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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tuning the reactivity of carbon surfaces with oxygen-containing functional groups

Oxygen-containing carbons are promising supports and metal-free catalysts for many reactions. However, distinguishing the role of various oxygen functional groups and quantifying and tuning each functionality is still difficult. Here we investigate the role of Brønsted acidic oxygen-containing functional groups by synthesizing a diverse library of materials. By combining acid-catalyzed elimination probe chemistry, comprehensive surface characterizations, 15N isotopically labeled acetonitrile adsorption coupled with magic-angle spinning nuclear magnetic resonance, machine learning, and density-functional theory calculations, we demonstrate that phenolic is the main acid site in gas-phase chemistries and unexpectedly carboxylic groups are much less acidic than phenolic groups in the graphitized mesoporous carbon due to electron density delocalization induced by the aromatic rings of graphitic carbon. The methodology can identify acidic sites in oxygenated carbon materials in solid acid catalyst-driven chemistry.

Zhou, Jiahua↗
DOE OSTI2020

Evaluating the impact of functional groups on membrane‐mediated CO 2 / N 2 gas separations using a common polymer backbone

Abstract Polymeric membranes have shown tremendous promise for the separation of CO 2 from flue gas streams. However, few systematic studies have been conducted to better understand the impact that chemical functionalities have on membrane‐based gas separation performance. To address this gap, we herein describe the synthesis and gas separation performance of a series of vinyl‐addition polynorbornenes bearing various CO 2 ‐philic functional groups. To facilitate direct comparison between functional groups, each material was designed to maintain a common polymer backbone. Though the incorporation of CO 2 ‐philic moieties within a dense polymeric membrane is frequently hypothesized to enhance CO 2 solubility, and thereby increase CO 2 /N 2 selectivity, our results demonstrate that the incorporation of CO 2 ‐philic groups onto a common polymer backbone do not necessarily result in increased gas separation performance. Experimental and computational results demonstrate that the incorporation of amidoxime groups onto a polynorbornene backbone increase CO 2 /N 2 selectivity, whereas commonly employed ethereal side chains only increased permeability.

Higgins, Morgan A.↗
DOE OSTI2025

Chemical Functional Groups Regulate Ion Concentrations and pHs in Nanopores

Understanding ion behaviors in functionalized nanopores is essential to deciphering reactions in both natural and engineered systems, such as sediments, biological ion channels, and membranes. While many efforts have shown the modified ion behaviors in the functionalized nanopores, a direct measurement and analysis to show how chemical functional groups affect ion concentrations in nanopores are critically needed. In this work, we present a plasmonic nanosensor that can measure the local concentrations of protons, anions (phosphate, nitrate, sulfate, and arsenate), and cations (mercury, lead, and copper) in functionalized nanopores, and we compare their concentrations in nanopores with the corresponding bulk concentrations. Notably, chemical functional groups induced ion concentrations differently in nanopores. In pristine nanopores and methyl- and phenyl-functionalized nanopores, we discovered an unexpected concurrence of an enhanced anion concentration and a suppressed cation concentration. In addition, the nanopore pH is dependent on bulk solution compositions and can be lower by 2.5 units, even when the bulk solution is well-buffered. In contrast, for hydrophilic (amine, thiol, and carboxyl) nanopores, pH depended on the p K a of the functional groups, and the heavy metal concentrations depended on chemical interactions with the functional groups. Our findings provide a better understanding of water chemistry in nanopores and can help precisely control ions in nanopores to benefit the design of membrane-based desalination techniques, CO 2 storage, and porous catalysts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Functional Groups Based on Leaf Physiology: Are they Spatially and Temporally Robust?

