Coupling the chemical reactivity of bimetallic surfaces to the orientations of liquid crystals

Actuating Liquid Crystals Rapidly and Reversibly by Using Chemical Catalysis

Microtubules and catalytic motor proteins underlie the microscale actuation of living materials, and they have been used in reconstituted systems to harness chemical energy to drive new states of organization of soft matter (e.g., liquid crystals (LCs)). Such materials, however, are fragile and challenging to translate to technological contexts. Rapid (sub-second) and reversible changes in the orientations of LCs at room temperature using reactions between gaseous hydrogen and oxygen that are catalyzed by Pd/Au surfaces are reported. Surface chemical analysis and computational chemistry studies confirm that dissociative adsorption of H2 on the Pd/Au films reduces preadsorbed O and generates 1 ML of adsorbed H, driving nitrile-containing LCs from a perpendicular to a planar orientation. Subsequent exposure to O2 leads to oxidation of the adsorbed H, reformation of adsorbed O on the Pd/Au surface, and a return of the LC to its initial orientation. The roles of surface composition and reaction kinetics in determining the LC dynamics are described along with a proof-of-concept demonstration of microactuation of beads. These results provide fresh ideas for utilizing chemical energy and catalysis to reversibly actuate functional LCs on the microscale.

Elucidating Molecular-Scale Principles Governing the Anchoring of Liquid Crystal Mixtures on Solid Surfaces

Computational chemistry calculations are broadly useful for guiding the atom-scale design of hard-soft material interfaces including how molecular interactions of single-component liquid crystals (LCs) at inorganic surfaces lead to preferred orientations of the LC far from the surface. The majority of LCs, however, are not single-component phases but comprise of mixtures, such as a mixture of mesogens, added to provide additional functions such as responsiveness to the presence of targeted organic compounds (for chemical sensing). In such LC mixtures, little is understood about the near-surface composition and organization of molecules and how that organization propagates into the far-field LC orientation. Here, we address this broad question by using a multiscale computational approach that combines density functional theory (DFT)-based calculations and classical molecular dynamics (MD) simulations to predict the interfacial composition and organization of a binary LC mixture of 4'-cyano-4-biphenylcarbolxylic acid (CBCA) and 4'-n-pentyl-4-biphenylcarbonitrile (5CB) supported on anatase (101) titania surfaces. DFT calculations determine the surface composition and atomic-scale organization of CBCA and 5CB at the titania surface, and classical MD simulations build upon the DFT description to describe the evolution of the near-surface order into the bulk LC. A surprising finding is that the 5CB and CBCA molecules adopt orthogonal orientations at the anatase surface and that, above a threshold concentration of CBCA, this mixture of orientations evolves away from the surface to define a uniform far-field homeotropic orientation. These results demonstrate that molecular-level knowledge achieved through a combination of computational techniques permits the design and understanding of functional LC mixtures at interfaces.

Sensing Gas Mixtures by Analyzing the Spatiotemporal Optical Responses of Liquid Crystals Using 3D Convolutional Neural Networks

We report how analysis of the spatial and temporal optical responses of liquid crystal (LC) films to targeted gases, when performed using a machine learning methodology, can advance the sensing of gas mixtures and provide important insights into the physical processes that underlie the sensor response. We develop the methodology using O₃ and Cl₂ mixtures (representative of an important class of analytes) and LCs supported on metal perchlorate-decorated surfaces as a model system. Although O₃ and Cl₂ both diffuse through LC films and undergo redox reactions with the supporting metal perchlorate surfaces to generate similar initial and final optical states of the LCs, we show that a three-dimensional convolutional neural network can extract feature information that is encoded in the spatiotemporal color patterns of the LCs to detect the presence of both O₃ and Cl₂ species in mixtures and to quantify their concentrations. Our analysis reveals that O₃ detection is driven by the transition time over which the brightness of the LC changes, while Cl₂ detection is driven by color fluctuations that develop late in the optical response of the LC. We also show that we can detect the presence of Cl₂ even when the concentration of O₃ is orders of magnitude greater than the Cl₂ concentration. The proposed methodology is generalizable to a wide range of analytes, reactive surfaces, and LCs and has the potential to advance the design of portable LC monitoring devices (e.g., wearable devices) for analyzing gas mixtures using spatiotemporal color fluctuations.

Ordering Transitions of Liquid Crystals Triggered by Metal Oxide-catalyzed Reactions of Sulfur Oxide Species

Liquid crystals (LCs), when supported on reactive surfaces, undergo changes in ordering that can propagate over distances of micrometers, thus providing a general and facile mechanism to amplify atomic-scale transformations on surfaces into the optical scale. While reactions on organic and metal substrates have been coupled to LC-ordering transitions, metal oxide substrates, which offer unique catalytic activities for reactions involving atmospherically important chemical species such as oxidized sulfur species, have not been explored. Here, we investigate this opportunity by designing LCs that contain 4'-cyanobiphenyl-4-carboxylic acid (CBCA) and respond to surface reactions triggered by parts-per-billion concentrations of SO₂ gas on anatase (101) substrates. We used electronic structure calculations to predict that the carboxylic acid group of CBCA binds strongly to anatase (101) in a perpendicular orientation, a prediction that we validated in experiments in which CBCA (0.005 mol %) was doped into an LC (4'-n-pentyl-4-biphenylcarbonitrile). Both experiment and computational modeling further demonstrated that SO₃-like species, produced by a surface-catalyzed reaction of SO₂ with H₂O on anatase (101), displace CBCA from the anatase surface, resulting in an orientational transition of the LC. Experiments also reveal the LC response to be highly selective to SO₂ over other atmospheric chemical species (including H₂O, NH₃, H₂S, and NO₂), in agreement with our computational predictions for anatase (101) surfaces. Overall, we establish that the catalytic activities of metal oxide surfaces offer the basis of a new class of substrates that trigger LCs to undergo ordering transitions in response to chemical species of relevance to atmospheric chemistry.