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Multiscale Modeling of Transport-Mediated Catalytic Reactions in Linear Nanopores: PNB Conversion in MSN
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Atrazine Degradation Using Immobilized Triazine Hydrolase from Arthrobacter aurescens TC1 in Mesoporous Silica Nanomaterials
Triazine hydrolase fromArthrobacter aurescens TC1 (TrzN) was successfully immobilized on mesoporous silica nanomaterials (MSNs) for the first time. For both nonfunctionalized MSNs and MSNs functionalized with Zn(II), three pore sizes were evaluated for their ability to immobilize wild-type TrzN: Mobile composition of matter no. 41 (small, 3 nm pores), mesoporous silica nanoparticle material with 10 nm pore diameter (MSN-10) (medium, 6-12 nm pores), and pore-expanded MSN-10 (large, 15-30 nm pores). Of these six TrzN:MSN biomaterials, it was shown that TrzN:MSN-10 was the most active (3.8 +/- 0.4 x 10 -5 U/mg) toward the hydrolysis of a 50 uM atrazine solution at 25 degrees C. The TrzN:MSN-10 biomaterial was then coated in chitosan (TrzN:MSN-10:Chit) as chitosan has been shown to increase stability in extreme conditions such as low/high pH, heat shock, and the presence of organic solvents. TrzN:MSN-10:Chit was shown to be a superior TrzN biomaterial to TrzN:MSN-10 as it exhibited higher activity under all storage conditions, in the presence of 20% MeOH, at low and high pH values, and at elevated temperatures up to 80 degrees C. Finally, the TrzN:MSN-10:Chit biomaterial was shown to be fully active in river water, which establishes it as a functional biomaterial under actual field conditions. A combination of these data indicate that the TrzN:MSN-10:Chit biomaterial exhibited the best overall catalytic profile making it a promising biocatalyst for the bioremediation of atrazine.
Medium controlled aggregative growth as a key step in mesoporous silica nanoparticle formation
Near monodisperse mesoporous silica nanoparticles (MSN) represent a promising and rapidly developing type of mesoporous silica materials; however, the vast data on their synthesis remains unorganized and ill-understood. We systematically studied the formation of MSN under basic and neutral conditions using various temperatures, CTAB concentrations, hydrolyzing agents (triethanolamine, ammonia, phosphate buffers), and media with different colloidal stabilization properties (with ethanol as a cosolvent and monovalent salts). In the typical conditions for the preparation of stable MSN colloids, the particle size was controlled by colloidal stabilization by the medium (solvent type, ionic strength, and surfactant concentration) in agreement with the “aggregative growth” mechanism, rather than by solely the hydrolysis and condensation rates conventionally used for data interpretation in the classical nucleation theory. Medium properties (pH, ion types and concentration, polarity) also defined the efficiency of silica-surfactant cooperative self-assembly, which directly affected the porosity, mesopore size and pore wall thickness. Interestingly, this traditional silica-surfactant route showed a limited effect on the particle size, emphasizing the dominating role of colloidal stabilization in the studied reaction conditions. In situ pH measurements showed that every reaction medium has unique pH evolution profiles depending on the buffer capacity, hydrolysis and condensation rates. Reaction systems that fail to maintain the working pH can lead to non-porous products or undesired particle morphology and size distribution. The established particle formation mechanism allowed us to formulate comprehensive guidelines for preparing relatively concentrated colloids of near monodisperse (PDI 5–15%) mesoporous 30–700 nm silica spheres with variable porosity and mesopore size. Here, these findings will be particularly useful in designing new mesoporous silica-containing materials for biomedical applications.
Kinetics of the functionalization of mesoporous silica nanoparticles: Implications on surface group distributions, adsorption and catalysis
The post-synthesis functionalization (grafting) kinetics of mesoporous silica nanoparticles (MSN) with organotrimethoxysilanes (R-TMS) is studied via solution 1 H NMR spectroscopy. The process involves a rapid adsorption/ desorption pre-equilibrium followed by reaction of R-TMS with surface silanols. Grafting rates are affected by the functional group in R-TMS. For example, the grafting rate of aminopropyl-trimethoxysilane (AP-TMS) is one order of magnitude higher than other R-TMS. High concentrations of AP-TMS result in substrate-inhibition kinetics, likely due to steric and mobility constraints for reactant alignment at high coverage. The higher rates of AP-TMS grafting indicate a catalytic effect of amine groups. This effect depends on the amine’s basicity and can be used to control the grafting rates and degree of condensation of other R-TMS. Adjusting the rate of mercaptopropyl-trimethoxysilane (MP-TMS) grafting using amines gives MP-MSN materials of varying adsorptive and catalytic activities, illustrated by Pd scavenging experiments and use of Pd@MP-MSN as catalysts for a Suzuki-Miyaura cross-coupling reaction.
