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At least 1,765 records · Page 98

Review of methods to probe single cell metabolism and bioenergetics

The sampling and manipulation of cells down to the individual has been of substantial interest since the very beginning of Life Sciences. Herein, our objective is to highlight the most recent developments in single cell manipulation, as well as pioneering ones. First, flow-through methods will be discussed, namely methods in which the single cells flow continuously in an ordered manner during their analysis. This section will be followed by confinement techniques that enable cell isolation and confinement in one, two- or three-dimensions. Flow cytometry and droplet microfluidics are the two most common methods of flow-through analysis. While both are high-throughput techniques, their difference lays in the fact that the droplet encapsulated cells experience a restricted and personal microenvironment, while in flow cytometry cells experience similar nutrient and stimuli initial concentrations. These methods are rather well established; however, they recently enabled immense strides in single cell phenotypic analysis, namely the identification and analysis of metabolically distinct individuals from an isogenic population using both droplet microfluidics and flow cytometry.

59 BASIC BIOLOGICAL SCIENCES↗

Engineering high-level production of fatty alcohols by Saccharomyces cerevisiae from lignocellulosic feedstocks

Fatty alcohols in the C12-C18 range are used in personal care products, lubricants, and potentially biofuels. These compounds can be produced from the fatty acid pathway by a fatty acid reductase (FAR), yet yields from the preferred industrial host Saccharomyces cerevisiae remain under 2% of the theoretical maximum from glucose. Here we improved titer and yield of fatty alcohols using an approach involving quantitative analysis of protein levels and metabolic flux, engineering enzyme level and localization, pull-push-block engineering of carbon flux, and cofactor balancing. We compared four heterologous FARs, finding highest activity and endoplasmic reticulum localization from a Mus musculus FAR. After screening an additional twenty-one single-gene edits, we identified increasing FAR expression; deleting competing reactions encoded by DGA1, HFD1, and ADH6; overexpressing a mutant acetyl-CoA carboxylase; limiting NADPH and carbon usage by the glutamate dehydrogenase encoded by GDH1; and overexpressing the Δ9-desaturase encoded by OLE1 as successful strategies to improve titer. Our final strain produced 1.2 g/L fatty alcohols in shake flasks, and 6.0 g/L in fed-batch fermentation, corresponding to ~ 20% of the maximum theoretical yield from glucose, the highest titers and yields reported to date in S. cerevisiae. We further demonstrate high-level production from lignocellulosic feedstocks derived from ionic-liquid treated switchgrass and sorghum, reaching 0.7 g/L in shake flasks. Together, our work represents progress towards efficient and renewable microbial production of fatty acid-derived products.

09 BIOMASS FUELS↗

177 Lu and 227 Th Labeled 3,4,3-(LI-1,2-HOPO): characterization, optimized synthesis, biological distribution and dosimetry

Objectives: Interest in targeted radionuclide therapy has greatly increased namely due to the FDA approval of radiotherapeutic drugs such as Lutathera The identification of chelators that can bind diag- nostic and therapeutic radionuclides would allow facile development of agents tailored for personalized medicine. Hydroxypyridinonate (HOPO) derivatives have been demonstrated as effective decorpo- ration agents for actinides owing to their hard oxygen donor atoms and strong complexation. Utilizing these molecules as chelators for potential nuclear medicine agents should allow for radiometals to be effectively sequestered by the ligand. The aim of this work was to evaluate the in vivo stability of 3-4-3-(LI-1,2-HOPO) (HOPO for short) with 177 Lu and 227 Th as potential beta- and alpha-emitting radiothera- peutic complexes, respectively.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The impact of urban configuration types on urban heat islands, air pollution, CO 2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanized. As cities around the world continue to grow, it is important for urban planners and policymakers to understand how different urban configuration patterns affect the environment and human health. We aimed at identifying European urban configuration types, based on the Local Climate Zones categories and street design variables from Open Street Map, and evaluating their association with motorized traffic flows, Surface Urban Heat Island (SUHI) intensities, tropospheric nitrogen dioxide (NO 2 ), CO 2 per capita emissions and age-standardized mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low-density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low-density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO 2 exposure were significantly higher in compact high density and open low rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low-density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO 2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bioinorganic Life and Neural Activity: Toward a Chemistry of Consciousness?

