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At least 1,405 records · Page 78

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

DESSY: Making a real-time expert system robust and useful

As the complexity and expected life-span of modern space systems continue to increase, the need for real-time data monitoring and failure analysis becomes more critical to their successful operation. The DEcision Support SYstem (DESSY) is a joint effort by the Intelligent Systems Branch/ER2 and the Remote Manipulator System (RMS) Section/DF44 to develop an expert system for the monitoring of the Payload Deployment and Retrieval System (PDRS). DESSY users, the RMS flight controllers, are provided with user interface enhancements and automated monitoring of system state (physical orientation) and status (operational health). Currently, a DESSY prototype for the Manipulator Positioning Mechanism (MPM) and Manipulator Retention Latches (MRL) of the PDRS has been developed and successfully demonstrated during the STS-49 and STS-46 missions. Expert systems for monitoring real-time operations must not only accurately represent domain knowledge, but also address the challenges of using unfiltered real-time data as input. This paper describes the methods and design strategies developed to overcome problems with real-time data in the NASA Mission Control Center. Types of data problems addressed are as follows: (1) loss of data; (2) erratic data; and (3) data lags and irregularities during state transition. Methods used to handle data problems include rule disabling for ignoring data when data quality is uncertain, context-sensitive bounded pattern recognition for minimizing incorrect conclusions based on bad data, and graceful recovery through system correction when reliable data returns. This combination of methods with an object-based modular DESSY design assures a robust program capable of lengthy periods of uninterrupted use in operations.

Land, Sherry A.↗

Design Choices in Anomaly Detection for Industrial Control Systems: Insights from Gas Pipeline Data

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and naïve imputation—prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensor-decomposition–based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗

Prefabricated High-Strength Rebar Systems with High-Performance Concrete for Accelerated Construction of Nuclear Concrete Structures

