discharge, patients from the intervention group recieved three-months intervention in addition to regular nursing care, while control group patients received regular nursing care only. Patients' quality of life was measured using the St. George's respiratory questionnaire (SGRQ), the 12-item General Health Questionnaire (GHQ-12) and body mass index (BMI).ResultsThe symptoms section score, the activity section score, the impacts section score, the total score and the rate of mental disorders were significantly changed after the intervention while there was no statistical difference in BMI between groups.ConclusionsTransitional care can improve health-related quality of life in COPD patients who have recently suffered an exacerbation