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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Recurrent flow analysis in spatiotemporally chaotic 2-dimensional Kolmogorov flow

Motivated by recent success in the dynamical systems approach to transitional flow, we study the efficiency and effectiveness of extracting simple invariant sets (recurrent flows) directly from chaotic/turbulent flows and the potential of these sets for providing predictions of certain statistics of the flow. Two-dimensional Kolmogorov flow (the 2D Navier-Stokes equations with a sinusoidal body force) is studied both over a square [0, 2π]{sup 2} torus and a rectangular torus extended in the forcing direction. In the former case, an order of magnitude more recurrent flows are found than previously [G. J. Chandler and R. R. Kerswell, “Invariant recurrent solutions embedded in a turbulent two-dimensional Kolmogorov flow,” J. Fluid Mech. 722, 554–595 (2013)] and shown to give improved predictions for the dissipation and energy pdfs of the chaos via periodic orbit theory. Analysis of the recurrent flows shows that the energy is largely trapped in the smallest wavenumbers through a combination of the inverse cascade process and a feature of the advective nonlinearity in 2D. Over the extended torus at low forcing amplitudes, some extracted states mimic the statistics of the spatially localised chaos present surprisingly well recalling the findings of Kawahara and Kida [“Periodic motion embedded in plane Couette turbulence: Regeneration cycle and burst,” J. Fluid Mech. 449, 291 (2001)] in low-Reynolds-number plane Couette flow. At higher forcing amplitudes, however, success is limited highlighting the increased dimensionality of the chaos and the need for larger data sets. Algorithmic developments to improve the extraction procedure are discussed.

42 ENGINEERING↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ammonia pretreatment of corn stover enables facile lignin extraction

Thermochemical pretreatment of lignocellulose is often employed to render polysaccharides more digestible by carbohydrate-active enzymes to maximize sugar yields. The fate of lignin during pretreatment, however, is highly dependent on the chemistry employed and must be considered in cases where lignin valorization is targeted alongside sugar conversion—an important feature of future biorefinery development. Here, a two-step process is demonstrated in which anhydrous ammonia (AA) pretreatment is followed by mild NaOH extraction on corn stover to solubilize and fractionate lignin. As known, AA pretreatment simultaneously alters the structure of cellulose with enhanced digestibility while redistributing lignin. The AA-pretreated residue is then extracted with dilute NaOH at mild conditions to maximize lignin separation, resulting in a digestible carbohydrate-rich solid fraction and a solubilized lignin stream. Lignin removal of more than 65% with over 84% carbohydrate retention is achieved after mild NaOH extraction of AA-pretreated corn stover with 0.1 M NaOH at 25 °C. Two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy of the AA-pretreated residue shows that ammonolysis of ester bonds occurs to partially liberate hydroxycinnamic acids, and the AA-pretreated/NaOH-extracted residue exhibits a global reduction of all lignin moieties caused by reduced lignin content. A significant reduction (~70%) in the weight-average molecular weight ( M w ) of extracted lignin is also achieved. Imaging of AA-pretreated/NaOH extracted residues show extensive delamination and disappearance of coalesced lignin globules from within the secondary cell walls. Glycome profiling analyses demonstrates ultrastructural level cell wall modifications induced by AA pretreatment and NaOH extraction, resulting in enhanced extractability of hemicellulosic glycans, indicating enhanced polysaccharide accessibility. The glucose and xylose yields from enzymatic hydrolysis of AA-pretreated/NaOH-extracted corn stover were higher by ~80% and ~60%, respectively, compared to untreated corn stover at 1% solids loadings. For digestions at 20% solids, a benefit of NaOH extraction is realized in achieving ~150 g/L of total monomeric sugars (glucose, xylose, and arabinose) in the enzymatic hydrolysates from AA-pretreated/NaOH-extracted corn stover. Altogether, this process enables facile lignin extraction in tandem with a leading thermochemical pretreatment approach, demonstrating excellent retention of highly digestible polysaccharides in the solid phase and a highly depolymerized, soluble lignin-rich stream.

