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Interfacial interactions between liquid crystal (LC) and two-dimensional (2D) materials provide a platform to facilitate novel optical and electronic material properties. These interactions are uniquely sensitive to the local energy landscape of the atomically thick 2D surface, which can be strongly influenced by defects that are introduced, either by design or as a byproduct of fabrication processes. Herein, we present density functional theory (DFT) calculations of the LC mesogen 4-cyan-4′-pentylbiphenyl (5CB) on graphene in the presence of a monovacancy (MV-G). We find that the monovacancy strengthens the binding of 5CB in the planar alignment and that the structure is lower in energy than the corresponding homeotropic structure. However, if the molecule is able to approach the monovacancy homeotropically, 5CB undergoes a chemical reaction, releasing 4.5 eV in the process. This reaction follows a step-by-step process gradually adding bonds, inserting the 5CB cyano group into MV-G. We conclude that this irreversible insertion reaction is likely spontaneous, potentially providing a new avenue for controlling both LC behavior and graphene properties.

Liquid crystal (LC) micro-droplet arrays are elegant systems that have a range of applications, such as chemical and biological sensing, due to a sensitivity to changes in surface properties and strong optical activity. In this work, we utilize self-assembled monolayers (SAMs) to chemically micro-pattern surfaces with preferred regions for LC occupation. Exploiting discontinuous dewetting, dragging a drop of fluid over the patterned surfaces demonstrates a novel, high-yield method of confining LC in chemically defined regions. The broad applicability of this method is demonstrated by varying the size and LC phase of the droplets. Although the optical textures of the droplets are dictated by topological constraints, the additional SAM interface is shown to lock in inhomogeneous alignment. The surface effects are highly dependent on size, where larger droplets exhibit asymmetric director configurations in nematic droplets and highly knotted structures in cholesteric droplets.

We first explore the topology of liquid crystals and look at the fundamental limitations of liquid crystals in confined geometries. The properties of liquid crystal droplets are studied both theoretically and through simulations. We then demonstrate a method of chemically patterning surfaces that allows us to generate periodic arrays of micron-sized liquid crystal droplets and compare them to our simulation results. The parallelizable method of self-localizing liquid crystals using 2D chemical patterning developed here has applications in liquid crystal biosensors and lens arrays. We also present the first work looking at colloidal liquid crystals under the guise of thermophoresis. We observe that strong negative thermophoresis occurs in these systems and develop a theory based on elastic energy minimization. We also calculate a Soret coefficient two orders of magnitude larger than those present in the literature. This large Soret coefficient has considerable potential for improving thermophoretic sorting mechanisms such as Thermal-Field Flow Fractionation and MicroScale Thermophoresis. The final piece of this work demonstrates a method of using projection lithography to polymerize liquid crystal colloids with a defined internal director. While still a work in progress, there is potential for generating systems of active colloids that can change shape upon external stimulus and in the generation of self-folding shapes by selective polymerization and director predetermination in the vain of micro-kirigami.

Background: Preparing patients for surgery considers assessing the patient’s somatic health, for example by the American Society of Anesthesiology (ASA) scale or the Revised Cardiac Risk Index (RCRI), known as the Lee index. This process usually ignores mental functioning (personality and anxiety), which is known to influence health. The purpose of this study is to analyze the existence of a relationship between personality traits (the Big Five model and trait-anxiety) and anesthesia scales (ASA scale, Lee index) used for the preoperative evaluation of patients. Methods: The study group comprised 102 patients (59 women, 43 men) scheduled for hip replacement surgery. Patients completed two psychological questionnaires: the NEO-FFI (NEO Five Factors Inventory) and the X-2 STAI (State-Trait Anxiety Inventory) sheet. Next, the presence and possible strength of the relationship between personality traits and demographic and medical variables were analyzed using Spearman’s rho rank correlation coefficient. Results: Patients with a high severity of trait anxiety are classified higher on the ASA scale (rs = 0.359; p < 0.001). Neuroticism, defined according to the Big Five model, significantly correlates with scales of preoperative patient assessment: the ASA classification (rs = 0.264; p < 0.001) and the Lee index (rs = 0.202; p = 0.044). A hierarchical regression model was created to test the possibility of predicting ASA scores based on personality. It explained more than 34% of the variance and was a good fit to the data (p < 0.05). The controlled variables of age and gender accounted for more than 23% of the variance. Personality indicators (trait anxiety, neuroticism) additionally accounted for slightly more than 11% of the variance. Trait anxiety (Beta = 0.293) proved to be a better predictor than neuroticism (Beta = 0.054). Conclusions: These results indicate that inclusion of personality screening in the preoperative patient evaluation might help to introduce a more individualized approach to patients, which could result in better surgical outcomes.