This project aimed to reduce the field construction times and fabrication costs of reinforced concrete (RC) nuclear structures through the use of: 1) high-strength steel deformed reinforcing bar (rebar); 2) prefabricated high-strength rebar (HSR) assemblies with headed anchorages; and 3) high-strength concrete (HSC). The focus of the project was not to develop new innovations on materials, but rather to fill a major knowledge gap on the effectiveness, code conformity, and viability (i.e., practicality, commercial availability) of existing high-strength materials in nuclear structures, especially in shear walls, their connections/joints, and around penetrations. These advances promote the Nuclear Energy Enabling Technologies Advanced Methods for Manufacturing (NEET-1) goals of accelerating deployment schedules by at least 6 months and reducing component fabrication costs by 20% or more. Toward this vision, the following objectives were identified and completed: Develop limit-benefit and cost-benefit analysis frameworks: The structural and economic limits and benefits of HSR and HSC in nuclear walls were evaluated. Importantly, it was found that modest increases in concrete strength up to 10.0 ksi and rebar yield strength up to 100 ksi result in the most economic designs and improved structural performance (Barbachyn et al., 2017a and Barbachyn et al., 2017b). Also, an industry survey was distributed to determine the cost benefits associated with prefabrication. Importantly, on-site worker-hours are significantly reduced, allowing for significantly accelerated construction schedules (Devine et al. 2018b). Develop an optimization methodology for structural design: An optimization study was deemed not necessary since the trivial solution with maximized use of high-strength materials and prefabrication always resulted in the largest cost and time savings. Instead, the benefits (and limits) of high-strength materials and prefabrication on construction costs and on-site construction time were investigated through a parametric study. Cost-reductions through the use of HSR and HSC were found to be greater than 40%. Also, on-site construction time of nuclear shear walls can be reduced by up to 83% through the use of prefabricated rebar assemblies. Conduct experimental evaluations of nuclear shear walls and wall-foundation joints: A large scale experimental program was completed on shear-critical RC cantilever deep beams. From these experiments, it was demonstrated that increasing rebar yield strength had a greater effect on increasing lateral strength than increasing the concrete compressive strength. Further, using HSR together with HSC resulted in the highest lateral strength and displacement ductility (Devine et al. 2018a). Additionally, large-scale reversed-cyclic lateral load tests were conducted on RC shear walls. It was demonstrated that through the utilization of HSR and HSC, a wall with 55% reduced vertical and horizontal rebar area was able to achieve 91% of the peak lateral strength of a conventional wall using state-of-practice materials with the same geometry. Further, trim reinforcement with headed anchorages around the penetrations proved to be effective. Develop validated numerical simulation models: Numerical modeling was completed in two phases during this project using 3 different finite element software packages. The first phase used existing measured data from previous experimental studies on stocky RC walls to validate simplified predictive models. Models using two different programs were validated based on a database of 38 stocky walls (Barbachyn et al., 2017a). The second phase occurred after experimental testing using a third and more detailed finite element package. Prediction improvements for the initial stiffness, lateral deformations, damage propagation, and failure mechanisms were targeted. The resulting detailed models more accurately predicted the peak lateral strength, initial and secant stiffnesses, lateral deformations, and cracking patterns of the wall test specimens subjected to reversed-cyclic lateral loading as compared to the simplified pretest models. Develop validated design procedures, tools, and criteria: This project evaluated the accuracy of existing closed-form design equations from U.S. building design standards and previous research (Barbachyn et al. 2017a and Devine et al. 2018a). It was shown that the current predictive equations for shear strength capacity need to be revisited as they provide significant scatter and gross overestimates, indicating the potential for unconservative designs. Further, for both the deep beam and shear wall specimens, the numerical models and flexural capacity predictions provided the most accurate strength predictions. Develop cost-effective field construction procedures: To promote the use of prefabricated rebar assemblies, the following construction conditions where prefabrication would be used instead of in-place rebar tying were identified from an industry survey: 1) to save on construction schedule; 2) to improve safety and/or quality control; 3) for areas with heavy rebar congestion; and 4) for structures with significant repetition in rebar layout. All of these conditions directly apply and benefit nuclear construction where construction costs and schedules are extensive, safety and quality are of utmost importance, the reinforcement is extremely dense, and the reinforcement layout is repetitive in many regions of the shear walls. Additionally, an experimental study was conducted to investigate the changes in bar spacing (with respect to code-required rebar spacing and placement tolerances) when a horizontally assembled prefabricated two-dimensional (2D) rebar mat or three-dimensional (3D) rebar cage is lifted (or tripped) to a vertical position. It was found that the bars involved in both the lateral translation of the rebar assemblies (i.e., movement of the assembly in its horizontal position) and the tripping process were most susceptible to large spacing changes, and thus, their positions within the assembly would need to be checked after the placement of the assembly in place within the formwork. Importantly, the spacings of all of the other bars in the assembly were not affected significantly by the lateral translation and tripping process, thereby eliminating the need to recheck their positions within the assembly (Devine et al. 2018b).

36 MATERIALS SCIENCE↗

A Low Loss Microstrip Antenna for Radiometric Applications

The design and analysis of a series-fed, low-loss, inverted microstrip array antenna, operating at 1.413 GHz is presented. The antenna is composed of two subarrays. Each subarray consists of an equal number of microstrip patches all connected together with microstrip lines. In the first design microstrip array for linear polarization is presented which incorporated a series feeding technique. The next design, which is capable of dual linear polarization (V-polarization and H-polarization), utilizes a corporate feed network for the V-pol and series feed arrangement for the H-pol. The first element of each subarray for H-pol is coaxially fed with a 180 deg phase difference. This approach ensures a symmetric radiation pattern on broadside in H-pol. For the V-pol two feeds are in the same phase on the two subarrays ensuring a broadside beam in V-pol. The designs presented here are simulated using the IE3D code that utilizes the method of moments. Measured results are compared with simulated results and show good agreement.

Wahid, Parveen↗

Micrometer-accuracy 2D displacement interferometer with plasmonic metasurface resonators

In this Letter, a high-accuracy, two-dimensional displacement sensor is proposed, designed, and demonstrated based on the concept of an extrinsic Fabry–Perot Interferometer. The sensor is composed of two bundled single-mode optic fibers in parallel and two plasmonic metasurface resonators inscribed on a gold substrate via a focused ion beam. The fiber end surface and the metasurface are in parallel with a small cavity between. The cavity change or Z -component displacement is determined from the pattern of interference fringes. The X -component displacement, perpendicular to the Z component, is identified from wavelength-selective metasurface resonators, which possess unique resonant wavelengths due to different nanostructure designs. The sensor was calibrated with six displacements applied through a three-axis precision linear stage. Test results indicated that the proposed interferometer can measure displacements with a maximum error of 5.4 µm or 2.2%.

