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At least 1,225 records · Page 68

Evaluating bloom potential of the green-tide forming alga Ulva ohnoi under ocean acidification and warming

Herein we discuss the occurrence of green-tides, whose bloom potential may be increased by various human activities and biogeochemical process, results in enormous economic losses and ecosystem collapse. In this study, we investigated the ecophysiology of the subtropical green-tide forming alga, Ulva ohnoi complex (hereafter: U. ohnoi), under simulated future ocean conditions in order to predict its bloom potential using photosynthesis and growth measurements, and stable isotope analyses. Our mesocosm system included four experimental conditions that simulated the individual and combined effects of elevated CO 2 and temperature, namely control (450 μatm CO 2 & 20 °C), acidification (900 μatm CO 2 & 20 °C), warming (450 μatm CO 2 & 25 °C), and greenhouse (900 μatm CO 2 & 25 °C). Photosynthetic electron transport rates (rETR) increased significantly under acidification conditions, but net photosynthesis and growth were not affected. In contrast, rETR, net photosynthesis, and growth all decreased significantly under elevated temperature conditions (i.e. both warming and greenhouse). These results represent the imbalance of energy metabolism between electron transport and O 2 production that may be expected under ocean acidification conditions. This imbalance appears to be related to carbon and nitrogen assimilation by U. ohnoi. In particular, 13 C and 15 N discrimination data suggest U. ohnoi prefers CO 2 and NH 4 + over HCO 3 - and NO 3 - as sources of carbon and nitrogen, respectively, and this results in increased N content in the thallus under ocean acidification conditions. Together, our results suggest a trade-off in which the bloom potential of U. ohnoi could increase under ocean acidification due to greater N accumulation and through the saving of energy during carbon and nitrogen metabolism, but that elevated temperatures could decrease U. ohnoi's bloom potential through a decrease in photosynthesis and growth.

54 ENVIRONMENTAL SCIENCES↗

Chemometrics and visible diffuse reflectance spectroscopy to classify plutonium dioxide

Diffuse reflectance (DR) spectra in the Vis-NIR (∼380–1050 nm) region were acquired for a series of PuO 2 samples with a spot size of about 10 × 10 μm. Two batches of six PuO 2 samples, synthesized approximately 7.5 months apart, were prepared using both Pu(III) and Pu(IV) oxalate precursors at three distinct calcination temperatures (450, 650, and 950 °C). This yielded a total of 12 PuO 2 samples and 433 DR spectra. The DR spectrum of PuO 2 contained numerous peaks in the visible region, and characteristic features were identified with respect to calcination temperature and chemistry. A distinct peak multiplet near 615 nm was observed for samples prepared at low calcination temperatures, and a peak near 660 nm was observed for higher calcination temperatures. A multivariate classification strategy based on principal component analysis (PCA) was developed to distinguish PuO 2 calcination temperatures of 450, 650, and 950 °C with 100 % accuracy. Classification results also indicate the potential to distinguish chemical processing history (i.e., Pu(III) or Pu(IV)) based on the spectra with 72 % accuracy based on k-nearest neighbors applied to the PCA scores. Partial least squares discriminant analysis was used to identify variation among batches with 88 % accuracy and found that peaks near 669, 681, 811, and 970 nm were the most useful for predicting the batch identity. Here, this work demonstrates how micro-diffuse reflectance spectroscopy and chemometrics can be used to classify PuO 2 processing history based on Vis-NIR spectral features. Combining the chemometric approach with mapping sequences could provide a rapid, nondestructive approach to classify Pu oxide materials for environmental, forensics, and nonproliferation applications.

