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At least 289 records · Page 16

Deep spectral CNN for laser induced breakdown spectroscopy

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). Once the spectral CNN is trained, it can accomplish either task through a single feed-forward pass, with real-time benefits and without any additional side information requirements including dark current, system response, temperature and detector-to-target range. Our experiments demonstrate that the proposed method outperforms the existing approaches used by the Mars Science Lab for pre-processing and calibration for remote sensing observations from the Mars rover, ‘Curiosity’.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Techno-economic and life cycle assessment of aluminum electrorefining from mixed scraps using ionic liquid

Aluminum production from bauxite ore uses significantly high amount of energy and capital expenditure. Recycle and reuse of aluminum can be economical and minimize the environmental impacts. Smelter based recycle and reuse of aluminum is used in recent days, however, it also uses high amount of energy with high cost of production and yields high life cycle impacts. The University of Alabama has developed aluminum electrorefining technology from mixed scraps using ionic liquids as an alternative to traditional smelter based recycle and reuse. This study has explored the techno-economical, and life cycle viability of that technology. An excel-based techno-economic and life cycle assessment model was developed at Idaho National Laboratory for techno-economic and life cycle assessment. SimaPro was used to get the necessary database for the life cycle assessment. This study determined that a 20,000 kg/day ionic liquid-based electrorefining system can be profitable with a net yearly profit of $2.00 million. Further, in terms of net global warming potential, it emits 0.92 kg CO 2 equivalent per kg of aluminum recycled, whereas the traditional smelter-based recycle technology emits 1.57 kg CO 2 equivalent per kg of aluminum recycled, and the aluminum production from bauxite ore emits 17.8 kg CO 2 equivalent per kg of aluminum produced. In other life cycle assessment categories, electrorefining of aluminum emits >88 % less than aluminum production from bauxite ore and it is also better than traditional aluminum recycling in six out of ten categories studied. This makes ionic liquid-based electrorefining technology a very promising technology in terms of process economics and environmental sustainability.

36 MATERIALS SCIENCE↗

Long-living excited states of a 2D diamagnetic exciton

Hydrogenic excited states of a 2D exciton are degenerate. In the presence of a weak magnetic field, the -states with a zero momentum of the center of mass get coupled to the -states with finite momentum of the center of mass. This field-induced coupling leads to a strong modification of the dispersion branches of the exciton spectrum. Namely, the lower branch acquires a shape of a “mexican hat” with a minimum at a finite momentum. At certain magnetic field, exciton branches exhibit a linear crossing, similarly to the spectrum of a 2D electron in the presence of spin–orbit coupling. While spin is not involved, degenerate and states play the role of the spin projections. Lifting of degeneracy due to diamagnetic shifts and deviation of electron–hole attraction from purely Coulomb suppresses the linear crossing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Establishment and characterization of a novel conditionally immortalized human parietal epithelial cell line

Highlights: • A novel conditionally immortalized human parietal epithelial cell (ciPEC) line was created. • ciPECs were isolated out of fresh human kidney tissue from an infant. • ciPECs show specific PEC characteristics. • ciPECs show no or little podocyte and glomerular endothelial cell marker expression. • ciPECs can be activated by IL-1β treatment. Parietal epithelial cells (PECs) are epithelial cells in the kidney, surrounding Bowman's space. When activated, PECs increase in cell volume, proliferate, migrate to the glomerular tuft and excrete extracellular matrix. Activated PECs are crucially involved in the formation of sclerotic lesions, seen in focal segmental glomerulosclerosis (FSGS). In FSGS, a number of glomeruli show segmental sclerotic lesions. Further disease progression will lead to increasing number of involved glomeruli and gradual destruction of the affected glomeruli. Although the involvement of PECs in FSGS has been acknowledged, little is known about the molecular processes driving PEC activation. To get more insights in this process, accurate in vivo and in vitro models are needed. Here, we describe the development and characterization of a novel conditionally immortalized human PEC (ciPEC) line. We demonstrated that ciPECs are differentiated when grown under growth-restrictive conditions and express important PEC-specific markers, while lacking podocyte and endothelial markers. In addition, ciPECs showed PEC-like morphology and responded to IL-1β treatment. We therefore conclude that we have successfully generated a novel PEC line, which can be used for future studies on the role of PECs in FSGS.

60 APPLIED LIFE SCIENCES↗

Construction of extracellular matrix-based 3D hydrogel and its effects on cardiomyocytes

Highlights: • SOD and Triton X-100 could efficiently decellularize cells to get cardiac ECM. • Main proteins of cECM were fibronectin, collagen, elastin, fibrillin, laminin, etc. • 75% cECM-containing 3D hydrogel promoted cell proliferation and anti-apoptosis. • cECM3DH facilitated the differentiation of ESCs into CMs. • APcECM3DH was more conducive to NCM and ESC-derived CM maturation. Some discoveries resulted from 2-dimensional (2D) cultured cardiac cells have been disqualified in animal testing and later clinical trials. Extracellular matrix (ECM) plays a vital role in cardiac homeostasis, cardiac ECM (cECM)-based 3D cell cultures can mimics the physiological and pathological conditions in vivo closely, it is hopeful of addressing this challenge. Construction of cECM-based 3-dimensional (3D) hydrogel (cECM3DH) and its effects on cell behaviors were studied here. The results indicated that cellular compartments could be efficiently removed from heart tissue via sodium dodecyl sulfonate (SDS)- and Triton X-100-mediated decellularization, remaining the natural fibrous network structure and major proteins. 3D hydrogel consisted of 1 × 10{sup 7} cells/mL cells and 75% cECM could promote the proliferation and anti-apoptosis ability of human embryonic kidney (HEK)-293T cells. 0.25% trypsin or 0.20% collagenase was suitable to retrieve these cells from 3D hydrogel for further researches. Compared with 2D culture system, cECM3DH could significantly increase the proportion of GATA 4{sup +} cardiomyocytes (CMs) derived from heart tissue of neonatal mouse or induced differentiation of embryonic stem cells (ESCs) (P < 0.05) The expression levels of mature genes including cTnT, JCN, CaV1.2, MYL2, CASQ2, NCX1, and Cx43 of these CMs in adult pig cECM-based 3D hydrogel (APcECM3DH) were significantly higher than that in 2D culture system and in newborn piglet cECM-based 3D hydrogel (NPcECM3DH), respectively (P < 0.05). Therefore, cECM3DH supports the generation of primary CMs and ESC-derived CMs, APcECM3DH was more conducive to promoting CM maturation, which contributes to building 3D model for pathogenesis exploration, drug screening, and regenerative medicine of heart diseases.