Guo, Chuanrui (ORCID:0000000271412972)↗

Architecting Safer Autonomous Aviation Systems

The aviation literature gives relatively little guidance to practitioners about the specifics of architecting systems for safety, particularly the impact of architecture on allocating safety requirements, or the relative ease of system assurance resulting from system or subsystem level architectural choices. As an exemplar, this paper considers common architectural patterns used within traditional aviation systems and explores their safety and safety assurance implications when applied in the context of integrating artificial intelligence (AI) and machine learning (ML) based functionality. Considering safety as an architectural property, we discuss both the allocation of safety requirements and the architectural trade-offs involved early in the design lifecycle. This approach could be extended to other assured properties, similar to safety, such as security. We conclude with a discussion of the safety considerations that emerge in the context of candidate architectural patterns that have been proposed in the recent literature for enabling autonomy capabilities by integrating AI and ML. A recommendation is made for the generation of a property-driven architectural pattern catalogue.

Architecture patterns↗

Architecting Safer Autonomous Aviation Systems

The aviation literature gives relatively little guidance to practitioners about the specifics of architecting systems for safety, particularly the impact of architecture on allocating safety requirements, or the relative ease of system assurance resulting from system or subsystem level architectural choices. As an exemplar, this paper considers common architectural patterns used within traditional aviation systems and explores their safety and safety assurance implications when applied in the context of integrating artificial intelligence (AI) and machine learning (ML) based functionality. Considering safety as an architectural property, we discuss both the allocation of safety requirements and the architectural trade-offs involved early in the design lifecycle. This approach could be extended to other assured properties, similar to safety, such as security. We conclude with a discussion of the safety considerations that emerge in the context of candidate architectural patterns that have been proposed in the recent literature for enabling autonomy capabilities by integrating AI and ML. A recommendation is made for the generation of a property-driven architectural pattern catalogue.

Architecture patterns↗

Design of the primary pre-TRMM and TRMM ground truth site

The primary objective of the Tropical Rain Measuring Mission (TRMM) were to: integrate the rain gage measurements with radar measurements of rainfall using the KSFC/Patrick digitized radar and associated rainfall network; delineate the major rain bearing systems over Florida using the Weather Service reported radar/rainfall distributions; combine the integrated measurements with the delineated rain bearing systems; use the results of the combined measurements and delineated rain bearing systems to represent patterns of rainfall which actually exist and contribute significantly to the rainfall to test sampling strategies and based on the results of these analyses decide upon the ground truth network; and complete the design begun in Phase 1 of a multi-scale (space and time) surface observing precipitation network centered upon KSFC. Work accomplished and in progress is discussed.

Garstang, Michael↗

Topology optimization for the design of porous electrodes

Porous electrodes are an integral part of many electrochemical devices since they have high porosity to maximize electrochemical transport and high surface area to maximize activity. Traditional porous electrode materials are typically homogeneous, stochastic collections of small-scale particles and offer few opportunities to engineer higher performance. Fortunately, recent breakthroughs in advanced and additive manufacturing are yielding new methods to structure and pattern porous electrodes across length scales. These architected electrodes are emerging as a promising new technology to continue to drive improvement; however, it is still unclear which structures to employ and few tools are available to guide their design. Here we address this gap by applying topology optimization to the design of porous electrodes. We demonstrate our framework on two applications: a porous electrode driving a steady Faradaic reaction and a transiently operated electrode in a supercapacitor. We present computationally designed electrodes that minimize energy losses in a half-cell. For low-conductivity materials, the optimization algorithm creates electrode designs with a hierarchy of length scales. Further, the designed electrodes are found to outperform undesigned, homogeneous electrodes. Finally, we present three-dimensional porous electrode designs. We thus establish a topology optimization framework for designing porous electrodes.

