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At least 325 records · Page 18

Phosphine Ligand Binding and Catalytic Activity of Group 10–14 Heterobimetallic Complexes

We report heterobimetallic complexes have attracted much interest due to their broad range of structures and reactivities as well as unique catalytic abilities. Additionally, these complexes can be utilized as single-source precursors for the synthesis of binary intermetallic compounds. An example is the family of bis(pyridine-2-thiolato)dichloro-germanium and tin complexes of group 10 metals (Pd and Pt). The reactivity of these heterobimetallic complexes is highly tunable through substitution of the group 14 element and the neutral ligand bound to the transition metal. Here, we study the binding energies of three different phosphorous-based ligands, PR 3 (R = Bu, Ph, and OPh) by density functional theory and restricted Hartree–Fock methods. The PR 3 ligand-binding energies follow the trend of PBu 3 > PPh 3 > P(OPh) 3 , in agreement with their sigma-bonding ability. These results are confirmed by ligand exchange experiments monitored with 31 P NMR spectroscopy, in which a weaker binding PR 3 ligand is replaced with a stronger one. Furthermore, we demonstrate that the heterobimetallic complexes are active catalysts in the Negishi coupling reaction, where stronger binding PR 3 ligands inhibit access to an active site at the metal center. Similar strategies could be applied to other complexes to better understand their ligand-binding energetics and predict their reactivity as both precursors and catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Machine Learning for Predicting the Viscosities of Deep Eutectic Solvents

Deep eutectic solvents (DESs) are emerging as environmentally friendly designer solvents for mass transport and heat transfer processes in industrial applications; however, the lack of accurate tools to predict and thus control their viscosities under both a range of environmental factors and formulations hinders their general application. While DESs may serve as designer solvents, with nearly unlimited combinations, this unfortunately makes it experimentally infeasible to comprehensively measure the viscosities of all DESs of potential industrial interest. To assist in the design of DESs, we have developed several new machine learning (ML) models that accurately and rapidly predict the viscosities of a diverse group of DESs at different temperatures and molar ratios using, to date, one of the most comprehensive data sets containing the properties of over 670 DESs over a wide range of temperatures (278.15–385.25 K). Three ML models, including support vector regression (SVR), feed forward neural networks (FFNNs), and categorical boosting (CatBoost), were developed to predict DES viscosity as a function of temperature and molar ratio and contrasted with multilinear and two-factor polynomial regression baselines. Further, quantum chemistry-based, COSMO-RS-derived sigma profile (σ-profile) features were used as inputs for the ML models. The CatBoost model is excellent at externally predicting DES viscosity, as indicated by high R 2 (0.99) and low root-mean-square-error (RMSE) and average absolute relative deviations (AARD) (5.22%) values for the testing data sets, and 98% of the data points lie within the 15% of AARD deviations. Furthermore, SHapley additive explanation (SHAP) analysis was employed to interpret the ML results and rationalize the viscosity predictions. The result is an ML approach that accurately predicts viscosity and will aid in accelerating the design of appropriate DESs for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combined Effects of Hemicolligation and Ion Pairing on Reduction Potentials of Biphenyl Radical Cations

Here, formal reduction potentials of highly oxidizing and short-lived radical cations of substituted biphenyls generated by pulse radiolysis in 1,2-dichloroethane (DCE) were measured using a redox equilibrium ladder method. The effect of halide ion–radical interactions on reduction potentials of biphenyls was examined by utilizing the ability of DCE to release Cl – in the vicinity of the radical cation. The Hammett correlation of measured potentials across a range of over 700 mV shows saturation at high Hammett sigma values. This effect has been explained by both ion-pairing and hemicolligation interactions between biphenyl radical cations and Cl – and appears to modulate reduction potentials by as much as 400 mV. This finding offers a convenient way to manipulate the energetics of electron transfer involving organic redox species.

14 SOLAR ENERGY↗

Effective Local Geometry Descriptor for 29Si NMR Q4 Anisotropy

The nuclear shielding anisotropy, ζ, is a useful nuclear magnetic resonance (NMR) shielding tensor parameter in describing the extent of electron cloud distortion about an atom. Despite the advantages afforded by NMR in structural characterization, the relationship between ζ and local structure of an atom in high-symmetry environments, such as Si-Q 4 sites, is poorly understood. Here, we use a data-driven approach combining random forest feature ranking and the Sure Independence Screening and Sparsifying Operator (SISSO) approach to derive a simple and accurate geometric descriptor for ζ with a root-mean-squared prediction error of 6.77 ppm and an R 2 of 0.761. We then apply this descriptor to describe the local geometric distortion of zeolites Sigma-2 and silica-ZSM-5 whose chemical shift anisotropy tensor has been reported. We envision that this geometric descriptor will allow for structural description and refinement in previously difficult-to-describe materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modifying Frank–Kasper Mesophases by Modulating Chain Configuration in PDMS- b -PTFEA Copolymers