Efficacy and Delivery of Novel FAST Agents for Coronaviruses
We proposed to test and develop advanced delivery for novel agents from our collaborators Facile Accelerated Specific Therapeutics (FAST) platform to reduce coronavirus replication. Sachi Bioworks Inc., Prof. Anushree Chatterjee, and Prof. Prashant Nagpal at the University of Colorado Boulder have developed a bioinformatics and synthesis pipeline to produce sequence specific theranostic agents (agents that can be therapies and/or diagnostics) that are inherently transported into the cytoplasm of mammalian host cells and sequence-specifically interfere in nucleic acid replication. The agent comprises a small nanoparticle (2-5 nm) chosen for ideal cellular transport and/or imaging conjugated to a short, synthetic DNA analog oligomer designed for binding to one or more target viral sequences. The sequence specific binding of the FAST agent to its target prevents nucleic acid replication due to its high affinity binding. While the small nanoparticle facilitates delivery in vitro, we plan to package the FAST agents into a larger nanoparticle (80-300 nm) for future in vivo delivery applications. Our team at Sandia has expertise encapsulating biomolecules including protein, DNA, and RNA into solid lipid nanoparticles (LNP) and lipid coated mesoporous silica nanoparticles (LC-MSN) and shown successful delivery in mouse models to multiple tissues. Our team focused on formulation parameters for FAST agents into lipid nanoparticles (LNP) and lipid coated mesoporous silica nanoparticles (LC-MSN) for enhanced delivery and/or efficacy and in vivo translation. We used lipid formulas that have been shown in literature to facility in vitro and more importantly, in vivo delivery. In our work discussed below, we successfully demonstrate loading and release of FAST agents on silica core and stable LC-MSN in a reasonable size range for in vivo testing.
Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles
The aldol reaction of p-nitrobenzaldehyde in amino-catalyzed mesoporous silica nanoparticles (MSN) has revealed varying catalytic activity with the size of the pores of MSN. The pore size dependence related to the reactivity indicates that the diffusion process is important. A detailed molecular-level analysis for understanding diffusion requires assessment of the noncovalent interactions of the molecular species involved in the aldol reaction with each other, with the solvent, and with key functional groups on the pore surface. Such an analysis is presented here based upon the effective fragment potential (EFP). The EFP method can calculate the intermolecular interactions, decomposed into Coulomb, polarization, dispersion, exchange-repulsion, and charge-transfer interactions. In this study, the potential energy surfaces corresponding to each intermolecular interaction are analyzed for homo- and hetero-dimers with various configurations. The monomers that compose dimers are five molecules such as p-nitrobenzaldehyde, acetone, n-hexane, propylamine, and silanol. The results illustrate that the dispersion interaction is crucial in most dimers.
Regulating the Catalytic Activity of Pd Nanoparticles by Confinement in Ordered Mesoporous Supports
Studying structure-sensitive reactions requires the synthesis of catalytic nanoparticles with precisely controlled sizes. Here we demonstrate the facile production of size controlled Pd nanoparticles by confinement in the pores of mesoporous silica nanoparticles (MSN). We show that Pd particles 2.1 nm in size have a higher catalytic activity than larger nanoparticles for the Suzuki-Miyaura cross coupling between 4’-bromoacteophenone and phenyl boronic acid and for the hydrogenation of phenol in aqueous phase. The enhanced activity can be explained in terms of increased number of coordinatively unsaturated sites and higher back donation capacity of the small nanoparticles.
Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs
Summary Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU‐GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi‐process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription.
Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection
Generating top-down tandem mass spectra (MS/MS) for complex mixtures of proteoforms has become possible through improvements in fractionation, on-line separation, dissociation, and mass analysis. The algorithms to match tandem mass spectra to sequences have undergone a parallel evolution, with both spectral alignment and peak matching being paired with diverse methods for scoring proteoform-spectral matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification through three distinct challenges. The first is identifying a large yield of PrSMs while controlling false discovery rate (FDR) in identifying thousands of proteoforms from complex cell lysates via four software workflows: ProSight Proteome Discoverer, TopPIC, Informed Proteomics, and pTop. The second is the deconvolution of data from both Thermo Orbitrap-class and Bruker maXis Q-TOF instruments to produce consistent precursor charge and mass determinations while generating fragment mass lists to optimize identification. The third attempts to detect diverse post-translational modifications (PTMs) in proteoforms from cow milk and human ovarian tissue. The data demonstrate that existing software suites produce admirable sensitivity, in some cases identifying a third of collected tandem mass spectra with FDR controlled below 2%; the overlap in these PrSMs, however, illustrates real value in searching data with multiple search engines. Differences among identification workflows seem to result from each search algorithm incorporating its own deconvolution algorithm. By transmitting deconvolution data from multiple deconvolution routes (Thermo Xtract, Bruker Auto MSn, Mascot Distiller, TopFD, and FLASHDeconv) to the downstream TopPIC search algorithm, we were able to detect common causes of deconvolution disagreement. The detection of PTMs was very inconsistent among search algorithms, with some workflows suggesting as little as 1% of PrSMs from cow’s milk were singly-phosphorylated while other workflows found that 18% of PrSMs were singly-phosphorylated. Taken together, these results make a strong argument for top-down researchers to adopt a standard practice of analyzing each MS/MS experiment with at least two different search engines.
