Understanding formation thermodynamics of structurally diverse zeolite oligomers with first principles calculations
Formation Thermodynamics of zeolite oligomers.
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Formation Thermodynamics of zeolite oligomers.
Drinking water treatment residuals (DWTRs) are complex mixtures of organic and inorganic phases generally disposed of as waste materials. However, their strong sorptive properties could be further exploited to immobilize contaminants. To characterize these materials, we applied a range of analytical techniques to a set of aluminum-based DWTRs. Here we determined surface areas, elemental compositions using CHNS analysis and X-ray fluorescence (XRF), performed thermogravimetric analyses paired with mass spectrometry (TGA-MS), and used synchrotron-based methods: X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS). Elemental analyses and specific surface area measurements – that vary between 7.23 ± 0.03 and 197.6 ± 0.9 m 2 g –1 – indicate that non-coagulant additives must play an important role in controlling sorption. High resolution powder XRD reveals the presence of only a few crystalline minerals mostly derived from source waters or additives. Fe was detected by XRF in all samples, whereas Mn was present in significant levels in samples with potassium permanganate as additive. The chemical speciation of these elements was characterized by performing spectral decompositions of XAS spectra. The spectral features of Fe are consistent with iron(III) oxides/hydroxides and structural iron in clays. On the other hand, Mn is predominantly present under its reduced form, Mn(II).
Xanthohumol, the principle prenylflavonoid found in hops ( Humulus lupulus ) and a reported anti-inflammatory agent, has great potential for pharmaceutical interventions related to inflammatory disorders in the gut.
The broader impacts of and social influences on scientific research were integrated into graduate education in chemistry.
Low-boiling alkylamines such as butylamine offer promise as effective biomass pretreatment solvents that can be readily recovered and recycled; however, their capability to support microbial conversion of nutrients present in hydrolysates represents an important area for investigation. Here we employed butylamine to pretreat poplar biomass and characterize its effects on the release of fermentable sugars after solvent removal and enzymatic hydrolysis, as well as the biocompatibility of the produced hydrolysates with three organisms commonly used as bioconversion hosts. We observed that residual butylamine and the derivative butylacetamide were present in high enough concentrations to exert toxicity to strains of Aspergillus niger, Pseudomonas putida, and Rhodosporidium toruloides that produce malic acid, isoprenol and bisabolene, respectively. Removal of the toxic compounds by charcoal filtration and nutrient supplementation resulted in a hydrolysate containing >100 g L −1 of sugars that enabled strong growth, substrate consumption and bioproduct accumulation, outperforming defined cultivation media. This is the first demonstration of a butylamine-based deconstruction process for poplar biomass at a pilot-scale to achieve conversion of high sugar concentrations to valuable bioproducts with engineered microbes.
Post-polymerization modification allows for the incorporation of functional groups that would otherwise be incompatible with polymerization conditions, enhancing synthetic efficiency and facilitating the creation of complex polymer architectures for specialized applications, such as biomedical devices, electronics, and advanced coatings. Herein, we report a method inspired by late-stage functionalization of small molecules for the post-polymerization modification of aromatic polymers, specifically polystyrene (PS), under mild reaction conditions. First, PS was converted to polystyrene sulfonamide (PSSNH 2 ) with an 85% yield using established procedures. PSSNH 2 was subsequently transformed into a reactive sulfinate by deamination using an N-heterocyclic carbene (NHC) catalyst and benzaldehyde. The catalytic process was optimized by varying catalysts, solvents, bases, temperatures, and reaction times. The highest degree of deamination was 88% with a bicyclic NHC and K 2 CO 3 base in DMSO for 18 hours at 120 °C. The reactive sulfinate was then treated with various functional reagents, resulting in a library of aromatic polymers with different substituents with high degrees of functionalization ranging from 74% to 98%. Similarly, we modified expanded PS waste with trifluorobutyl iodide with a degree of functionalization of 72%, highlighting a new avenue for plastic upgrading. This approach could be used to rapidly generate functionalized polymers from PS with potential applications, including antibacterial properties and flame retardancy.
Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.
The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (E vac ) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 E vac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 E vac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.
Significance The long-term effects of rising atmospheric carbon dioxide (CO 2 ), high rates of nitrogen deposition, and declining plant biodiversity on ecosystem carbon pools are uncertain and rarely assessed in concert yet represent key feedbacks to global climate change. In a 19-y study in an open-air grassland experiment, increasing planted species richness substantially enhanced ecosystem carbon storage, while elevated CO 2 and nitrogen addition treatments had only modest effects. Effects of the three global changes were largely additive, and stronger effects of species richness compared with CO 2 or nitrogen resulted from large enhancements in plant productivity relative to ecosystem losses. Our results suggest that biodiversity losses may influence carbon storage as much as or more than rising CO 2 or high nitrogen deposition rates.