The common spherical mesophases observed from chemically distinct compounds have promoted extensive studies of packing structures in soft-matter self-assemblies. In this report we present a new approach for controlling sphere-packing phases by modulating homologous copolymer chain configurations. To this end, three sets of sample pairs, compositionally asymmetric polydimethylsiloxane-b-poly(2,2,2-trifluoroethyl acrylate) (PDMS-b-PTFEA) diblock copolymers (diBCPs) and their homologues containing the corresponding triblock copolymer (triBCP), are synthesized via atom transfer radical polymerization and designed with the consistent volume fractions of the core-forming PTFEA block, f PTFEA = 0.20, 0.18, and 0.15. We identify the formation of C15 and hexagonally close-packed (HCP) phases in the triBCP-containing PDMS-b-PTFEAs, whereas the sigma and C14 phases are formed in their diBCP analogues, respectively. These phase shifts into C15 and HCP, due to molecular configuration differences, reveal a significant yet unrealized role of chain configurations and the associated chain size effects in determining the stable sphere-packing phases in BCP systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutron Diffraction Study of Significant sp 3 and sp 2 C–H Bond Shortening in a Fluorinated Pyridinium Saccharinate

Here we have experimentally shown by neutron diffraction significant shortening of both $sp^3$- and $sp^2$-hybridized C–H bonds to 1.092(2) and 1.081(1) Å in a hydrogen-bonded crystal of a difluorinated compound, 4-((2,2-difluoroethoxy)methyl)pyridinium saccharinate. Both MP2 and DFT calculations affirmed the C–H bond shrinkages. Sanderson’s electronegativity equalization principle provides insight into the shortening of the C–H covalent bond lengths for both $sp^3$- and $sp^2$-hybridized carbon atoms. To the best of our knowledge, this neutron diffraction study has revealed the largest extents of $sp^3$ and $sp^2$ C–H bond shrinkages with a 3-sigma rule being satisfied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Hydrogen Isotope Separations through Strong Hydrogen Adsorption at Open Copper(I) Sites in an Ultramicroporous Metal-Organic Framework

Metal-organic frameworks with coordinatively unsaturated metal sites (open metal sites) capable of engaging in orbital interactions with pi-acidic gases are of interest for enabling ambient-temperature gas separations, such as hydrogen isotope separations. In view of the weakly pi-acidic nature of H2, we sought to strengthen pi-backbonding-mediated H2 adsorption through pore confinement effects. Toward that end, we synthesized and characterized the ultramicroporous metal-organic framework CuxZn5-xCl4-yHz(bbta)3 (CuIZn-MFU-4; H2bbta = 1H,5H-benzo(1,2-d:4,5-d')bistriazole), featuring pi-basic trigonal pyramidal CuI sites that reside within 7 A of one another at their closest. Gas adsorption measurements reveal an H2 adsorption enthalpy of -38 kJ/mol, exceeding that of the larger-pore analog (CuIZn-MFU-4l; -33 kJ/mol) and representing the strongest H2 adsorption yet achieved in a metal-organic framework. The stronger H2 adsorption in CuIZn-MFU-4 is attributed to a combination of pore confinement effects and the increased ..sigma..-accepting nature of the CuI sites caused by a more electron-withdrawing bbta2- linker, as supported by structural, spectroscopic, and computational evidence. With the strongest H2 adsorption, equilibrium isotope effects in CuIZn-MFU-4 lead to a D2/H2 selectivity (as estimated by ideal adsorbed solution theory) of 1.35 even at 298 K, approaching the values reported below 200 K for conventional porous materials.

08 HYDROGEN↗

Interlaboratory Study for Characterizing Monoclonal Antibodies by Top-Down and Middle-Down Mass Spectrometry

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product’s primary structure reliably and reproducibly. The major objective of the present study was to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up approaches, such as confirming protein integrity, sequencing variable domains, ruling out artefacts, and revealing modifications and their locations. A panel of three mAbs was selected and centrally provided to twenty laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). A variety of different MS instrument platforms and ion dissociation techniques were employed. Overall, the present study confirms that MD/TD MS strategies are valuable and readily available tools in laboratories worldwide. They provide complementary information to the bottom-up approach and can add unique information, which may be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. One of the limitations revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS, but the number of TD/MD MS experts is still very low.