09 BIOMASS FUELS↗
DOE OSTI2020

An experimental investigation of the effectiveness of Ar-CO 2 shielding gas mixture for the wire arc additive process

Wire arc additive manufacturing (AM) is the process by which a large, metallic structure is built layer-by-layer using a welding arc to melt a wire feedstock. A novel opportunity exists to alter the shielding gas composition to fabricate distinct geometrical features without altering the other AM parameters. In this paper, shielding gases with varied concentrations of Argon (Ar) and CO 2 was used to deposit three distinct geometric shapes (walls, infill, and overhang) using a wire-based additive manufacturing system utilizing the gas metal arc welding (GMAW) surface tension transfer (STT) process. Computer-aided design (CAD) models were sliced with a custom-built slicer, and the sliced algorithm was converted into optimal robotic toolpaths. A custom virtual instrument (VI) was built in LabVIEW to compare the temperature profiles on the surface during each deposition process. After each deposition, the geometric features were scanned, and the surface waviness value was evaluated. Tensile and Charpy impact coupons were extracted from the wall geometries in the longitudinal and transverse directions and tested. The results indicated that a higher CO 2 content produced higher melt pool temperatures to an extent, while lower contents of CO 2 resulted in a dimensionally accurate geometry. The data also indicated that the 2%/98% CO 2 /Ar blend produced scatter in tensile strength and the analysis of variance (ANOVA) shows significant difference. However, the intermediate range of CO 2 (5–10%) resulted in uniform tensile properties. Altogether, these results indicate that a 5%/95% CO 2 /Ar blend is the ideal shielding gas for lowering process temperatures and improving mechanical properties in wire arc additive manufacturing using the gas metal arc welding surface tension transfer process. Additionally, varying concentrations of Ar/CO 2 can be used within the same part in order to modify the local properties or process parameters such as strength, toughness, temperature, or dimensional features. This may improve overall manufacturing quality without sacrificing specific properties.

42 ENGINEERING↗
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A phantom design for assessment of detectability in PET imaging

Purpose: The primary clinical role of positron emission tomography (PET) imaging is the detection of anomalous regions of {sup 18}F-FDG uptake, which are often indicative of malignant lesions. The goal of this work was to create a task-configurable fillable phantom for realistic measurements of detectability in PET imaging. Design goals included simplicity, adjustable feature size, realistic size and contrast levels, and inclusion of a lumpy (i.e., heterogeneous) background. Methods: The detection targets were hollow 3D-printed dodecahedral nylon features. The exostructure sphere-like features created voids in a background of small, solid non-porous plastic (acrylic) spheres inside a fillable tank. The features filled at full concentration while the background concentration was reduced due to filling only between the solid spheres. Results: Multiple iterations of feature size and phantom construction were used to determine a configuration at the limit of detectability for a PET/CT system. A full-scale design used a 20 cm uniform cylinder (head-size) filled with a fixed pattern of features at a contrast of approximately 3:1. Known signal-present and signal-absent PET sub-images were extracted from multiple scans of the same phantom and with detectability in a challenging (i.e., useful) range. These images enabled calculation and comparison of the quantitative observer detectability metrics between scanner designs and image reconstruction methods. The phantom design has several advantages including filling simplicity, wall-less contrast features, the control of the detectability range via feature size, and a clinically realistic lumpy background. Conclusions: This phantom provides a practical method for testing and comparison of lesion detectability as a function of imaging system, acquisition parameters, and image reconstruction methods and parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Analysis of Sample DUM002 (INL pin casting, 800C/48 hr, 500C 8 hr): Metallographic re-prep, FIB TEM foil extraction and (S)TEM analysis [Slides]