The functional grouping hypothesis, which suggests that complexity in ecosystem function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species in fire maintained Florida scrub regulate exchange of carbon and water with the atmosphere as indicated by both instantaneous gas exchange measurements and integrated measures of function (%N, delta C-13, delta N-15, C-N ratio). Using cluster analysis, five distinct physiologically-based functional groups were identified in the fire maintained scrub. These functional groups were tested to determine if they were robust spatially, temporally, and with management regime. Analysis of Similarities (ANOSIM), a non-parametric multivariate analysis, indicated that these five physiologically-based groupings were not altered by plot differences (R = -0.115, p = 0.893) or by the three different management regimes; prescribed burn, mechanically treated and burn, and fire-suppressed (R = 0.018, p = 0.349). The physiological groupings also remained robust between the two climatically different years 1999 and 2000 (R = -0.027, p = 0.725). Easy-to-measure morphological characteristics indicating functional groups would be more practical for scaling and modeling ecosystem processes than detailed gas-exchange measurements, therefore we tested a variety of morphological characteristics as functional indicators. A combination of non-parametric multivariate techniques (Hierarchical cluster analysis, non-metric Multi-Dimensional Scaling, and ANOSIM) were used to compare the ability of life form, leaf thickness, and specific leaf area classifications to identify the physiologically-based functional groups. Life form classifications (ANOSIM; R = 0.629, p 0.001) were able to depict the physiological groupings more adequately than either specific leaf area (ANOSIM; R = 0.426, p = 0.001) or leaf thickness (ANOSIM; R 0.344, p 0.001). The ability of life forms to depict the physiological groupings was improved by separating the parasitic Ximenia americana from the shrub category (ANOSIM; R = 0.794, p = 0.001). Therefore, a life form classification including parasites was determined to be a good indicator of the physiological processes of scrub species, and would be a useful method of grouping for scaling physiological processes to the ecosystem level.

Foster, Tammy E.↗
DOE OSTI2023

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Efficient Pd on carbon catalyst for ammonium formate dehydrogenation: Effect of surface oxygen functional groups

Formate solution is one of a kind promising liquid organic hydrogen carrier but suffers from kinetic challenges. This study investigates the kinetics of the surfacefunctionalized Pd on carbon catalysts for formate dehydrogenation and the impact of O-functional groups. Here, the fraction of the distinguished O-functional groups was modulated by the different concentrated HNO 3 solutions treatment or by H 2 reduction. This study shows that the O-functional groups play critical roles in dispersing Pd nanoparticles and decreasing the activation energy for dehydrogenation. Density functional theory (DFT) calculation reveals that most O-functional groups enhance formate adsorption on the Pd active site. However, the existence of C=O groups consumes reducing agents and hinders the formation of metallic Pd. The electron transfer from Pd to oxygen functional groups is unfavorable to dehydrogenation. The as-prepared Pd5/re-ACA (reduced activated carbon washed by acid) exhibited significant activity with a higher turnover frequency of 13,511 h -1 than commercial Pd/C.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Functional Groups Based on Leaf Physiology: Are they Spatially and Temporally Robust?

The functional grouping hypothesis, which suggests that complexity in function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species in fire maintained FL scrub function in terms of carbon, water and nitrogen dynamics. The suite of physiologic parameters measured to determine function included both instantaneous gas exchange measurements obtained from photosynthetic light response curves and integrated measures of function. Using cluster analysis, five distinct physiologically-based functional groups were identified. Using non-parametric multivariate analyses, it was determined that these five groupings were not altered by plot differences or by the three different management regimes; prescribed burn, mechanically treated and burn, and fire-suppressed. The physiological groupings also remained robust between the two years 1999 and 2000. In order for these groupings to be of use for scaling ecosystem processes, there needs to be an easy-to-measure morphological indicator of function. Life form classifications were able to depict the physiological groupings more adequately than either specific leaf area or leaf thickness. THe ability of life forms to depict the groupings was improved by separating the parasitic Ximenia americana from the shrub category.

Foster, Tammy E.↗
DOE OSTI2021

The Significance of Aggregation Methods in Functional Group Modeling

The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic processes vary among species. An innovation in solving this challenge is the recognition that species can be lumped into “functional groups” based on metabolic similarity, and these functional groups can then be studied in computational models that simulate ecosystem function. Despite the vast resources devoted to functional group studies and the progress made by them, an important logical and biological question has not been formally addressed, “How do the groupings alter the results of modeling studies?” To what extent do modeling results depend on the choices made in aggregating taxa into functional groups. Here, we consider the effects of using different aggregation strategies in simulating the carbon dynamics of a deciduous forest. Understanding the impacts that aggregation strategy has on efforts to simulate regional-to-global-scale forest dynamics offers insights into both ecosystem regulation and model function and addresses this central problem in the study of carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impact of functional groups on the electrocatalytic hydrogenation of aromatic carbonyls to alcohols