Identifying what elements are required for neural activity as potential path toward consciousness, which represents life with the state or quality of awareness, is a "Holy Grail" of chemistry. As life itself arises from coordinated interactions between elements across the periodic table, the majority of which are metals, new approaches for analysis, binding, and control of these primary chemical entities can help enrich our understanding of inorganic chemistry in living systems in a context that is both universal and personal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical Detection of Oxycodone and Its Main Metabolites with Nafion-Coated Single-Walled Carbon Nanotube Electrodes

Oxycodone is a strong opioid frequently used as an analgesic. Although proven efficacious in the management of moderate to severe acute pain and cancer pain, use of oxycodone imposes a risk of adverse effects such as addiction, overdose, and death. Fast and accurate determination of oxycodone blood concentration would enable personalized dosing and monitoring of the analgesic as well as quick diagnostics of possible overdose in emergency care. However, in addition to the parent drug, several metabolites are always present in the blood after a dose of oxycodone, and to date, there is no electrochemical data available on any of these metabolites. In this paper, a single-walled carbon nanotube (SWCNT) electrode and a Nafion-coated SWCNT electrode were used, for the first time, to study the electrochemical behavior of oxycodone and its two main metabolites, noroxycodone and oxymorphone. Both electrode types could selectively detect oxycodone in the presence of noroxycodone and oxymorphone. However, we have previously shown that addition of a Nafion coating on top of the SWCNT electrode is essential for direct measurements in complex biological matrices. Therefore, in this work, the Nafion/SWCNT electrode was further characterized and used for measuring clinically relevant concentrations of oxycodone in buffer solution. The limit of detection for oxycodone with the Nafion/SWCNT sensor was 85 nM, and the linear range was 0.5–10 μM in buffer solution. Furthermore, this study shows that the fabricated Nafion/SWCNT sensor has potential to be applied in clinical concentration measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. Finally, we explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanopillar-based enhanced-fluorescence detection of sur-face-immobilized beryllium.

The unique properties associated with beryllium metal ensures the continued use in many industries despite the documented health and environmental risks. While engineered safeguards and personal protective equipment can reduce risks associated with working with the metal, it has been mandated by the Environmental Protection Agency (EPA) and Occupational Safety and Health Administration (OSHA) that the workplace air and surfaces must be monitored for toxic levels. While many methods have been developed to monitor levels down to the low μg/m 3 , the complexity and expense of these methods have driven the investigation into alternate methodologies. Herein, we use a combination of the previously developed fluorescence Be(II) ion detection reagent, 10-hydroxybenzo[h]quinoline (HBQ), with an optical field enhanced silicon nanopillar array, creating a new surface immobilized (si-HBQ) platform. The si-HBQ platform allows the positive control of the reagent for demonstrated reusability and a pillar diameter based tunable enhancement. Furthermore, native silicon nanopillars are overcoated with thin layers of porous silicon oxide to develop an analytical platform capable of a 0.0006 μg/L limit of detection (LOD) using sub-μL sample volumes. Additionally, we demonstrate a method to multiplex the introduction of the sample to the platform, with minimal 5.2% relative standard deviation (RSD) at 0.1 μg/L, to accommodate the potentially large number of samples needed to maintain industrial compliance. The minimal sample and reagent volumes and lack of complex and highly specific instrumentation, as well as positive control and reusability of traditionally consumable reagents, create a platform that is both accessible and economically advantageous.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure, Hydration, and Interactions of Native and Hydrophobically Modified Phytoglycogen Nanoparticles

Phytoglycogen is a highly branched polymer of glucose produced as soft, compact nanoparticles by sweet corn. Properties such as softness, porosity, and mechanical integrity, combined with nontoxicity and biodegradability, make phytoglycogen nanoparticles ideal for applications involving the human body, ranging from skin moisturizing and rejuvenation agents in personal care formulations to functional therapeutics in biomedicine. To further broaden the range of applications, phytoglycogen nanoparticles can be chemically modified with hydrophobic species such as octenyl succinic anhydride (OSA). In this study, we present a self-consistent model of the particle structure, water content, and degree of chemical modification of the particles, as well as the emergence of well-defined interparticle spacings in concentrated dispersions, based on small-angle neutron scattering (SANS) measurements of aqueous dispersions of native phytoglycogen nanoparticles and particles that were hydrophobically modified using octenyl succinic anhydride (OSA) in both its protiated (pOSA) and deuterated (dOSA) forms. Measurements on native particles with reduced polydispersity have allowed us to refine the particle morphology, which is well described by a hairy particle (core-chain) geometry with short chains decorating the surface of the particles. The isotopic variants of OSA-modified particles enhanced the scattering contrast for neutrons, revealing lightly modified hairy chains for small degrees of substitution (DS) of OSA, and a raspberry particle geometry for the largest DS value, where the OSA-modified hairy chains collapse to form small seeds on the surface of the particles. This refined model of native and OSA-modified phytoglycogen nanoparticles establishes a quantitative basis for the development of new applications of this promising sustainable nanotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of Metal Cocatalysts in the Photocatalytic Production of Hydrogen from Water Revisited