The scale of FIB foils versus the microstructure makes it likely that more than one feature of interest may be in each FIB foil prepared. Intergranular and intragranular silicides and carbides are present. It may be that the silicides are the more potent nuclea9on sites, by initial impressions without statistics. Non-statistical measurements of the lamellar spacing average approximately 300 to 500 nm. Measured U-Mo ratios via EDS were near expectations, even without the need for standards, simplifying analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Crack detection in fuel cell electrodes using a spatial filtering technique for overcoming noisy backgrounds

Image processing is a powerful tool that allows for rapid and automated data parsing in settings that occupy large variable spaces and require large data sets. Feature detection on difficultly discerned backgrounds is a subset of image processing that facilitates the extraction of quantitative metrics from otherwise subjective data. Crack detection and quantification is an important capability in polymer electrolyte membrane fuel cell quality control, failure analysis, and optimization. This work presents a technique to perform crack detection and quantification which overcomes challenges faced by commonly used image segmentation techniques. We demonstrate the use of a geometrically filtered noise‐level detection technique to select a binary threshold value from which we then quantify how cracked a sample is. Furthermore, we demonstrate the accuracy of our technique using programmatically generated test images of known crack amounts and their performance on real‐world fuel cell catalyst layer samples.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Linkages Between Mineral Element Composition of Soils and Sediments With Hyporheic Zone Dissolved Organic Matter Chemistry Across the Contiguous United States

The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x-ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo-metal linkages into multi-scale hydrobiogeochemical models.

58 GEOSCIENCES↗
DOE OSTI2014

Design study of a 17.3 GHz electron cyclotron resonance (ECR) ion source at Louvain-la-Neuve

The Cyclotron Resources Center of the Louvain-la-Neuve University is developing a new electron cyclotron resonance ion source to increase the energy of the accelerated beam by injection of higher charge state ions into the cyclotron. The design of the source is based on a 17.3 GHz frequency and classical coils to produce the axial field. The field reaches 2 T at the injection side and 1.2 T at extraction. The total power consumption for the coils is limited to 80 kW. The design features of the source are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

PERIODIC SIGNALS IN BINARY MICROLENSING EVENTS

Gravitational microlensing events are powerful tools for the study of stellar populations. In particular, they can be used to discover and study a variety of binary systems. A large number of binary lenses have already been found through microlensing surveys and a few of these systems show strong evidence of orbital motion on the timescale of the lensing event. We expect that more binary lenses of this kind will be detected in the future. For binaries whose orbital period is comparable to the event duration, the orbital motion can cause the lensing signal to deviate drastically from that of a static binary lens. The most striking property of such light curves is the presence of quasi-periodic features, which are produced as the source traverses the same regions in the rotating lens plane. These repeating features contain information about the orbital period of the lens. If this period can be extracted, then much can be learned about the lensing system even without performing time-consuming, detailed light-curve modeling. However, the relative transverse motion between the source and the lens significantly complicates the problem of period extraction. To resolve this difficulty, we present a modification of the standard Lomb–Scargle periodogram analysis. We test our method for four representative binary lens systems and demonstrate its efficiency in correctly extracting binary orbital periods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers

Abstract Motivation Deep learning has revolutionized protein tertiary structure prediction recently. The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy tertiary structures for most individual protein chains. However, the accuracy of predicting quaternary structures of protein complexes consisting of multiple chains is still relatively low due to lack of advanced deep learning methods in the field. Because interchain residue–residue contacts can be used as distance restraints to guide quaternary structure modeling, here we develop a deep dilated convolutional residual network method (DRCon) to predict interchain residue–residue contacts in homodimers from residue–residue co-evolutionary signals derived from multiple sequence alignments of monomers, intrachain residue–residue contacts of monomers extracted from true/predicted tertiary structures or predicted by deep learning, and other sequence and structural features. Results Tested on three homodimer test datasets (Homo_std dataset, DeepHomo dataset and CASP-CAPRI dataset), the precision of DRCon for top L/5 interchain contact predictions (L: length of monomer in a homodimer) is 43.46%, 47.10% and 33.50% respectively at 6 Å contact threshold, which is substantially better than DeepHomo and DNCON2_inter and similar to Glinter. Moreover, our experiments demonstrate that using predicted tertiary structure or intrachain contacts of monomers in the unbound state as input, DRCon still performs well, even though its accuracy is lower than using true tertiary structures in the bound state are used as input. Finally, our case study shows that good interchain contact predictions can be used to build high-accuracy quaternary structure models of homodimers. Availability and implementation The source code of DRCon is available at https://github.com/jianlin-cheng/DRCon. The datasets are available at https://zenodo.org/record/5998532#.YgF70vXMKsB. Supplementary information Supplementary data are available at Bioinformatics online.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Inferring the Dynamics of the State Evolution During Quantum Annealing

To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we propose to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Furthermore, using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called "slicing", we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits.

42 ENGINEERING↗
DOE OSTI2014

Structure and stabilization of hydrogen-rich transverse jets in a vitiated turbulent flow

This paper reports the results of a joint experimental and numerical study of the ow characteristics and flame stabilization of a hydrogen rich jet injected normal to a turbulent, vitiated cross ow of lean methane combustion products. Simultaneous high-speed stereoscopic PIV and OH PLIF measurements were obtained and analyzed alongside three-dimensional direct numerical simulations of inert and reacting JICF with detailed H 2 /CO chemistry. Both the experiment and the simulation reveal that, contrary to most previous studies of reacting JICF stabilized in low-to-moderate temperature air cross ow, the present conditions lead to an autoigniting, burner-attached flame that initiates uniformly around the burner edge. Significant asymmetry is observed, however, between the reaction zones located on the windward and leeward sides of the jet, due to the substantially different scalar dissipation rates. The windward reaction zone is much thinner in the near field, while also exhibiting significantly higher local and global heat release than the much broader reaction zone found on the leeward side of the jet. The unsteady dynamics of the windward shear layer, which largely control the important jet/cross flow mixing processes in that region, are explored in order to elucidate the important flow stability implications arising in the reacting JICF. Vorticity spectra extracted from the windward shear layer reveal that the reacting jet is globally unstable and features two high frequency peaks, including a fundamental mode whose Strouhal number of ~0.7 agrees well with previous non-reacting JICF stability studies. The paper concludes with an analysis of the ignition, ame stabilization, and global structure of the burner-attached flame. Chemical explosive mode analysis (CEMA) shows that the entire windward shear layer, and a large region on the leeward side of the jet, are highly explosive prior to ignition and are dominated by non-premixed flame structures after ignition. The predominantly mixing limited nature of the flow after ignition is confirmed by computing the Takeno flame index, which shows that ~70% of the heat release occurs in non-premixed regions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Study on high-flux laser ion source with applying magnetic field

The laser ion source is a technology where by irradiating a solid target with a pulsed laser of high intensity (10 8 W/cm 2 ~), ablation plasma is generated, and by applying there an external electric field for extracting and accelerating ions, high brightness ion beams are produced. This paper introduced the basic features of laser ion source and recent movement of the control of laser ion source using magnetic field. In the development of heavy ion inertial fusion (HIF) driver, engineers are challenging new tasks of supplying low valence, large current, and low emittance beams. In order to respond to the requirements of large current beams in HIF driver, attempts have been made to control the plasma via magnetic field to further increase the flux. The current of the laser ion source with application of solenoid magnetic field is dramatically improved and its amplification magnification can be adjusted by changing the position, length, and magnetic flux density of the solenoid. In order to further control the laser ion source toward HIF, the authors propose the guiding of plasma via multiple cusp magnetic field, and the guiding effect is being demonstrated through examination. According to the studies so far, the laser ion source can supply ion beams using a simple configuration, so it is suitable for miniaturization and may be adopted at many accelerator facilities. (A.O.)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗
DOE OSTI2019

MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases

Purpose: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. Methods: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unrespectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size. Texture analysis was quantified on T2-weighted images by two radiologists with consensus on regions of interest which were manually drawn on the largest cross-sectional area of the lesions. Five histogram features (mean, variance, skewness, kurtosis, and entropy{sup 1}) and five gray level co-occurrence matrix features (GLCM; angular second moment (ASM), entropy{sup 2}, contrast, correlation, and inverse difference moment (IDM)) were extracted. The texture parameters were statistically analyzed to identify the differences between the two groups, and the potential predictive parameters to differentiate the responding group from the non-responding group were subsequently tested using multivariable logistic regression analysis. Results: A total of 107 responding and 86 non-responding lesions were evaluated. A higher variance, entropy{sup 1}, contrast, entropy{sup 2} and a lower ASM, correlation, IDM were independently (P < 0.05) associated with a good response to chemotherapy with the areas under the ROC curves (AUCs) of 0.602–0.784. Variance (P < 0.001) and ASM (P = 0.001) remained potential predictive values to discriminate responding lesions from non-responding lesions when tested using multivariable logistic regression analysis. The highest AUC of the predictors from the association of variance and ASM was 0.814. Conclusion: MR texture features on pre-treated T2 images have the potential to predict the therapeutic response of colorectal liver metastases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Soft Materials Constructed Using Calix[4]pyrrole- and “Texas-Sized” Box-Based Anion Receptors

We present that soft materials have received considerable attention from supramolecular chemists and material scientists alike. This interest reflects the advantages provided by their soft, flexible nature and the convenience of the molecular self-assembly that underlies their preparation. Common soft supramolecular materials include polymeric gels, supramolecular polymers, nanoaggregates, and membranes. Polymeric gels are solidlike networks of cross-linked polymer chains. Supramolecular polymers contain repeat units connected through reversible non-covalent bonds. Nanoaggregates are formed as a result of hydrophobic interactions involving amphiphilic building blocks. Because of the presence of non-covalent interactions, supramolecular soft materials typically display stimuli-responsive or adaptive features. Various macrocyclic hosts, such as cyclodextrins, crown ethers, calixarenes, cucurbiturils, and pillararenes, and many classic non-covalent interactions have been harnessed to construct supramolecular soft materials. Only recently has anion binding been used as the underlying recognition motif. Anions are ubiquitous in the natural world. Their importance has inspired efforts to achieve good anion binding and to exploit anion recognition in a number of fields, including extraction, transport, sensing, and catalysis. Most of this effort has involved the use of stand-alone anion receptors. On the other hand, soft materials with anion recognition features could lead to new macromolecular systems of interest in the context of many application areas. In this Account, we summarize the latest efforts from our laboratory to prepare supramolecular soft materials, including polymeric gels, supramolecular polymers, and nanoaggregates, with bona fide anion recognition features. Two anion receptor systems, namely, calix[4]pyrroles (C4Ps) and a tetraimidazolium macrocycle known as the “Texas-sized” molecular box (TxSB), have been used for this purpose. To date, TxSB-based hydrogels have been utilized to capture anions from water and for coded information applications; C4P-based organic polymeric gels have been used to extract dianions from aqueous source phases and for the on-site detection of chloride anions. Polymers containing C4P and TxSB anion recognition subunits typically display responsive features and can be modified through application of appropriately chosen external stimuli. For instance, nanoaggregates may be formed as a result of the hydrophobic interactions of C4P- and TxSB-based amphiphiles. The resulting aggregates were found to mimic the structural evolution of organelles and could be used as effective anion and ion pair extractants. This Account summarizes progress to date while underscoring potential opportunities associated with combining anion recognition and soft materials chemistry. Finally, the hope is to stimulate further advances in broad areas, including polymer science, supramolecular chemistry, biology, materials research, and information storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