We report that electrocatalytic hydrogenation (ECH) of biomass-derived feedstocks has a critical dependence on the molecular structure of the organic and its adsorption on the electrode surface. In this study, we investigated the role of functional groups in the adsorption of the organic molecule on the charged Pd (111) surface and its subsequent effect on organic reduction in electrochemical hydrogenation of organic molecules. With three aromatic carbonyls of benzaldehyde (BZD), acetophenone (ACE), and vanillin (VAN), we rationalize molecular-scale adsorption and interfacial charge transfer processes by employing density-functional-theory based ab initio molecular dynamics simulations. We observe that the functional group and electrode charge strongly affect the proximity of organic molecule to the Pd (111) surface, where distances of aromatic ring and carbonyl group of the organic on the electrode change distinctively with functional groups and charge state of electrode, which strongly impact reduction of organics on the surface. Calculations of differential electron density show the strongest reduction with benzaldehyde via interfacial electron transfer from the charged Pd surface. We also observe that the interaction between the functional groups and solvent (VAN > BZD > ACE) significantly influence the organic interaction with the charged electrode (BZD > VAN > ACE), resulting in the net interaction energy between the organic and the electrode in the order of BZD > ACE > VAN. Experimental measurement of ECH rate also show the same trend of the net interaction energy. These results demonstrate the significance of solvent effect on the reducibility of organic molecules on electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electrochemical CO 2 Reduction Reaction over Cu Nanoparticles with Tunable Activity and Selectivity Mediated by Functional Groups in Polymeric Binder

Electrochemical carbon dioxide reduction reaction (CO 2 RR) using copper (Cu)-based catalysts has received significant attention mainly because Cu is an element capable of producing hydrocarbons and oxygenates. One possible way to control the CO 2 RR performance at the electrode interface is by modifying catalysts with specific functional groups of different polymeric binders, which are necessary components in the process of electrode fabrication. However, the modification effect of the key functional groups on the CO 2 RR activity and selectivity is poorly understood over Cu-based catalysts. In this work, the role of functional groups (e.g., -COOH and -CF 2 groups) in hydrophilic and hydrophobic polymeric binders on the CO 2 RR of Cu-based catalysts is investigated using a combination of electrochemical measurements, in-situ characterization and density functional theory (DFT) calculations. DFT results reveal that functional groups influence the binding energies of key intermediates involved in both CO 2 RR and the competing hydrogen evolution reaction, consistent with experimental observation of binder-dependent product distributions among formic acid, CO, CH 4 , and H 2 . This study provides a fundamental understanding that the selection of desired polymeric binders is a useful strategy for tuning the CO 2 RR activity and selectivity.

25 ENERGY STORAGE↗
DOE OSTI2024

From individual leaves to forest stands: importance of niche, distance decay, and stochasticity vary by ecosystem type and functional group for fungal community composition

Abstract Community assembly is influenced by environmental niche processes as well as stochastic processes that can be spatially dependent (e.g. dispersal limitation) or independent (e.g. priority effects). Here, we sampled senesced tree leaves as unit habitats to investigate fungal community assembly at two spatial scales: (i) small neighborhoods of overlapping leaves from differing tree species and (ii) forest stands of differing ecosystem types. Among forest stands, ecosystem type explained the most variation in community composition. Among adjacent leaves within stands, variability in fungal composition was surprisingly high. Leaf type was more important in stands with high soil fertility and dominated by differing tree mycorrhizal types (sugar maple vs. basswood or red oak), whereas distance decay was more important in oak-dominated forest stands with low soil fertility. Abundance of functional groups was explained by environmental factors, but predictors of taxonomic composition within differing functional groups were highly variable. These results suggest that fungal community assembly processes are clearest for functional group abundances and large spatial scales. Understanding fungal community assembly at smaller spatial scales will benefit from further study focusing on differences in drivers for different ecosystems and functional groups, as well as the importance of spatially independent factors such as priority effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structure Activity Relationships for Second‐Coordination Sphere Functional Group Dependent CO 2 Reduction by Manganese Bipyridyl Electrocatalysts

