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Results for “Functional groups”
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Radiation Stability of the Nitrate Ester Energetic Functional Group
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Creating Databases for Training Neural Networks to Identify Functional Groups from NMR, IR, and Raman Spectroscopic Data
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Attention-Based Fusion of Infrared and Mass Spectra for Identification of Chemical Threats BY Functional Group Prediction
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Peak2Patch: High-Fidelity Functional Group Identification Through Attention-based Fusion of Infrared and Mass Spectra
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Commonality in Functional Groups on Trace Compounds in High Explosives
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Functional Group Properties and Position Drive Differences in Xenobiotic Plant Uptake Rates, but Metabolism Shares a Similar Pathway
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Mass spectrometry in structural and stereochemical problems. CXXXVII - Examples of interaction of remote functional groups after electron impact.
Cyclic ketones containing methoxyl and hydroxyl studied for oxygen rearrangement on electron impact
NMR characterization of functional groups: 9--isomer ratios of available chloromethylstyrene mixtures
From the assignments of the 1H and 13C 11.7 tesla NMR spectra of available mixtures of m- and p-chloromethylstyrene, the proportion of the meta and para compounds are easily determined. For these materials from two common commercial sources, proportions of 72 and 28% and 68 and 32% were found. These concentrations are substantially different from the often assumed 60 and 40% for the meta and para compounds, respectively. The influence of this difference on the desired properties of copolymers made from such mixtures is discussed. An alternative quantitative procedure for determining the chloromethyl group isomer ratios is also described which employs silver trifluoroacetate in acetone displacement of chloride and 19F NMR examination of the resulting ester mixture with a 2.3 tesla spectrometer.
Capitol Reef Ecological Conservation: Mapping Vegetation Functional Groups to Inform Invasive Vegetation Management, Ecological Conservation, and Restoration in Capitol Reef National Park
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Trends in electron–ion dissociative recombination of benzene analogs with functional group substitutions: Positive Hammett σpara constants
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Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry
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Plant diversity and functional identity drive grassland rhizobacterial community responses after 15 years of CO 2 and nitrogen enrichment
Abstract Improved understanding of bacterial community responses to multiple environmental filters over long time periods is a fundamental step to develop mechanistic explanations of plant–bacterial interactions as environmental change progresses. This is the first study to examine responses of grassland root‐associated bacterial communities to 15 years of experimental manipulations of plant species richness, functional group and factorial enrichment of atmospheric CO 2 (eCO 2 ) and soil nitrogen (+N). Across the experiment, plant species richness was the strongest predictor of rhizobacterial community composition, followed by +N, with no observed effect of eCO 2 . Monocultures of C 3 and C 4 grasses and legumes all exhibited dissimilar rhizobacterial communities within and among those groups. Functional responses were also dependent on plant functional group, where N 2 ‐fixation genes, NO 3− ‐reducing genes and P‐solubilizing predicted gene abundances increased under resource‐enriched conditions for grasses, but generally declined for legumes. In diverse plots with 16 plant species, the interaction of eCO 2 +N altered rhizobacterial composition, while +N increased the predicted abundance of nitrogenase‐encoding genes, and eCO 2 +N increased the predicted abundance of bacterial P‐solubilizing genes. Synthesis : Our findings suggest that rhizobacterial community structure and function will be affected by important global environmental change factors such as eCO 2 , but these responses are primarily contingent on plant species richness and the selective influence of different plant functional groups.
Discerning the thermodynamic feasibility of the spontaneous coexistence of multiple functional vegetation groups
Can the Second Law of Thermodynamics explain why ecosystems naturally organize into a complex structure composed of multiple vegetation species and functional groups? Ecosystem structure, which refers to the number and type of plant functional groups, is the result of self-organization, or the spontaneous emergence of order from random fluctuations. By considering ecosystems as open thermodynamic systems, we model and study these fluctuations of throughput signatures on short timescales to determine the drivers and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of energy and entropy to calculate an ecosystem’s estimated work and understand the thermodynamic behavior of the system. We use a multi-layer canopy-root-soil model to calculate the energy and entropy fluxes of different scenarios for field sites across various climates. At each site, scenarios comprised of native individual plant functional groups and a coexisting multi-group composition scenario including all functional groups observed at the site are compared. Ecosystem-scale calculations demonstrate that entropy fluxes and work efficiency—the work performed for the amount of radiation entering the ecosystem—are greatest in the multi-group scenario when its leaf area is significantly larger than each of its individual functional groups. Thus, we conclude that ecosystems self-organize towards the vegetation structure with the greatest outgoing entropy flux and work efficiency, resulting in the coexistence of multiple functional groups and performing the maximum amount of work within the constraints of locally available energy, water, and nutrients.
