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Modeling swelling of pH-responsive microgels: Theory and simulations
No full textCombining a mean-field swelling model—which incorporates the Poisson-Boltzmann cell model for describing the electrostatics of microgels and a Flory-Rehner-based model for describing the polymer network—with the law of mass action to account for chemical reactions, we present a comprehensive swelling model for weakly charged microgels. This model provides an expression for the microgel osmotic pressure, used to determine the equilibrium swelling and, consequently, the net charge of the microgel as a function of reservoir pH, salt concentration, degree of polymerization, and other suspension and microscopic network properties. The model allows us to relate microscopic microgel features with the equilibrium swelling properties. The weak-field limiting case of the Poisson-Boltzmann theory is analyzed, yielding closed formulas. We validate the model against state-of-the-art coarse-grained simulations of a microgel, utilizing molecular dynamics to explore configurational degrees of freedom and the Monte Carlo grand-reaction method to simulate chemical reactions in equilibrium with a pH and salt reservoir. We test the model predictions for equilibrium ionization, size, and net charge against particle-based simulations and experiment. Our findings show that the model accurately describes microgel swelling and net charge over a wide range of pH levels. Although the accuracy decreases for larger salt concentrations, its overall qualitative accuracy makes it a reliable tool for parameter exploration and data interpretation, aiding in the rational design of microgel suspensions
On the importance of configuration search to the predictivity of lanthanide selectivity
No full textThe lanthanide elements are crucial components in numerous technologies, yet their industrial production through liquid-liquid extraction continues to be economically and environmentally costly due to the challenge of separating elements with similar physico-chemical properties. While computational ligand screening has shown promise towards discovering efficient extractants, the complexity of constructing chemically-sensible 3D structures (often by-hand), coupled with the high cost of quantum chemistry calculations, often limits exploration of the vast ligand chemical and conformational space in favor of local exploration around known chemistries. Moreover, metal complexes can have many stable configurations whose differences in energies exceed the small energy differences that determine extractant selectivity for certain lanthanides. Because of this difference, incorrect selectivity predictions can be made if the lowest energy coordination complex is not identified and modeled. To address this issue, we present a high- throughput computational workflow that automates the construction and quantum mechanical modeling of 3D lanthanide-extractant complexes. This approach allows for an unbiased search of distinct configurational and compositional variations for each metal, enabling accurate predictions of their solution structures and lanthanide selectivity. As showcased by three extractants from diverse chemical categories—a crown ether, a phenanthroline monocarboxamide, and a malonamide—it is found that sampling the lanthanide-ligand configuration space is critical to correctly predicting the solvation structure and experimental lanthanide selectivity trends
Sulfate radical anion-based degradation of metazachlor herbicide in the water and gas: A theoretical study
No full textMetazachlor (MTZ) herbicide oxidation initiated by sulfate radical anion (SO4●-) in water and gas was investigated using the density functional theory (DFT) at the M06-2X/6-311++G(3df,3pd)//M06-2X/6-31+G(d,p) level of theory. Mechanisms and kinetics of MTZ oxidation via three oxidation mechanisms were investigated, including abstraction (Abs), addition (Add), and single electron transfer (SET). Results show that most oxidation reactions are favorable and spontaneous in both phases. The overall rate constants at 298.15K in water is 5.06 × 1010 M-1 s-1 whereas the one in gas is many times higher, 1.51 × 1013 M-1 s-1. Notably, the degradation in water is non-selected with the fastest reaction being SET with 5.76 × 109 M-1 s-1 and 11.39% of the kapp and Г, respectively. On the contrary, the one in gas almost occurs via Abs reaction with the fastest one being Abs-H24 with kapp and Г values being 1.08 × 1013 M-1 s-1 and 71.76%. In addition, the influence of temperature on the degradation kinetics is evaluated. Results show that the degradation in water increases as a function of temperature (283 to 323 K), while the drawback trend is found in the gas phase from 253 to 323 K. Diving into the chemical nature of the hydrogen abstraction processes, it is noteworthy that the most predominant Abs reactions at the methyl and methylene groups occur via the proton-coupled electron transfer (PCET) mechanism. Overall, the SO4●--based degradation is an effective and potential method for removing MTZ herbicide
Combined physics- and machine-learning-based method to identify druggable binding sites using SILCS-Hotspots