Abstract A series of twelve second coordination sphere (SCS) functionalized manganese tricarbonyl bipyridyl complexes are investigated for their electrocatalytic CO 2 reduction properties in acetonitrile. A qualitative and quantitative assessment of the SCS functional groups is discussed with respect to the catalysts’ thermodynamic and kinetic efficiencies, and their product selectivities. In probing a broad scope of functional groups, it is clear that only the aprotic ortho‐arylester SCS is capable of promoting the highly desired low‐overpotential proton‐transfer electron‐transfer (PT‐ET) pathway for selective CO production. The ortho‐phenolic analogues cause an increase in overpotential with a product selectivity favoring H 2 evolution, consistent with a high‐overpotential pathway via the anionic [Mn−H] − intermediate. Alternative aprotic Lewis base functional groups such as trifluoromethyl, morpholine and acetamide are shown to also be capable of intermediate manganese hydride generation. The tertiary amine substituent, 2‐morpholinophenyl, exhibits a desirable product distribution characteristic of syn‐gas (CO : H 2 =30 : 48) with an impressive turnover frequency, while the secondary amine group, 2‐acetamidophenyl, induces a notable shift in selectivity with a faradaic yield of 55 % for the formate (HCO 2 − ) product. In addition to their catalytic properties, cyclic voltammetry and infrared spectroelectrochemistry (IR‐SEC) studies are presented to probe pre‐catalyst electronic properties and the two‐electron reduction activation pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗
DOE OSTI2023

Surface Functional Groups Affect Iron (Hydr)oxide Heterogeneous Nucleation: Implications for Membrane Scaling

Because of its favorable thermodynamics and fast kinetics, heterogeneous solid nucleation on membranes triggers early-stage mineral scaling. Iron (hydr)oxide, a typical membrane scale, initially forms as nanoparticles that interact with surface functional groups on membranes, but these nanoscale phenomena are difficult to observe in real time. In this study, we utilized in situ grazing incidence small angle X-ray scattering and ex situ atomic force microscopy to examine the heterogeneous nucleation of iron (hydr)oxide on surface functional groups commonly used in membranes, including hydroxyl (OH), carboxyl (COOH), and fluoro (F) groups. We found that, compared to nucleation on hydrophilic OH- and COOH-surfaces, the high hydrophobicity of an F-modified surface significantly reduced the extents of both heterogeneously and homogeneously formed iron (hydr)oxide nucleation. Moreover, on the OH-surface, the high functional group density of 0.76 nmol/cm 2 caused faster heterogeneous nucleation than that on a COOH-surface, with a density of 0.28 ± 0.04 nmol/cm 2 . The F-surface also had the highest heterogeneous nucleation energy barrier (26 ± 0.6 kJ/mol), followed by COOH- (23 ±0.8 kJ/mol) and OH- (20 ± 0.9 kJ/mol) surfaces. The kinetic and thermodynamic information provided here will help us better predict the rates and extents of early-stage scaling of iron (hydr)oxide nanoparticles in membrane processes. Finally, this work provides both kinetic and thermodynamic information about iron (hydr)oxide nucleation controlled by membrane-related functional groups (OH, COOH, and F).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

General Strategy for Incorporation of Functional Group Handles into Covalent Organic Frameworks via the Ugi Reaction

The library of imine-linked covalent organic frameworks (COFs) has grown significantly over the last two decades, featuring a variety of morphologies, pore sizes, and applications. An array of synthetic methods has been developed to expand the scope of the COF functionalities; however, most of these methods were designed to introduce functional scaffolds tailored to a specific application. Having a general approach to diversify COFs via late-stage incorporation of functional group handles would greatly facilitate the transformation of these materials into platforms for a variety of useful applications. In this paper, we report a general strategy to introduce functional group handles in COFs via the Ugi multicomponent reaction. To demonstrate the versatility of this approach, we have synthesized two COFs with hexagonal and kagome morphologies. We then introduced azide, alkyne, and vinyl functional groups, which could be readily utilized for a variety of post-synthetic modifications. This facile approach enables the functionalization of any COFs containing imine linkages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The effect of chemical functional groups on the octane sensitivity of fuel blends for spark-ignited and multimode engines

We report the octane sensitivity of fuel blends containing blendstocks of diverse chemical functionalities blended in concentrations up to 20% by volume into BOBs (Blendstocks for Oxygenate Blending). This study focuses on the blendstocks containing functional groups which lack reliable octane number data. The effects on octane sensitivity of blends of cyclopropanes, alkyl carbonates, oxiranes, alcohols, ketones, esters, nitrogen-containing compounds, cyclic and olefinic hydrocarbons, multifunctional materials containing combinations of these functionalities, and the co-blends of the blendstocks with ethanol in a BOB have been evaluated. Octane sensitivity of the blends containing functional groups that haven’t been evaluated before are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