Actinide↗

The role of peer review and science for advancing public understanding

We live in a time of rapid change. The Covid-19 pandemic has united the world to understand and develop solutions to protect the health and wellbeing of society. At the same time, access to information on the internet and social media has exploded. People are exposed to information with many claims. Some of the information is relevant and accurate. A significant fraction may be inaccurate, biased, and potentially dangerous. With Covid-19, the information might point to cures that are toxic or risks that are not relevant. The scientific community has developed a process to develop and convey knowledge. The validation of results and their interpretation is critical to advancing knowledge. The core of the scientific process is based on developing a hypothesis-driven concept, designing and executing an experimental approach to prove or disprove the hypothesis, conducting a statistical analysis of the results to confirm their validity, and interpreting their meaning and impact. When their work is completed the scientist prepares to publish the work. Publication requires peer review. Hypotheses, experimental approaches, results, and interpretation of results are independently and anonymously reviewed by a scientific peer. The reviewers are selected based on their expertise in the field. The peer review process is essential for the integrity of the scientific process. Without a robust scientific process, society cannot discriminate between validated results and interpretations and biased, inaccurate, and potentially dangerous conjecture. With inaccurate science society and policy makers may make poor decisions that could hurt people and the world around them. While scientists should not censor information available to the public, scientists have a responsibility to inform the public. We must articulate what the scientific process is and why it is essential when considering the validity of information. Scientist are responsible for pointing out when public information has not been vetted through a scientific process and therefore cannot be considered conclusive. Scientists are responsible for highlighting information that has been generated and vetted with the scientific process. Over time, our goal is for the public to value the scientific process based on peer review. The public could become enlightened to the necessity for peer review to support decisions and action. Scientists need to contribute to advancing public knowledge. When invited to serve as a peer reviewer, scientists have a responsibility to contribute to the process. We all are extremely busy making peer review a distraction. While peer review does not directly benefit our own work and career, it benefits our chosen field of science. This is very important for the research area that our journal, Water-Energy Nexus, is focusing on. We cover the convergence of science and technology integrating across large spatial ranges (micro to global) in environmental pollution and the balance of remediation issues with energy use. Water-Energy Nexus wants to provide scientists with a platform for scientific debate and discussion on this rich and complicated topic. With the manuscripts submitted to WEN cover integrated research topics across a broad range of subjects from environment sciences through energy engineering, the role of peer review is essential. Peer review on a new submission to WEN should not be biased towards a specific science field. It should be done considering the complex nature of issues in the water-energy nexus. Scientists need to contribute to the public dialog. To accomplish these goals, we need to be honest, accurate, articulate, and use understandable language. The impact of WEN is very diverse affecting society in many ways. The scientific audience for WEN is diverse and readers may not fully understand the content of the papers outside their research expertise. Therefore, scientists, especially those who want to contribute to WEN, should work with communications specialists to convey message to benefit society. The audience includes the general public and researchers outside the author’s core specialty. While the peer-reviewed journal article is the cornerstone of our careers and critical for advancing scientific knowledge, a general interest story could benefit society even more. The author cannot lose sight that our work has two audiences, the science community, and more importantly, our family, friends, neighbors, and policy makers.

54 ENVIRONMENTAL SCIENCES↗

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Abstract Maintenance optimization is a process for improving the efficiency of maintenance strategies and activities, considering various aspects of the target system and components, such as the probabilities of system failures and the cost of repair and replacement of a failed component. The improvement of maintenance optimization algorithms generally requires information from various data sources. For example, it may require the system risk information derived from risk analysis tools or the residual lifetime of a component from fault prognosis tools. The requirements of data acquisition (DAQ) and aggregation pose new challenges for maintenance management systems (MMSs) that implement and use these maintenance optimization algorithms. This paper proposes a multiple aspects maintenance ontology-based framework to facilitate DAQ from MMSs, online monitoring systems, fault detection and discrimination tools, risk assessment tools, decision-making tools, and component identification tools, and accelerate the implementation and verification of contemporary maintenance optimization models and algorithms. The proposed framework consists of a multi-aspect maintenance ontology with critical information for maintenance optimization and application interfaces for collecting information from various data sources, such as fault prognosis tools, online monitoring tools, risk assessment tools, and decision-making algorithms. In addition, this paper proposes a heuristic method for integrating concepts and properties from other existing ontologies into the proposed framework when the existing ontology is not fully compatible with the ontology under construction. Finally, the paper verifies the proposed ontology framework using a feedwater system designed for nuclear power plants with valves and filters as the components under maintenance.

Diao, Xiaoxu (ORCID:0000000346726352)↗

An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics

Abstract Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. Scanning transmission electron microscopy (STEM), a cornerstone of the study of chemical and materials systems, stands to benefit greatly from AI-driven automation. However, present barriers to low-level instrument control, as well as generalizable and interpretable feature detection, make truly automated microscopy impractical. Here, we discuss the design of a closed-loop instrument control platform guided by emerging sparse data analytics. We hypothesize that a centralized controller, informed by machine learning combining limited a priori knowledge and task-based discrimination, could drive on-the-fly experimental decision-making. This platform may unlock practical, automated analysis of a variety of material features, enabling new high-throughput and statistical studies.