25 ENERGY STORAGE↗

Elucidating the speciation of extracted lanthanides by diglycolamides

Many studies over the past few decades have been devoted to addressing the application of diglycolamides (DGAs) for hydrometallurgical-based, f-element separations. Work to date has shown the molecular structure of a DGA derivative can have a significant impact on intra-lanthanide partitioning patterns. More recent studies have pushed towards probing the structure function relationship of the lanthanide-DGA complex to enable the design of more efficient lanthanide separation systems. Spectroscopic techniques, such as UV–Visible, Fourier Transformed Infrared Spectroscopy (FT-IR), Nuclear Magnetic Resonance (NMR), and Extended X-ray Absorption Fine Structure (EXAFS), provide information regarding the inner-sphere coordination of a given lanthanide-DGA complex. Scattering techniques, such as Dynamic Light Scattering (DLS), Small-Angle X-ray Scattering (SAXS), and Small-Angle Neutron Scattering (SANS), address nanoscale structures including aggregate sizes and morphology. Here, this review assesses the current state-of-knowledge regarding lanthanide-DGA hydrometallurgical (i.e., solvent extraction systems) interrogated using spectroscopic and scattering techniques to characterize the extracted Ln 3+ DGA species. Of particular interest to this review is the impact of varied diluents, inclusion and variation of phase modifiers, and DGA derivatization on system characteristics. While there has been extensive literature on the application of DGAs for f-element separations, the literature lacks a collective assessment of the speciation of Ln 3+ in the organic phase. This review provides new insights into the field of DGA separations, explicitly with an application to intra-lanthanide separations. Specifically, this review illustrates the importance of both the co-extraction anion (Cl - , NO 3 - , or ClO 4 - ) as it pertains to both the aggregate size and Ln 3+ distribution coefficient. It is evident the ability of the anion to disrupt the hydrogen bonding network limits both aggregate size and distribution coefficients according to the Hoffmeister series. This suggests the importance of the large, softer anions with a low charge-to-surface area ratio on encouraging hydrogen bond interactions. In addition, the co-extracted cation (H + vs Na + ) is important for mitigating transfer of Ln 3+ from the aqueous to the organic phase through extensive hydrogen bonding networks. These networks are responsible for forming supramolecular aggregates where a change in morphology is observed with increasing concentrations of H + and/or Ln 3+ in the organic phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗

Collective Phonon–Polaritonic Modes in Silicon Carbide Subarrays

Localized surface phonon polaritons (LSPhPs) can be implemented to engineer light–matter interactions through nanoscale patterning for a range of midinfrared application spaces. However, the polar material systems studied to date have mainly focused on simple designs featuring a single element in the periodic unit cell. Increasing the complexity of the unit cell can serve to modify the resonant near-fields and intra- and inter-unit-cell coupling as well as to dictate spectral tuning in the far-field. In this work, we exploit more complicated unit-cell structures to realize LSPhP modes with additional degrees of design freedom, which are largely unexplored. Collectively excited LSPhP modes with distinctly symmetric and antisymmetric near-fields are supported in these subarray designs, which are based on nanopillars that are scaled by the number of subarray elements to ensure a constant unit-cell size. Moreover, we observe an anomalous mode-matching of the collective symmetric mode in our fabricated subarrays that is robust to changing numbers of pillars within the subarrays as well as to defects intentionally introduced in the form of missing pillars. This work therefore illustrates the hierarchical design of tailored LSPhP resonances and modal near-field profiles simultaneously for a variety of IR applications such as surface-enhanced spectroscopies and biochemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systems biology-guided biodesign of consolidated lignin conversion

Lignin is the second most abundant biopolymer on the earth, yet its utilization for fungible products is complicated by its recalcitrant nature and remains a major challenge for sustainable lignocellulosic biorefineries. In this study, we used a systems biology approach to reveal the carbon utilization pattern and lignin degradation mechanisms in a unique lignin-utilizing Pseudomonas putida strain (A514). The mechanistic study further guided the design of three functional modules to enable a consolidated lignin bioconversion route. First, P. putida A514 mobilized a dye peroxidase-based enzymatic system for lignin depolymerization. This system could be enhanced by overexpressing a secreted multifunctional dye peroxidase to promote a two-fold enhancement of cell growth on insoluble kraft lignin. Second, A514 employed a variety of peripheral and central catabolism pathways to metabolize aromatic compounds, which can be optimized by overexpressing key enzymes. Third, the β-oxidation of fatty acid was up-regulated, whereas fatty acid synthesis was down-regulated when A514 was grown on lignin and vanillic acid. Therefore, the functional module for polyhydroxyalkanoate (PHA) production was designed to rechannel β-oxidation products. As a result, PHA content reached 73% per cell dry weight (CDW). Further integrating the three functional modules enhanced the production of PHA from kraft lignin and biorefinery waste. Furthermore, this study elucidated lignin conversion mechanisms in bacteria with potential industrial implications and laid out the concept for engineering a consolidated lignin conversion route.