Pseudouridine (Ψ) is a ubiquitous RNA modification incorporated by pseudouridine synthase (Pus) enzymes into hundreds of noncoding and protein-coding RNA substrates. Here, in this study, we determined the contributions of substrate structure and protein sequence to binding and catalysis by pseudouridine synthase 7 (Pus7), one of the principal messenger RNA (mRNA) modifying enzymes. Pus7 is distinct among the eukaryotic Pus proteins because it modifies a wider variety of substrates and shares limited homology with other Pus family members. We solved the crystal structure of Saccharomyces cerevisiae Pus7, detailing the architecture of the eukaryotic-specific insertions thought to be responsible for the expanded substrate scope of Pus7. Additionally, we identified an insertion domain in the protein that fine-tunes Pus7 activity both in vitro and in cells. These data demonstrate that Pus7 preferentially binds substrates possessing the previously identified UGUAR (R = purine) consensus sequence and that RNA secondary structure is not a strong requirement for Pus7-binding. In contrast, the rate constants and extent of Ψ incorporation are more influenced by RNA structure, with Pus7 modifying UGUAR sequences in less-structured contexts more efficiently both in vitro and in cells. Although less-structured substrates were preferred, Pus7 fully modified every transfer RNA, mRNA, and nonnatural RNA containing the consensus recognition sequence that we tested. Our findings suggest that Pus7 is a promiscuous enzyme and lead us to propose that factors beyond inherent enzyme properties (e.g., enzyme localization, RNA structure, and competition with other RNA-binding proteins) largely dictate Pus7 substrate selection.
<Type IV pili (T4P) are ubiquitous in both bacteria and archaea. They are polymers of the major pilin protein, which has an extended and protruding N-terminal helix, α1, and a globular C-terminal domain. Cryo-EM structures have revealed key differences between the bacterial and archaeal T4P in their C-terminal domain structure and in the packing and continuity of α1. This segment forms a continuous α-helix in archaeal T4P but is partially melted in all published bacterial T4P structures due to a conserved helix breaking proline at position 22. The tad (tight adhesion) T4P are found in both bacteria and archaea and are thought to have been acquired by bacteria through horizontal transfer from archaea. Tad pilins are unique among the T4 pilins, being only 40 to 60 residues in length and entirely lacking a C-terminal domain. They also lack the Pro22 found in all high-resolution bacterial T4P structures. We show using cryo-EM that the bacterial tad pilus from Caulobacter crescentus is composed of continuous helical subunits that, like the archaeal pilins, lack the melted portion seen in other bacterial T4P and share the packing arrangement of the archaeal T4P. We further show that a bacterial T4P, the Vibrio cholerae toxin coregulated pilus, which lacks Pro22 but is not in the tad family, has a continuous N-terminal α-helix, yet its α1 s are arranged similar to those in other bacterial T4P. Our results highlight the role of Pro22 in helix melting and support an evolutionary relationship between tad and archaeal T4P.
Organ-specific gene expression datasets that include hundreds to thousands of experiments allow the reconstruction of organ-level gene regulatory networks (GRNs). However, creating such datasets is greatly hampered by the requirements of extensive and tedious manual curation. Here, we trained a supervised classification model that can accurately classify the organ-of-origin for a plant transcriptome. This K-Nearest Neighbor-based multiclass classifier was used to create organ-specific gene expression datasets for the leaf, root, shoot, flower, and seed in Arabidopsis thaliana . A GRN inference approach was used to determine the: i. influential transcription factors (TFs) in each organ and, ii. most influential TFs for specific biological processes in that organ. These genome-wide, organ-delimited GRNs (OD-GRNs), recalled many known regulators of organ development and processes operating in those organs. Importantly, many previously unknown TF regulators were uncovered as potential regulators of these processes. As a proof-of-concept, we focused on experimentally validating the predicted TF regulators of lipid biosynthesis in seeds, an important food and biofuel trait. Of the top 20 predicted TFs, eight are known regulators of seed oil content, e.g., WRI1, LEC1, FUS3. Importantly, we validated our prediction of MybS2, TGA4, SPL12, AGL18, and DiV2 as regulators of seed lipid biosynthesis. We elucidated the molecular mechanism of MybS2 and show that it induces purple acid phosphatase family genes and lipid synthesis genes to enhance seed lipid content. This general approach has the potential to be extended to any species with sufficiently large gene expression datasets to find unique regulators of any trait-of-interest.
Venus and Earth are rocky planets of roughly the same size and bulk density, yet their surface volcanic and tectonic features appear substantially different. On Venus, the coexistence of large volcanic highlands—interpreted as the surface expression of long-lived mantle plumes—alongside coronae, smaller features thought to be caused by transient thermal diapirs, remains enigmatic. Using two-dimensional numerical models of mantle convection with sharp and broad mineral phase transitions for pyrolite, we show that both scales of upwellings can be generated in a stagnant lid planet with an interior temperature 250 to 400 K warmer than Earth’s. The smaller plumes originate from a ~600 km deep internal layer that exists as a consequence of the different sequence of mineral phase transitions that occur in warmer mantles less processed and differentiated by partial melting and volcanism. Future models that include melting will provide further tests of our hypothesis.
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Many winter annual crops, such as pennycress ( Thlaspi arvense L.), are subjected to heavy precipitation events during their growing season. Therefore, it is essential to identify pennycress accessions with natural variation in flooding resilience. We used climate modeling data to assess spring soil moisture levels in the geographic origins of 471 natural pennycress accessions. We selected 34 accessions with variation in predicted soil moisture and tested survivability under prolonged waterlogging at the rosette stage. It took seven weeks for the first accessions to die, indicating that pennycress is hardy to prolonged waterlogging at the vegetative stage. Furthermore, we chose ‘susceptible’ and ‘tolerant’ accessions to waterlog for one week at the reproductive stage, the growth stage aligned with spring rainfall. Six accessions had significantly reduced seed weight at maturity and two had minimal impacts on growth and seed yield after waterlogging and can be further explored for adaptive traits.
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