Publications by authors named "Huaizhe Yu"

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)).

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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.

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The development of responsive soft materials with tailored functional properties based on the chemical reactivity of atomically precise inorganic interfaces has not been widely explored. In this communication, guided by first-principles calculations, we design bimetallic surfaces comprised of atomically thin Pd layers deposited onto Au that anchor nematic liquid crystalline phases of 4'-n-pentyl-4-biphenylcarbonitrile (5CB) and demonstrate that the chemical reactivity of these bimetallic surfaces towards Cl gas can be tuned by specification of the composition of the surface alloy. Specifically, we use underpotential deposition to prepare submonolayer to multilayers of Pd on Au and employ X-ray photoelectron and infrared spectroscopy to validate computational predictions that binding of 5CB depends strongly on the Pd coverage, with ∼0.

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Soft matter that undergoes programmed macroscopic responses to molecular analytes has potential utility in a range of health and safety-related contexts. In this study, we report the design of a nematic liquid crystal (LC) composition that forms through dimerization of carboxylic acids and responds to the presence of vapors of organoamines by undergoing a visually distinct phase transition to an isotropic phase. Specifically, we screened mixtures of two carboxylic acids, 4-butylbenzoic acid and trans-4-pentylcyclohexanecarboxylic acid, and found select compositions that exhibited a nematic phase from 30.

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Elementary reaction steps, including adsorption and dissociation, of a range of molecular adsorbates on transition metal surfaces have been elucidated in the context of chemical catalysis. Here we leverage this knowledge to design liquid crystals (LCs) supported on ultrathin polycrystalline gold films (predominant crystallographic face is (111)) that are triggered to undergo orientational transitions by dissociative adsorption and dehydrogenation reactions involving chlorine and carboxylic acids, respectively, thus amplifying these atomic-scale surface processes in situ into macroscopic optical signals. We use electronic structure calculations to predict that 4'--pentyl-4-biphenylcarbonitrile (5CB), a room temperature nematic LC, does not bind to Au(111) in an orientation that changes upon dissociative adsorption of molecular chlorine, a result validated by experiments.

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We present a machine learning (ML) framework to optimize the specificity and speed of liquid crystal (LC)-based chemical sensors. Specifically, we demonstrate that ML techniques can uncover valuable feature information from surface-driven LC orientational transitions triggered by the presence of different gas-phase analytes (and the corresponding optical responses) and can exploit such feature information to train accurate and automatic classifiers. We demonstrate the utility of the framework by designing an experimental LC system that exhibits similar optical responses to a stream of nitrogen containing either 10 ppmv dimethyl-methylphosphonate (DMMP) or 30% relative humidity (RH).

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Surface-supported liquid crystals (LCs) that exhibit orientational and thus optical responses upon exposure to ppb concentrations of Cl gas are reported. Computations identified Mn cations as candidate surface binding sites that undergo redox-triggered changes in the strength of binding to nitrogen-based LCs upon exposure to Cl gas. Guided by these predictions, μm-thick films of nitrile- or pyridine-containing LCs were prepared on surfaces decorated with Mn binding sites as perchlorate salts.

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The development of stimuli-responsive materials suitable for use in wearable sensors is a key unresolved challenge. Liquid crystals (LCs) are particularly promising, as they do not require power, are light-weight, and can be tuned to respond to a range of targeted chemical stimuli. Here, an advance is reported in the design of LCs for chemical sensors with the discovery of LCs that assume parallel orientations at free surfaces and yet retain their chemoresponsiveness.

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We report a combined theoretical and experimental effort to elucidate systematically for the first time the influence of anions of transition metal salt-decorated surfaces on the orientations of supported films of nematic liquid crystals (LCs) and adsorbate-induced orientational transitions of these LC films. Guided by computational chemistry predictions, we find that nitrate anions weaken the binding of 4'-n-pentyl-4-biphenylcarbonitrile (5CB) to transition metal cations, as compared to perchlorate salts, although binding is still sufficiently strong to induce homeotropic (perpendicular) orientations of 5CB. In addition, we find the orientations of the LC to be correlated across all metal cations investigated by a molecular anchoring energy density that is calculated as the product of the single-site binding energy and metal cation binding site density on the surface.

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Nematic liquid crystals make promising chemoresponsive systems, but their development is currently limited by extensive experimental screening. Here we report a computational model to understand and predict orientational changes of surface-anchored nematic liquid crystals in response to chemical stimuli. In particular, we use first-principles calculations to evaluate the binding energies of benzonitrile, a model for 4'-pentyl-4-biphenylcarbonitrile, and dimethyl methylphosphonate to metal cation models representing the substrate chemical sensing surface.

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