59 BASIC BIOLOGICAL SCIENCES↗

Sub-10 nm patterning with DNA nanostructures: a short perspective

DNA is the hereditary material that contains our unique genetic code. Since the first demonstration of two-dimensional (2D) nanopatterns by using designed DNA origami ~10 years ago, DNA has evolved into a novel technique for 2D and 3D nanopatterning. It is now being used as a template for the creation of sub-10 nm structures via either 'top-down' or 'bottom-up' approaches for various applications spanning from nanoelectronics, plasmonic sensing, and nanophotonics. This paper starts with an histroric overview and discusses the current state-of-the-art in DNA nanolithography. Finally, emphasis is put on the challenges and prospects of DNA nanolithography as the next generation nanomanufacturing technique.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Alignment Implementation for Manufacturing using Fringe Analysis Slope Technique (AIMFAST) 2018.11.20

AIMFAST is a software code used to align facets on a dish or heliostat solar concentrator to a specific aimpoint strategy to minimize peak fluxes and maximize system optical performance. AIMFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject dish mirrors. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. This fitted comparison is then used to develop a single vector representing the orientation of the facets relative to the design orientation and provide near-real-time adjustment information to a communicating computer. The communicating computer can display adjustments or directly interface with adjustment tools.

Yellowhair, Julius↗

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Command of active and responsive elastomers by topological defects and patterns

The project resulted in the development of stimuli-responsive elastomer coatings formed by photopolymerized liquid crystal molecules. The molecular orientation of the liquid crystal elastomers is coupled to rubber-like elasticity. The project developed an approach to produce complex patterns of molecular orientation in elastomers by employing photopatterning technique based on plasmonic metamasks that convert unpolarized incoming light into a transmitted light beam with spatially-varying linear polarization. The polarization-modulated light beam aligns the film of azodye molecules, which serves as the substrate for liquid crystal elastomer coating. The alignment of the azodye molecules follows the polarization pattern with a phase shift of the alignment direction by 90 degrees. The azodye substrate imposes orientation of molecules in the adjacent liquid crystal layer which is preserved after the monomers are polymerized into a liquid crystal elastomer. By using differently aligned substrates one could produce various patterns of molecular orientation in the elastomer, which dictate the mechanical properties of the elastomers and their response to external stimuli such as temperature, humidity, and ultraviolet irradiation. In particular, the predesigned molecular orientation produces deterministically defined topography response of the liquid crystal coatings, in which their free surface changes from flat to either locally elevated or locally compressed, depending on whether the pre-inscribed molecular orientation is predesigned with a splay or bend deformation. The research established that the mechanism of this deterministic relation between the dynamic topography and pre-inscribed molecular orientation is rooted in the change of the tensorial order parameter that characterizes the degree of orientational order, and in the contraction/expansion of polymer molecules in response to the order parameter changes. In particular, lowering the order causes contraction of polymer globules. The work demonstrated that the dynamic topography of elastomer coatings with three-dimensional pattern of orientational order includes up and down motion of the material (along the normal to the coating) and also shifts in lateral directions. We demonstrate that the deterministic relationship between the orientational patterns and variations of coatings’ profile is caused by forces that are mathematically equivalent to active forces in the system of “pullers” or “pushers” in active matter, demonstrating universality of the out-of-equilibrium behavior. The project resulted in theoretical models that predictively describe the dynamic response of coatings. The topography of liquid crystal elastomers is sensitive to stimuli such as temperature, ultraviolet irradiation, and humidity. The applicability of the patterned approach to produce dynamic coatings was expanded from nematic elastomers to their smectic counterparts. The project combined a battery of imaging techniques to unveil the dynamic properties of the coatings, ranging from the state-of-the-art dynamic holographic microscopy to fluorescent confocal polarizing microscopy and polscope microscopy. The research uncovered potential applications of dynamic elastomer coatings, such as control placement of colloidal particles, engineering of living tissues with alignment patterns of cells that follow the orientational order of elastomer coatings. The approach developed in the project can be used to design programmable dynamic coatings with functionalities that mimic biological tissues such as skin.

36 MATERIALS SCIENCE↗