The use of photocatalysts to promote the production of molecular hydrogen from water, following the so-called water splitting reaction, continues to be a promising route for the green production of fuels. The molecular basis of this photocatalysis is the photoexcitation of electrons from the valence band of semiconductors to their conduction band, from which they can be transferred to chemical reactants, protons in the case of water, to promote a reduction reaction. The mechanism by which such a process takes place has been studied extensively using titanium oxide, a simple material that fulfills most requirements for water splitting. However, photocatalysis with TiO 2 tends to be highly inefficient; a cocatalyst, commonly a late transition metal (Au, Pt) in nanoparticle form, needs to be added to facilitate the production of H 2 . The metal is widely believed to help with the scavenging of the excited electrons from the conduction band of the semiconductor in order to prevent their recombination with the accompanying hole formed in the valence band, a step that cancels the initial photon absorption and competes with the photolytic chemical reduction. Here we review and analyze the molecular basis for that mechanism and argue for an alternative explanation, that the role of the metal is to help with the recombination of the atomic hydrogen atoms produced by proton reduction on the semiconductor surface instead. First, we summarize what is known about the electronic structure of these photocatalysts and how the electronic levels need to line up for the reduction of protons in water to be feasible. Next, we review the current understanding of the dynamics of the steps associated with the absorption of photons, the de-excitation via electron–hole pair recombination and fluorescence decay, and the electronic transitions that lead to proton reduction, and contrast those with the rates of the chemical steps required to produce molecular hydrogen. The following section addresses the changes introduced by the addition of the metal cocatalyst, comparatively evaluating its role as either an electron scavenger or a promoter of the recombination of hydrogen atoms. A discussion of the viable chemical mechanisms for the latter pathway is included. Finally, we briefly mention other associated aspects of this photocatalysis, including the possible promotion of H 2 production with visible light via resonant excitation of the surface plasmon of Au nanoparticles, the use of single-metal (Au, Pt) atom catalysts and of yolk–shell nanostructures, and the reduction of organic molecules. We end with a brief personal perspective on the possible generality of the concepts introduced in this Critical Review.

08 HYDROGEN↗

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

54 ENVIRONMENTAL SCIENCES↗

Effective Remediation of Groundwater Fluoride with Inexpensively Processed Indian Bauxite

India represents one-third of the world’s fluorosis burden and is the fifth global producer of bauxite ore, which has previously been identified as a potential resource for remediating fluoride-contaminated groundwater in impoverished communities. In this work, we use thermal activation and/or groundwater acidification to enhance fluoride adsorption by Indian bauxite obtained from Visakhapatnam, an area proximate to endemic fluorosis regions. We compare combinatorial water treatment and bauxite-processing scenarios through batch adsorption experiments, material characterization, and detailed cost analyses. Heating Indian bauxite above 300 °C increases available surface area by > 15× (to ~170 m 2 /g) through gibbsite dehydroxylation and reduces the bauxite dose for remediating 10 ppm F – to 1.5 ppm F – by ~93% (to 21 g/L). Additionally, lowering groundwater pH to 6.0 with HCl or CO 2 further reduces the average required bauxite doses by 43–73% for ores heated at 300 °C (~12 g/L) and 100 °C (~77 g/L). Product water in most examined treatment scenarios complies with EPA standards for drinking water (e.g., As, Cd, Pb, etc.) but potential leaching of Al, Mn, and Cr is of concern in some scenarios. Among the defluoridation options explored here, bauxite heated at 300 °C in acidified groundwater has the lowest direct costs ($6.86 per person per year) and material-intensity.

54 ENVIRONMENTAL SCIENCES↗

The Chemistry Graduate Student Experience: Findings from an ACS Survey

Graduate training is a key element in producing a scientific workforce that reflects the nation’s diversity. This paper examines data from a 2013 American Chemical Society (ACS) survey of 2,544 chemistry masters and doctoral students and reveals barriers to reaching this goal. Multivariate statistical analyses indicate that women reported significantly less supportive relationships with advisors. Women were less likely to plan to finish their degrees, and for PhD students, the discrepancy was larger for students at the start of their graduate program. Women were also less likely to pursue the next level of training, and the gender difference related to postdoctoral plans was greater for those who identified with a racial-ethnic group traditionally underrepresented in chemistry (underrepresented minority, URM). URM students who were beyond the first year of their graduate program reported significantly less supportive relationships with peers. They were also less likely to have funding sufficient to meet their needs and more often used personal resources including loans. Despite these difficulties, URM students were more likely to definitely plan to finish their degrees, and men who identified as URM were more likely to plan to pursue postdoctoral work. Independent of gender and identification as URMs, students in more highly ranked schools reported less advisor support. Extensive open-ended comments indicated that large proportions of the students desired more attention and meaningful feedback from advisors and changes within their programs to promote support for students and advisor accountability. Suggestions for future research are given, and a companion commentary discusses needed directions for change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge

Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information gleaned from the scientific literature can help inform and accelerate nanomaterials development, but again, searching the literature and digesting the information are time-consuming manual processes for researchers. To help address these challenges, here we developed scientific article-processing tools that extract and structure information from the text and figures of nanomaterials articles, thereby enabling the creation of a personalized knowledgebase for nanomaterials synthesis that can be mined to help inform further nanomaterials development. Starting with a corpus of ~35k nanomaterials-related articles, we developed models to classify articles according to the nanomaterial composition and morphology, extract synthesis protocols from within the articles’ text, and extract, normalize, and categorize chemical terms within synthesis protocols. We demonstrate the efficiency of the proposed pipeline on an expert-labeled set of nanomaterials synthesis articles, achieving 100% accuracy on composition prediction, 95% accuracy on morphology prediction, 0.99 AUC on protocol identification, and up to a 0.87 F1-score on chemical entity recognition. In addition to processing articles’ text, microscopy images of nanomaterials within the articles are also automatically identified and analyzed to determine the nanomaterials’ morphologies and size distributions. To enable users to easily explore the database, we developed a complementary browser-based visualization tool that provides flexibility in comparing across subsets of articles of interest. We use these tools and information to identify trends in nanomaterials synthesis, such as the correlation of certain reagents with various nanomaterial morphologies, which is useful in guiding hypotheses and reducing the potential parameter space during experimental design.

36 MATERIALS SCIENCE↗

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ensemble-Based Replica Exchange Alchemical Free Energy Methods: The Effect of Protein Mutations on Inhibitor Binding

According to the article, the accurate prediction of the binding affinity changes of drugs caused by protein mutations is a major goal in clinical personalized medicine. We have developed an ensemble-based free energy approach called thermodynamic integration with enhanced sampling (TIES), which yields accurate, precise, and reproducible binding affinities. TIES has been shown to perform well for predictions of free energy differences of congeneric ligands to a wide range of target proteins. We have recently introduced variants of TIES, which incorporate the enhanced sampling technique REST2 (replica exchange with solute tempering) and the free energy estimator MBAR (Bennett acceptance ratio). Here we further extend the TIES methodology to study relative binding affinities caused by protein mutations when bound to a ligand, a variant which we call TIES-PM. We apply TIES-PM to fibroblast growth factor receptor 3 (FGFR3) to investigate binding free energy changes upon protein mutations. The results show that TIES-PM with REST2 successfully captures a large conformational change and generates correct free energy differences caused by a gatekeeper mutation located in the binding pocket. Simulations without REST2 fail to overcome the energy barrier between the conformations, and hence the results are highly sensitive to the initial structures. We also discuss situations where REST2 does not improve the accuracy of predictions.

59 BASIC BIOLOGICAL SCIENCES↗

Catechol-Ligated Transition Metals: A Quantum Chemical Study on a Promising System for Gas Separation

We report that metal-organic frameworks (MOFs) have received a great deal of attention for their potential in atmospheric filtering, and recent work has shown that catecholate linkers can bind metals, creating MOFs with monocatecholate metal centers and abundant open coordination sites. In this study, M-catecholate systems (with M = Mg 2+ , Sc 2+ , Ti 2+ , V 2+ , Cr 2+ , Mn 2+ , Fe 2+ , Co 2+ , Ni 2+ , Cu 2+ , and Zn 2+ ) were used as computational models of metalated catecholate linkers in MOFs. Nitric oxide (NO) is a radical molecule that is considered an environmental pollutant and is toxic if inhaled in large quantities. Binding NO is of interest in creating atmospheric filters, both at the industrial and personal scale. The binding energies of NO to the metal-catecholate systems were calculated using density functional theory (DFT) and complete active space self-consistent field (CASSCF) followed by second order perturbation (CASPT2). Selectivity was studied by calculating the binding energies of additional guests (CO, NH 3 , H 2 O, N 2 , and CO 2 ). The toxic guests have stronger binding than the benign guests for all metals studied, and NO has significantly stronger binding than other guests for most of the metals studied, suggesting that metal-catecholates are worthy of further study for NO filtration. Finally, certain metal-catecholates also showed potential for separation of N 2 and CO 2 via N 2 activation, which could be relevant for carbon capture or ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