No full textIdentifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Competitive Saturation (SILCS) method accounts for the flexibility of the target protein using all-atom molecular simulations that include various small molecule solutes in aqueous solution. During the simulations the combination of protein flexibility and comprehensive sampling of the water and solute spatial distributions can identify buried binding pockets absent in experimentally-determined structures. Previously, we reported a method for leveraging the information in the SILCS sampling to identify binding sites (termed Hotspots) of small mono- or bi-cyclic compounds, a subset of which coincide with known binding sites of drug-like molecules. Here we build in that physics-based approach and present a ML model for ranking the Hotspots according to the likelihood they can accommodate drug-like molecules (e.g. molecular weight > 200 daltons). In the independent validation set, which includes various enzymes and receptors, our model recalls 67% and 89% of experimentally-validated ligand binding sites in the top 10 and 20 ranked Hotspots, respectively. Furthermore, we show that the model’s output Decision Function is a useful metric to predict binding sites and their potential druggability in new targets. Given the utility the SILCS method for ligand discovery and optimization the tools presented represent an important advancement in the identification of orthosteric and allosteric binding sites and the discovery of drug-like molecules targeting those sites
Navigation through High-dimensional Chemical Space: Discovery of Ba5Y13[SiO4]8O8.5 and Ba3Y2[Si2O7]2
No full textTwo compounds were discovered in the well-studied BaO-Y2O3-SiO2 phase field. Two different experimental routines were used for the exploration of this system due to the differences of synthetic conditions and competition with a glass field. The first phase Ba5Y13[SiO4]8O8.5 was isolated through a combination of energy dispersive X-ray spectroscopy analysis and diffraction techniques which guided the exploration. The second phase Ba3Y2[Si2O7]2 was located using iterative algorithmic identification of target compositions. The structure solution of the new compounds was aided by continuous rotation electron diffraction, and the structures were refined against combined synchrotron and neutron time-of-flight powder diffraction. Ba5Y13[SiO4]8O8.5 crystallizes in I4 ̅2m, a = 18.92732(1), c = 5.357307(6) Å and represents its own structure type which combines elements of structures of known silicates embedded in columns of interconnected yttrium-centred polyhedra characteristic of high-pressure phases. Ba3Y2[Si2O7]2 has P21 symmetry with a pseudo-tetragonal cell (a = 16.47640(4), b = 9.04150(5), c = 9.04114(7) Å, β = 90.0122(9)°) and is a direct superstructure of the Ca3BaBi[P2O7]2 structure. Despite the lower symmetry, the structure of Ba3Y2[Si2O7]2 retains disorder in both Ba/Y sites and disilicate network, thus presenting a superposition of possible locally-ordered fragments. Ba5Y13[SiO4]8O8.5 has low thermal conductivity and was assessed to be a good potential phosphor host. The two discovered phases provide a rich structural platform for further functional material design. The interplay of automated unknown phase composition identification with multiple diffraction methods offers acceleration of the time-consuming exploration of high-dimensional chemical spaces for new structures
Papertronics: Integrating Electronics and Microfluidics on Paper for Sustainable Electroanalysis
No full textThe widespread use of non-renewable materials in point-of-care (PoC) electroanalysis, such as disposable test strips with electronic meters, has inadvertently contributed to electronic waste. Paper, traditionally used as a passive substrate, offers a renewable alternative but faces limitations in direct conversion into conductive electronic components, hindering its adoption for on-site analysis. Here, we present the development of papertronics, integrating conductive electronic components and microfluidics on a single sheet of paper for sustainable electroanalysis. Using a flame retardant and laser treatment, we enable a direct conversion of cellulose paper into laser-induced graphite (PLIG). By optimizing laser parameters (e.g., laser power, scan speed and defocus/focus), the physicochemical properties of the PLIG are tailored. Microfluidic channels are patterned with sub-millimetre resolution via hot-pressing hydrophobic parafilm into paper at a relatively low temperature of 60 °C for 15 seconds. This process facilitates a seamless integration of paper-based electronic components with microfluidics. Demonstrative applications in pH sensing showed a sensitivity of -40.3 mV pH-1, and lactate biosensing achieved a sensitivity of 0.92 μA mM-1. This study establishes a foundation for cost-effective, environmentally friendly electroanalytical platforms with broad implications in biomedical diagnostics and environmental monitoring
Enhance Cold Adaptation of Bidomain Amylases via High-throughput Computational Engineering