59 BASIC BIOLOGICAL SCIENCES↗

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Abstract Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ 70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ 70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

42 ENGINEERING↗

Mechanism of anion exchange and small-molecule inhibition of pendrin

Pendrin (SLC26A4) is an anion exchanger that mediates bicarbonate (HCO 3 - ) exchange for chloride (Cl-) and is crucial for maintaining pH and salt homeostasis in the kidney, lung, and cochlea. Pendrin also exports iodide (I - ) in the thyroid gland. Pendrin mutations in humans lead to Pendred syndrome, causing hearing loss and goiter. Inhibition of pendrin is a validated approach for attenuating airway hyperresponsiveness in asthma and for treating hypertension. However, the mechanism of anion exchange and its inhibition by drugs remains poorly understood. We applied cryo-electron microscopy to determine structures of pendrin from Sus scrofa in the presence of either Cl - , I - , HCO 3 - or in the apo-state. The structures reveal two anion-binding sites in each protomer, and functional analyses show both sites are involved in anion exchange. The structures also show interactions between the Sulfate Transporter and Anti-Sigma factor antagonist (STAS) and transmembrane domains, and mutational studies suggest a regulatory role. We also determine the structure of pendrin in a complex with niflumic acid (NFA), which uncovers a mechanism of inhibition by competing with anion binding and impeding the structural changes necessary for anion exchange. These results reveal directions for understanding the mechanisms of anion selectivity and exchange and their regulations by the STAS domain. This work also establishes a foundation for analyzing the pathophysiology of mutations associated with Pendred syndrome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Double Chooz {theta}13 measurement via total neutron capture detection

Neutrinos were assumed to be massless particles until the discovery of the neutrino oscillation process. This phenomenon indicates that the neutrinos have non-zero masses and the mass eigenstates (nu(1), nu(2), nu(3)) are mixtures of their flavour eigenstates (nu(e), nu(mu), nu(tau)). The oscillations between different flavour eigenstates are described by three mixing angles (theta(12), theta(23), theta(13)), two differences of the squared neutrino masses of the nu(2)/nu(1) and nu(3)/nu(1) pairs and a charge conjugation parity symmetry violating phase delta(CP). The Double Chooz experiment, located near the Chooz Electricite de France reactors, measures the oscillation parameter theta(13) using reactor neutrinos. Here, the Double Chooz collaboration reports the measurement of the mixing angle theta(13) with the new total neutron capture detection technique from the full data set, yielding sin(2)(2 theta(13)) = 0.105 +/- 0.014. This measurement exploits the multidetector configuration, the isoflux baseline and data recorded when the reactors were switched off. In addition to the neutrino mixing angle measurement, Double Chooz provides a precise measurement of the reactor neutrino flux, given by the mean cross-section per fission <sigma(f)& rang; = (5.71 +/- 0.06) x 10(-43) cm(2) per fission, and reports an empirical model of the distortion in the reactor neutrino spectrum. The Double Chooz collaboration reports the neutrino oscillation parameter theta(13) from a measurement of the disappearance of reactor anti-electron neutrinos with the total neutron capture technique.

Djurcic, Z.↗

Bonding and reactivity of isostructural uranyl and neptunyl peroxide phases

Understanding the reactivity of actinide peroxides is critical for predicting the behavior of spent nuclear fuel in radiolytic environments. Herein, we report the synthesis and characterization of a lithium neptunyl(VI) hydroxo peroxo compound (LiNp), which is isostructural to the uranyl analogue (LiU). Single-crystal X-ray diffraction reveals that LiNp contains both [NpO 2 (O 2 ) 3 ] 4- and [NpO 2 (OH) 4 ] 2- units stabilized by Li + and hydrogen bonding and Raman spectroscopy shows systematic redshifts in neptunyl vibrational modes relative to uranyl. DFT calculations highlight the importance of secondary coordination in reproducing vibrational and structural features, but challenges remain with correctly modeling strong sigma donors. Solid-state EPR spectroscopy and DFT confirm superoxide stabilization within LiU and calculations suggest favorability of the analogous radical species in LiNp. Solution state EPR spectroscopy with the radical spin trap 5-tert-butoxycarbonyl-5-methyl-1-pyrroline N-oxide (BMPO) reveal evidence of superoxide in the LiU and LiNp phases and suggests stabilization of superoxide within actinyl triperoxide complexes, forming [AnO 2 (O 2 ) 2 (O) 2 • ] 3- .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Selective bond formation triggered by short optical pulses: quantum dynamics of a four-center ring closure