47 OTHER INSTRUMENTATION↗

Position-Specific Carbon Isotope Fingerprinting of Fluorinated Organics and Degradation Products

Fluorinated organic compounds are of growing environmental and forensic relevance due to their widespread use in pharmaceuticals, agrochemicals, and consumer products, their environmental persistence, and potential ecological and human health impacts. Elucidating their sources and transformation pathways is therefore a major focus of current research. Stable carbon isotope analysis provides a powerful approach for tracing molecular origins and linking parent compounds to degradation products. Recent isotope measurements have largely relied on mass-spectrometry techniques, which provide only an average isotope ratio across a compound. In this work, we employ a novel nuclear magnetic resonance (NMR) spectroscopy tool to determine position-specific carbon isotope ratios ( 13 C/ 12 C) in organofluorine compounds and their degradation products. This approach enables isotope measurements without combustion or extensive purification and, crucially, resolves ratios at individual carbon positions rather than bulk averages. The resulting intramolecular isotope fingerprints are unique to a molecule’s source. Applied to selected pharmaceuticals and pesticides, these fingerprints allow discrimination of chemically identical compounds. Moreover, we show that the 13 C/ 12 C signature at the fluorinated carbon persists through degradation, demonstrated for lansoprazole and fipronil. The 19 F NMR data produced for the 13 C/ 12 C analyses are also well suited for impurity profiling, providing an additional dimension for fingerprinting fluorinated organics. These findings suggest that position-specific isotope analysis can serve as part of a broader suite of tools for source characterization of organofluorine compounds and their breakdown derivatives, with potential applications in product validation, forensics, and linking these compounds to their breakdown products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective Crystallization for Green Separations of Lanthanides Using 5-(Pyrimidyl)Tetrazolate

In an effort to develop facile, low-cost, and environmentally benign separations of lanthanides, the coordination chemistry and selective crystallization of Ln 3+ cations with the water-soluble ligand 5-(pyrimidyl)tetrazolate (pmtz) have been investigated. The wide range of coordination modes of pmtz allows for discrimination between these cations, and five distinct compound types can be prepared that are dependent on the lanthanide employed. La 3+ leads to the formation of [La(pmtz) 2 (H 2 O) 6 ]Cl (S1). [Ln(pmtz) 3 (H 2 O) 3 ]·(3+n)H 2 O is obtained with Ce 3+ and Pr 3+ (S2). Ce 3+ can also form [(Ce(pmtz) 2 (H 2 O) 3 ) 2 (μ-pmtz)](pmtz)·11H 2 O (S3). [(Ln(pmtz) 2 (H 2 O) 3 ) 2 (μ-pmtz)] 2 (pmtz) 2 ·14H 2 O (S4) is formed with Nd 3+ and Sm 3+ . Here, the smaller Ln 3+ cations, Dy 3+ to Lu 3+ , all yield [Ln(H 2 O) 8 ](pmtz) 3 ·3H 2 O (S5). This selective crystallization of Ln 3+ cations based primarily on ionic radii provides a simple method for achieving group separations.

Bai, Zhuanling↗

Mechanistically Informed Strategies for Site-Selective Atomic Layer Deposition

While atomic layer deposition (ALD) processes from across the periodic table have been designed to deposit conformal thin films, an atomistic view of disparate substrate sites reveals the possibility of even greater synthetic control and precision. An understanding of the mechanism by which a particular ALD precursor reacts (or does not react) at myriad surface sites remains in its infancy. Here, in this Perspective, we summarize site-specific chemical reaction strategies that utilize ALD precursors and tailored surface chemistry to discriminate among potential deposition sites as well as describe techniques and tools that can be used to investigate site-selective ALD (SS-ALD). The Perspective is focused on the science of site-selective vapor-phase surface reactions but inevitably reveals the potential utility of such surface synthetic precision.