No full textCold-adapted bidomain enzymes are vital for transforming modern industries by decreasing energy consumption, delivering economic benefits, and fostering sustainability through reduced greenhouse gas emissions. Yet, the design strategies guiding their acquisition of cold adaptation remain unknown. Here, we developed an integrated computational-experimental strategy to engineer bidomain enzymes for enhanced cold-adaptation. Using five model amylase variants exhibiting different degrees of cold adaptation, we identified a descriptor from molecular dynamics simulations, namely domain separation index (DSI), which positively correlates with bidomain amylases’ relative activity at 0°C. The bidomain amylase variants with a longer distance between its catalytic domain and carbohydrate-binding module (i.e., a high DSI) were observed to demonstrate cold adaptation. Guided by DSI, we developed a high-throughput molecular modeling protocol to convert the thermophilic Pseudomonas saccharophila amylase (psA) into a cold-adapted bidomain enzyme, virtually screening 120 psA variants with different linkers. Two psA variants with a greater DSI value were selected and experimentally confirmed to be cold-adapted, with the psA121 variant achieving a 12-fold increase in relative activity at 0°C from 2.4% (specific activity: 14 U/mg) to 30.5% (specific activity: 219 U/mg). Conformational analyses reveal that compared to non-cold-adapted counterparts, cold-adapted variants leverage its linker to induce domain separation and enhance flexibility of active-site and binding loop via dynamic allostery, thereby promoting substrate recruiting, binding, and catalysis at lower temperatures. Statistical analyses of 120 variants demonstrate that helical motifs within linkers drive interdomain separation. Overall, our study offers strategies for engineering cold-adapted bidomain enzymes and suggests the molecular basis of cold adaptation in bidomain amylases
Ketonization of Valeric Acid to 5-Nonanone over Metal Oxides catalysts
No full textValeric acid (VA), readily obtainable in the biorefinery from sugary biomass streams, can be upgraded to 5-nonanone, a versatile chemical building block with numerous applications. This study investigates the performance of nine metal oxide catalysts (SnO2, SiO2, Y2O3, CeO2, ZrO2, TiO2, La2O3, Cr2O3, and Al2O3) in the gas-phase ketonization of VA to 5-nonanone in the 350-450°C range. This screening reveals a correlation between the metal oxides lattice energy and their catalytic activity for valeric acid ketonization. ZrO2, TiO2, and La2O3, char-acterized by high lattice energy, demonstrate the highest catalytic activity. Y2O3, SnO2, SiO2, showing low lattice energy, are barely active. However, exceptions to this trend were ob-served: Cr2O3 and Al2O3 displayed poor catalytic performance despite their elevated lattice energy. The comprehensive characterization of the catalysts, encompassing XRD, N2-physisorption, NH3-TPD, and CO2-TPD analyses, has unveiled the crucial role of important parameters including acid-base properties in addition to lattice energy. Only oxides showing amphoteric properties can catalyse the reaction effectively. Interestingly, low-lattice energy and amphoteric oxides such as SnO2 (showing poor performance) became significantly active at higher temperature (500°C). Analysis of by-products by online GC-MS and spent catalyst characterization indicated that in this case the ketonization mechanism changed from the so-called surface mechanism to the so-called bulk mechanism. This study contributes to a refined understanding of catalyst properties governing ketonization efficiency, paving the way for optimizing the conversion of biomass-derived carboxylic acids into valuable biofuel precursors
Modified Pickering Catalysis: Green Transfer Hydrogenation of the Tri-substituted Olefin of Tetrahydocannabinol
No full textGreen transfer hydrogenation of the trisubstituted olefin within the tetrahydrocannabinol scaffold, has been performed using minimal amount of organic solvent in water, on the basis of a modified Pickering catalysis, with greater selectivity over standard industrial conditions with decreased reaction times under ambient conditions. Examples of various solvents, surfactants, and observation of europium in the selectivity of the hydrogenated products are given
Charge regulation of nanoparticles in the presence of multivalent electrolytes
No full textWe explore charge regulation (CR) of spherical nanoparticles immersed in an asymmetric electrolyte of a specified pH. Using a recently developed reactive canonical Monte Carlo (MC) simulation method, titration isotherms are obtained for suspensions containing monovalent, divalent, and trivalent coions. A theory based on the modified Poisson-Boltzmann (PB) approximation, which incorporates the electrostatic ion solvation free energy and discrete surface charge effects, is used to compare with the simulation results. A remarkably good agreement is found without any fitting parameters, both for the ion distributions and titration curves, suggesting that ionic correlations between coions and hydronium ions at the nanoparticle surface play only a minor role in determining the association equilibrium between hydroniums and the functional sites on the nanoparticle surface. On the other hand, if suspension contains multivalent counterions, we observe large deviation between theory and simulations, showing that the electrostatic correlations between counterions and hydronium ions at the nanoparticle surface are very significant and must be properly taken into account to correctly describe CR for such solution