Simultaneous Development of Antiferromagnetism and Local Symmetry Breaking in a Kagome Magnet (Co 0.45 Fe 0.55 )Sn
CoSn and FeSn, two kagome-lattice metals, have recently attracted significant attention as hosts of electronic flat bands and emergent physical properties. However, current understandings of their physical properties are limited to knowledge of the average crystal structure. Here, we report the Fe-doping induced coemergence of the antiferromagentic (AFM) order and local symmetry breaking in (Co 0.45 Fe 0.55 )Sn. Rietveld analysis on the neutron and synchrotron X-ray diffraction data indicates A-type antiferromagnetic order with the moment pointing perpendicular to the kagome layers, associated with the anomaly in the MSn(1) 2 Sn(2) 4 (M = Co/Fe) octahedral distortion and the lattice constant c. Reverse Monte Carlo (RMC) modeling of the synchrotron X-ray total scattering results captured the subtle local orthorhombic distortion involving off-axis displacements of Sn(2). Our results indicate that the stable hexagonal lattice above T N becomes unstable once the A-type AFM order is formed below T N . Here we argue that the local symmetry breaking has a magnetic origin, since the spatially varied M–Sn(2) bond lengths arise from out-of-plane magnetic exchange coupling J c via the exchange pathway M–Sn(2)–M. Our study provides comprehensive information on the crystal structure in both long-range scale and local scale, unveiling unique coupling between AFM order, octahedral distortion, and hidden local symmetry breaking.
Mass Spectrometric Determination of Site-Specific O -Acetylation in Rhamnogalacturonan I Oligomers
O-acetylation, a common modification in rhamnogalacturonan I (RG-I), is critical for various biological processes, including plant growth, stress responses, and pathogen defense. Precise determination of the degree and specific positions of acetylation is therefore essential. To date, nuclear magnetic resonance (NMR) and tandem mass spectrometry have been employed to identify O-acetyl positions in pectin oligosaccharides. Although NMR is effective, it requires pure, high-concentration samples. Tandem mass spectrometry (MS), which uses smaller sample amounts, faces challenges due to O-acetyl migration between monosaccharide positions. The multiple steps in pectin sample analysis can further promote O-acetyl migration, especially near free hydroxyl groups. Moreover, during tandem MS, O-acetyl groups may detach, complicating the accurate tracking. This study presents an approach to lock O-acetyl groups by introducing trideuteroacetyl and propionyl substituents onto free hydroxyls of RG-I or partially acetylated RG-I. By combining matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS and electrospray ionization (ESI) MS with MS/MS or tandem mass spectrometry (MSn), we devised a way to determine the monosaccharide sequence in the oligomer and the precise positions of O-acetyl groups in partially acetylated RG-I. This method enables the study of the regiospecificity of recombinant pectin O-acetyltransferases and can be applied to other oligosaccharides to determine acyl positions.
Ternary aromatic and anti-aromatic clusters derived from the hypho species [Sn 2 Sb 5 ] 3-
Heterometallic clusters have attracted broad interests in the synthetic chemistry due to their various coordination modes and potential applications in heterogeneous catalysis. Here we report the synthesis, experimental, and theoretical characterizations of four ternary clusters ([M 2 (CO) 6 Sn 2 Sb 5 ] 3- (M = Cr, Mo), and [(MSn 2 Sb 5 ) 2 ] 4- , (M = Cu, Ag)) in the process of capturing the hypho - [Sn 2 Sb 5 ] 3- in ethylenediamine (en) solution. We show that the coordination of the binary anion to transition-metal ions or fragments provides additional stabilization due to the formation of locally σ-aromatic units, producing a spherical aromatic shielding region in the cages. While in the case of [Mo 2 (CO) 6 Sn 2 Sb 5 ] 3- stabilization arises from locally σ-aromatic three-centre and five-centre two-electron bonds, aromatic islands in [(AgSn 2 Sb 5 ) 2 ] 4- and [(CuSn 2 Sb 5 ) 2 ] 4- render them globally antiaromatic. This work describes the coordination chemistry of the versatile building block [Sn 2 Sb 5 ] 3- , thus providing conceptual advances in the field of metal-metal bonding in clusters.