36 MATERIALS SCIENCE↗

Microbial Communities Associated with Methylmercury Degradation in Paddy Soils

Bioaccumulation of the neurotoxin methylmercury (MeHg) in rice has raised worldwide concerns because of its risks to human health. Certain microorganisms are able to degrade MeHg in pure cultures, but the roles and diversities of the microbial communities in MeHg degradation in rice paddy soils are unknown. Using a series of microcosms, we investigated MeHg degradation in paddy soils from Hunan, Guizhou, and Hubei provinces, representing three major rice production regions in China, and further characterized one of the soils from the Hunan Province for microbial communities associated with MeHg degradation. Microbial demethylation was observed in all three soils, demonstrated by significantly more MeHg degraded in the unsterilized soils than in the sterilized controls. More demethylation occurred in water-saturated soils than in unsaturated soils, but the addition of molybdate and bromoethanesulfonic acid as the respective inhibitors of sulfate reducing bacteria and methanogens showed insignificant effects on MeHg degradation. However, the addition of Cu enhanced MeHg degradation and the enrichment of Xanthomonadaceae in the unsaturated soil. 16S rRNA Illumina sequencing and metatranscriptomic analyses of the Hunan soil consistently revealed that Catenulisporaceae, Frankiaceae, Mycobacteriaceae, and Thermomonosporaceae were among the most likely microbial taxa in influencing MeHg degradation in the paddy soil, and they were confirmed by combined analyses of the co-occurrence network, random forest modeling, and linear discriminant analysis of the effect size. Furthermore, our results shed additional light onto the roles of microbial communities in MeHg degradation in paddy soils and its subsequent bioaccumulation in rice grains.

59 BASIC BIOLOGICAL SCIENCES↗

Controlling Extraction of Rare Earth Elements Using Functionalized Aryl-vinyl Phosphonic Acid Esters

Ligands that can discriminate between individual rare earth elements are important for production of these critical elements. A set of aryl-vinyl phosphonic acid ligands for extracting rare earth elements were designed and synthesized under the hypothesis that the strength of the rare earth-ligand interactions could be tuned by changing the dipole moment of the ligand. The ligands were synthesized via a two-step reaction procedure using a Heck coupling reaction to functionalize vinyl phosphonic acid, followed by Steglich esterification to obtain high-purity styryl phosphonic acid monoesters with varying dipole moments along the P-C bond. The metal binding strength and composition of the rare earth complexes formed with these styryl phosphonic acid monoesters were experimentally studied by liquid-liquid extraction techniques, while DFT calculations were performed to determine the dipole moments of the free and complexed ligands and the electronic structure of the complexes formed. All three prepared ligands were much stronger extracting agents for europium(III) than the dialkylphosphonic acids usually used for this separation. However, the order of increasing extraction strength was found to match the order of the decreasing calculated dipole moment along the P-C bond of the three styryl-based ligands, rather than correlating with increasing ligand basicity, as reflected by the pK a of the ligands. Finally, these findings suggest that this approach can be used to systematically alter the extraction strength of aromatic phosphonic monoesters for rare earth element purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗

Fingerprinting Uranium Oxides with Electron Energy Loss Spectroscopy Supported by Theoretical Computations

Uranium oxides occur in a variety of phases that differ in crystal structure and uranium oxidation states. Electron energy loss spectroscopy (EELS) is one of the few techniques that has sufficient spatial resolution and sensitivity to electronic structure to distinguish amongst phases at the nanoscale. However, beam-sensitive materials such as uranium oxides are subject to spectral modification due to interactions with the electron beam. Therefore, theory support is essential to reliably exclude the impact of beam damage and generate true reference datasets. Here we use a comparison of theoretical and experimental spectra to probe the impact of beam damage on O K-edge and U N-edge (N6,7 and N4,5) EELS spectra of various single-valent and mixed-valence uranium oxide bulk phases. Using a low-dose experimental set-up, we show that the O K-edge theoretical spectra are in excellent agreement with experiment for both peak positions and relative intensities of respective peaks. In contrast, U N-edge features are less distinguishing due to the partially localized nature of the U 5f orbitals and overlapping multiplet and spin–orbit coupling effects. This work demonstrates that O K-edge EELS is sufficiently diagnostic to distinguish a wide range of uranium oxides and that the experimental approach used here minimizes beam damage and allows valence state discrimination across the U(IV), U(V) and U(VI) series. When combined with imaging modes available in electron mi-croscopy, the work enables detailed investigation and characterization of uranium redox transformations at the nanoscale.