Chemical constraints governing the origin of metabolism: the thermodynamic landscape of carbon group transformations under mild aqueous conditions
The thermodynamics of organic chemistry under mild aqueous conditions was examined in order to begin to understand its influence on the structure and operation of metabolism and its antecedents. Free energies (deltaG) were estimated for four types of reactions of biochemical importance carbon-carbon bond cleavage and synthesis, hydrogen transfer between carbon groups, dehydration of alcohol groups, and aldo-keto isomerization. The energies were calculated for mainly aliphatic groups composed of carbon, hydrogen, and oxygen. The energy values showed (1) that generally when carbon-carbon bond cleavage involves groups from different functional group classes (i.e., carboxylic acids, carbonyl groups, alcohols, and hydrocarbons), the transfer of the shared electron-pair to the more reduced carbon group is energetically favored over transfer to the more oxidized carbon group, and (2) that the energy of carbon-carbon bond transformation is primarily determined by the functional group class of the group that changes oxidation state in the reaction (i.e., the functional group class of the group that donates the shared electron-pair during cleavage, or that accepts the incipient shared electron-pair during synthesis). In contrast, the energy of hydrogen transfer between carbon groups is determined by the functional group class of both the hydrogen-donor group and the hydrogen-acceptor group. From these and other observations we concluded that the chemistry involved in the origin of metabolism (and to a lesser degree modern metabolism) was strongly constrained by (1) the limited redox-based transformation energy of organic substrates that is readily dissipated in a few energetically favorable irreversible reactions; (2) the energy dominance of a few transformation half-reactions that determines whether carbon-carbon bond transformation (cleavage or synthesis) is energetically favorable (deltaG < -3.5 kcal/mol), reversible (deltaG between +/-3.5 kcal/mol), or unfavorable (deltaG > +3.5 kcal/mol); and (3) the dependence of carbon group transformation energy on the functional group class (i.e., oxidation state) of participating groups that in turn is contingent on prior reactions and precursors in the synthetic pathway.
Imine Reductase-Catalyzed, Radical-Mediated Asymmetric Cyano Group Migration
Functional group migration (FGM) reactions represent a fundamental class of transformations in organic chemistry, enabling the repositioning of functional moieties in nonobvious ways. However, catalytic asymmetric radical-mediated FGMs remain rare due to the inherent challenges of achieving catalyst-controlled enantioselectivity over free radical intermediates. Herein, we repurpose imine reductases (IREDs), a class of biotechnologically important enzymes known for their substrate promiscuity, to enable the first examples of catalytic asymmetric cyano group migration via a radical mechanism. An orthogonal set of radical enzymes, including PbaIREDCym and SmiIREDCym, was engineered, allowing both 1,4- and 1,5-cyano group migration reactions to occur in an enantiodivergent fashion. The use of the nonionic surfactant TPGS-1000 was found to improve both the yield and enantioselectivity of these cyano migration reactions. Furthermore, this biocatalytic process exhibited a broad substrate scope and is readily scalable, affording a rare example of chiral nonamine product assembly with imine reductases. More broadly, stereoselective radical biocatalysis with engineered IREDs and other versatile enzymes provides a potentially general solution to challenging asymmetric FGM reactions.
Accurate Thermochemistry of Complex Lignin Structures via Density Functional Theory, Group Additivity, and Machine Learning
A molecular-level understanding of lignin structures and bond dissociation energies could facilitate depolymerization technologies. Still, this information is currently limited due to the lack of databases and the simplification of surrogate models. Here, substitution effects on seven common linkages in lignin polymers are systematically investigated. An automated reaction network generator is employed to create a database of structures. A new group additivity (GA) model based on principal component analysis (PCA) descriptors is introduced and trained on gas-phase density functional theory data of 4100 species at the M06-2X/6-311++G(d,p) level. Hydrogen bonds, local steric, and nonaromatic ring contributions are also incorporated. Lastly, we improve the accuracy of the group additivity model to reach the G4 theory by computing a data set of 770 species at this level and using a data fusion approach.