Insights into the 3D permeable pore structure within novel monodisperse mesoporous silica nanoparticles by cryogenic electron tomography
Synthetic mesoporous silica nanoparticle (MSN) is an architected geomaterial that provides confinement-mediated flow and transport properties of fluids needed for environmental research such as subsurface energy storage or carbon capture.
Gas-phase negative ion photoelectron spectroscopy and reactivity of phenylacetylide
Arylacetylides such as phenylacetylide (PhCC–, 1) are important nucleophiles used in synthetic chemistry yet rarely have they been studied as bare carbanions. In this work, the phenylacetylide anion was formed via electrospray ionization (ESI) or multistage mass spectrometry (MSn) experiments and subsequently examined in the gas phase by negative ion photoelectron spectroscopy (NIPES), ion-molecule reactions (IMR), alongside theoretical calculations to probe its fundamental structure and reactivity. Photoelectron spectra of PhCC– (1) revealed vertical (VDE) and adiabatic detachment energies (ADE), both of 3.220 eV. The latter value is also the electron affinity (EA) of the phenylethynyl radical (PhCC•) from which a bond dissociation energy (BDE) of phenylacetylene (PhCCH) was derived to be ca. 131.3 ± 1.7 kcal mol-1 using a gas-phase thermochemical cycle. Detachment of an electron from PhCC– at 266 nm likely results in resonant autodetachment, supported by Franck-Condon Factor (FCF) simulations. The phenylacetylide anion reacts with methyl iodide (CH3I) and allyl iodide (C3H5I) via SN2 nucleophilic displacement with measured rate coefficients of 4.29 and 3.66 × 10-10 cm3 molecule-1 s-1, respectively. The mechanisms associated with these displacement reactions are explained and understood in terms of the reaction kinetics, natural bond orbital (NBO) theory, and Density Functional Theory (DFT) calculations.
Comparison of linear regression, k-nearest neighbour and random forest methods in airborne laser-scanning-based prediction of growing stock
Abstract In this study, for five sites around the world, we look at the effects of different model types and variable selection approaches on forest yield modelling performances in an area-based approach (ABA). We compared ordinary least squares regression (OLS), k-nearest neighbours (kNN) and random forest (RF). Our objective was to test if there are systematic differences in accuracy between OLS, kNN and RF in ABA predictions of growing stock volume. The analyses are based on a 5-fold cross-validation at five study sites: an eucalyptus plantation, a temperate forest and three different boreal forests. Two completely independent validation datasets were also available for two of the boreal sites. For the kNN, we evaluated multiple measures of distance including Euclidean, Mahalanobis, most similar neighbour (MSN) and an RF-based distance metric. The variable selection approaches we examined included a heuristic approach (for OLS, kNN and RF), exhaustive search among all combinations (OLS only) and all variables together (RF only). Performances varied by model type and variable selection approaches among sites. OLS and RF had similar accuracies and were more efficient than any of the kNN variants. Variable selection did not affect RF performance. Heuristic and exhaustive variable selection performed similarly for OLS. kNN fared the poorest amongst model types, and kNN with RF distance was prone to overfitting when compared with a validation dataset. Additional caution is therefore required when building kNN models for volume prediction though ABA, being preferable instead to opt for models based on OLS with some variable selection, or RF with all variables together.
Identification of Novel Microcystins Using High-Resolution MS and MS n with Python Code
Cyanotoxins called microcystins (MCs) are highly toxic and can be present in drinking water sources. Determining the structure of MCs is paramount because of its effect on toxicity. Though over 300 MC congeners have been discovered, many remain unidentified. In this work, a method is described for the putative identification of MCs using liquid chromatography (LC) coupled with high-resolution (HR) Orbitrap mass spectrometry (MS) and a new bottom-up sequencing strategy. Maumee River water samples were collected during a harmful algal bloom and analyzed by LC–MS with simultaneous HRMS and MS/MS. Unidentified ions with characteristic MC fragments (135 and 213 m/z) were recognized as possible novel MC congeners. An innovative workflow was developed for the putative identification of these ions. Python code was written to generate the potential structures of unidentified MCs and to assign ions after the fragmentation for structural confirmation. The workflow enabled the putative identification of eight previously reported MCs for which standards are not available and two newly discovered congeners, MC-HarR and MC-E(OMe)R.