Here we report bond formation induced by an ultrashort UV pulse. The photochemical process is described by quantum dynamics as coherent electronic and nuclear motions during the ultrashort pulse induced ring closure of norbornadiene to quadricyclane. Norbornadiene consists of two ethylene moieties connected by a rigid (CH 2 ) 3 bridge. Upon photoexcitation, two new sigma bonds are formed, resulting in the closure of a four-atom ring. As a medium-sized polyatomic molecule, norbornadiene exhibits a high density of strongly coupled electronic states from about 6 eV above the ground state. We report on inducing the formation of the new bonds using a short femtosecond UV pulse to pump a non-equilibrium electronic density in the open form that evolves towards the closed ring form. As the coherent electronic-nuclear coupled dynamics unfold, the excited states change character through non-adiabatic interactions and become valence states for the two new C–C bonds of quadricyclane. Our three-dimensional fully quantum dynamical grid simulations during the first 200 fs show that short UV pulses of different polarization initiate markedly different initial non-equilibrium electronic densities that follow different dynamical paths to the S 0 /S 1 conical intersection. They lead to different initial relative yields of quadricyclane, thereby opening the way to controlling bond-making with attopulses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration of neutron radiation-induced nucleation of supercooled water

In this study, we present direct evidence for neutrons causing nucleation of supercooled water. Highly purified water (20 nm filtration) is cooled to well below freezing (as low as −20 °C) with a radioactive calibration source of neutrons/gamma-rays either present or removed during each of many control cooling runs for the same volume of water. When it is primarily neutrons irradiating the sample bulk, the non-equilibrium freezing point (also known as the “supercooling point”) is, on average, +0.7 °C warmer than the control equivalent, with a statistical significance of greater than 5 Sigma, with systematic uncertainty included. This effect is not observed with water in the presence of gamma-rays instead of neutrons. While these neutrons should have theoretically had sufficient energy to mount the energy barrier, corroborating our results, their raising of supercooling temperature has never been reported experimentally to the best of our knowledge. The potential to use deeply supercooled solutions, not only water, as metastable detectors for radiation and perhaps dark matter or neutrino physics presents now a new avenue for exploration.

Szydagis, Matthew↗

Multiscale investigation of the mechanism of biomass deconstruction in the dimethyl isosorbide/water Co-solvent pretreatment system

In the context of promoting a circular bioeconomy, the development of green and efficient lignocellulosic biomass pretreatment technologies so as to realize high value-added biomass utilization is of intense interest. We demonstrated the potential of the bio-based green solvent dimethyl isosorbide (DMI) for the fractionation of Eucalyptus biomass with excellent performance. Here, to investigate the mechanisms involved in biomass fractionation, microimaging and microspectroscopic techniques were employed together with molecular dynamics (MD) simulation and COSMO-RS quantum chemical calculations to derive multiscale information. Both the microstructure and regional chemistry of the cell wall vary significantly with the volume ratio of DMI/H 2 O. The strongest effects were found at DMI/H 2 O = 9:1 and showed visible cell wall tearing cracks and cell wall deformation and collapse as well as the lowest values of cell wall thickness and circularity. From the MD simulations, lignin exhibits collapsed-like structure in pure H 2 O with low solvent accessibility surface area (SASA) and radius of gyration (R g ). In contrast, lignin in DMI/H 2 O shows extended structure with high SASA and solvent interactions dominated by van der Waals forces, with maximal contact in the 9:1 (v/v) system. Further, the COSMO-RS calculated sigma (σ-) potential suggests the intermolecular interactions in DMI and DMI/H 2 O co-solvent are weak, leading to stronger interaction with lignin and correspondingly higher lignin dissolution. The radial distribution functions and σ-potential all show that again DMI/H 2 O at 9:1 is an optimal volume ratio for high lignin dissolution. Finally, this study provides a solvent-ratio dependent mechanism for the action of polar aprotic solvents in the deconstruction of biomass.

09 BIOMASS FUELS↗

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗

Disoriented isospin condensates in heavy-ion collisions

Anomalous neutral to charged kaon correlations measured by the ALICE collaboration have defied usual explanations. We propose that the large fluctuations could arise because of a disoriented isospin condensate where there is an imbalance between up and down condensates at the time kaons hadronize. This could happen in heavy-ion collisions when the quark condensate re-forms as the system cools and the approximate chiral symmetry of QCD is broken. Within the linear sigma model, we show that the energy cost of forming a disoriented isospin condensate is small making it very plausible.

Kapusta, Joseph [University of Minnesota, Minneapo↗

A New Modeling Approach for a Priori Uncertainties of Laser Tracker Angle Measurements

Methods for modeling the uncertainty in laser tracker angle measurements vary within the metrology industry, leading to confusion and questionable stochastic modeling for survey network adjustments and error propagation analysis. Interpreting the published laser tracker manufacturer performance specifications to determine an a priori sigma value for weighting azimuth and zenith angle measurements can be confusing and has led to differing implementations. Furthermore, this paper proposes a unique way to model survey network a priori laser tracker angular uncertainties based on laser tracker manufacturers’ published maximum permissible error (MPE) values referenced to current standards for weighting survey network measurements. This paper’s proposed model takes into account the disparate effects that pointing errors, target centering errors, and leveling errors have on azimuth and zenith angular uncertainties for measurements with steep sightings and at near ranges.

42 ENGINEERING↗