Carbone, Jacopo↗

Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. Here we show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)–to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. Furthermore, these results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intermediate Species in the Crystallization of Sodium Aluminate Hydroxy Hydrates

In highly alkaline “water-in-salt” Na 2 O/Al 2 O 3 /H 2 O solutions where the monomeric Al(OH) 4 - anion dominates, isolation of transitional species that seed crystallization of sodium aluminate salt hydrates has been challenging. For example, discrimination of dimeric [e.g., Al 2 O(OH) 6 2- ] from species via 27 Al nuclear magnetic resonance (NMR) spectroscopy is limited via fast interconversion through hydrolysis and condensation reactions. Despite this, using magic-angle spinning NMR ( 27 Al MAS NMR) at high magnetic field strengths (14.1 and 20.0 T) on crystals of nonasodium bis(hexahydroxyaluminate) trihydroxide hexahydrate [NSA, Na 9 [Al(OH) 6 ] 2 ·3(OH)·6(H 2 O)], we observed a 27 Al resonance consistent with Na 2 Al 2 O(OH) 6 . This tetrahedral dimeric species was also identified in the mother liquor by Raman spectroscopy while remaining expectedly unresolved by high-field liquid-state 27 Al NMR. Its substantial abundance in the mother liquor and as either an interstitial or an adsorbate on precipitated solids suggest that it plays a crucial role in NSA crystallization. Here, our detailed characterization, which includes single-pulse 27 Al MAS NMR, nutation 27 Al MAS NMR, and multiple quantum 27 Al MAS NMR, provides new molecular insights into how aluminate transitions from tetrahedral in solution to octahedral in solid. This understanding could ultimately lead to better predictions of aluminum phase change behavior in caustic sodium hydroxide with wide-ranging technological and environmental implications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering the Functional Role of Coherent Phonons during the Photoinduced Phase Transition in a Molecular Crystal

The atomic motions that make up phonons and molecular vibrations in molecular crystals influence their photophysical and electronic properties, including polaron formation, carrier mobility, and phase transitions. Discriminating between spectator and driving motions is a significant challenge hindering optimization. Unlocking this information and developing fine-tuned controls over actively participating phonon modes would not only lead to a stronger understanding of photochemistry but also provide a significant new tool in controlling solid state chemistry. We present a strategy using rationally designed double pulses to unveil the unique function of specific excited state phonon modes. Using ultrafast spectroscopy, we identified 50 and 90 cm –1 phonons involved in modulating the photoinduced spin-Peierls melting of potassium tetracyanoquinodimethane crystals. Here, we show that the 50 cm –1 phonon specifically corresponds to the coherent nuclear wavepacket involved in the charge transfer component of the overall spin-Peierls phase melting process, while the 90 cm –1 phonon facilitates the phase transition component.

74 ATOMIC AND MOLECULAR PHYSICS↗

How to Get the Best Gas Separation Membranes from State-of-the-Art Glassy Polymers

Herein we focus on fundamental polymer science factors in membrane-based gas separation to open another chapter on this important topic. Realistically thinking about nano and angstrom scale matrix attributes that are translatable into higher performance thin glassy polymer asymmetric membrane layers in practical large-scale devices is crucial. Such thinking should be guided by expertise in both polymer and membrane communities to advance the state of the art. Polymer structures, membrane morphologies and effects of operating conditions are discussed here, using specific examples to illustrate key issues. Rubbery polymers are not the focus of this discussion, since they lack diffusive discrimination for size-similar penetrants, which glassy polymers provide and make them the focus here. Four scalable subtopics guide necessary thinking: (i) plasticization; (ii) anti-plasticization†2; (iii) dual-mode transport involving saturation of unrelaxed free volume, and (iv) non-uniform free volume and stress profiles in thin skin glassy polymer asymmetric or composite membranes. Furthermore, using these subtopics in the context of macromolecular science we discuss issues needed to expand the state-of-the-art in gas separation membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoresponsive Azobenzene-Functionalized Shell Cross-Linked Micelles for Selective Asymmetric Transfer Hydrogenation

We describe the substrate-selective asymmetric transfer hydrogenation of aromatic ketones using rhodium complexes immobilized on a photoresponsive nanoreactor. The nanoreactor is based on multifunctional amphiphilic poly(2-oxazoline)s that are covalently cross-linked with functionalized azobenzene after micelle formation in water. The nanoreactor switches its morphology upon light irradiation in a wavelength-selective manner as confirmed by dynamic light scattering. Kinetic studies show that the gated behavior induced by the phototriggered reversible isomerization of trans- azobenzene to cis- azobenzene in the cross-linking layer is key to discriminate among substrates and reagents during catalysis. Under UV light irradiation, the diffusion of larger substrates into the core is slower in comparison to smaller substrates. The nanoreactor displays substrate selectivity, converting smaller ketone-substrates faster to the corresponding secondary alcohols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