60 APPLIED LIFE SCIENCES↗

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermally Driven Interfacial Degradation between Li 7 La 3 Zr 2 O 12 Electrolyte and LiNi 0.6 Mn 0.2 Co 0.2 O 2 Cathode

Solid-state batteries offer higher energy density and enhanced safety compared to the present lithium-ion batteries using liquid electrolytes. A challenge to implement them is the high resistances, especially at the solid electrolyte interface with the cathode. Sintering at elevated temperature is needed in order to get good contact between the ceramic solid electrolyte and oxide cathodes and thus to reduce contact resistances. Many solid electrolyte and cathode materials react to form secondary phases. It is necessary to find out which phases arise as a result of interface sintering and evaluate their effect on electrochemical properties. Herein, we assessed the interfacial reactions between LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) and Li 7 La 3 Zr 2 O 12 (LLZO) as a function of temperature in air. We prepared model systems by depositing thin-film NMC622 cathode layers on LLZO pellets. The thin-film cathode approach enabled us to use interface-sensitive techniques such as X-ray absorption spectroscopy in the near-edge as well as the extended regimes and identify the onset of detrimental reactions. We found that the Ni and Co chemical environments change already at moderate temperatures, on-setting from 500 °C and becoming especially prominent at 700 °C. By analyzing spectroscopy results along with X-ray diffraction, we identified Li 2 CO 3 , La 2 Zr 2 O 7 , and La(Ni,Co)O 3 as the secondary phases that formed at 700 °C. The interfacial resistance for Li transfer, measured by electrochemical impedance spectroscopy, increases significantly upon the onset and evolution of the detected interface chemistry. Our findings suggest that limiting the bonding temperature and avoiding CO 2 in the sintering environment can help to remedy the interfacial degradation.

36 MATERIALS SCIENCE↗

Sequential Fe Reduction, Involving Two Different Fe + Intermediates, in the Conversion Reaction of Prussian Blue in Lithium-Ion Batteries

In this work, ex situ X-ray absorption spectroscopy and in operando 57 Fe-Mössbauer spectroscopy measurements are conducted to examine in detail the ongoing reaction mechanism of potassium Prussian blue (K-PB) within the narrow [1.6–0.005 V] voltage range, and so to determine whether this material truly undergoes a conversion reaction, as we proposed elsewhere. The generation of Fe 0 is confirmed by both techniques, finding that 40 to 58% of iron gets reduced to metallic iron at 5 mV. The elucidation of the mechanism by in situ 57 Fe-Mössbauer spectroscopy further reveals a sequential process for the reduction (lithiation) of the two different iron species initially present in Prussian blue. Both high-spin Fe 2+ –N first and low-spin Fe II –C next go through the unusual Fe 1+/I formal oxidation state during the reduction process, before forming surface Fe 0 nanoparticles (NPs) below 0.48 V. Upon charge, Fe 0 NPs preferentially oxidizes into Fe + –N. Interestingly, these surprising Fe + species play an important role in decreasing the overpotential during the charge (delithiation) process with respect to other conversion systems.

25 ENERGY STORAGE↗

Multiscale Modeling of a Direct Nonoxidative Methane Dehydroaromatization Reactor with a Validated Model for Catalyst Deactivation

Due to the recent boom in shale gas production, aromatics production using direct nonoxidative methane dehydroaromatization (DHA) is being investigated extensively. However, due to rapid coke formation, catalysts in the nonoxidative methane DHA reactors get deactivated, which is one of the critical issues for the commercial success of the methane DHA process. In this paper, a model for catalyst deactivation is developed. Rate models for other DHA reactions are developed by considering the decrease in the catalyst activity with time. Due to the very fast coke formation rate on the fresh catalyst, there is coke formation immediately upon the introduction of the feed. Therefore, an algorithm is developed for estimation of the initial state of the reactor and the kinetic parameters by coupling an iterative direct substitution approach with an optimization approach. Transient experimental data from an in-house reactor are first reconciled and then used for developing the kinetic model including the coke formation model. Using the rate model, a dynamic, heterogeneous, multiscale reactor model with embedded heating is developed. Here, the model couples the catalyst pellet level model with a reactor level model. Impacts of temperature, L/D ratio, and scheduling of reactors on variability in conversion and yield with time are studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bench-Scale Apparatus for Rapid, Simultaneous, Comprehensive Vapor–Liquid Equilibrium and Kinetic Property Measurements to Advance CO 2 Capture Solvent Technology

We present here, the design, fabrication, and testing of a new "pressure, volume, temperature (PVT)" apparatus that enables rapid standardized testing for viscosity, vapor–liquid equilibria, and kinetics for water-lean carbon capture solvents. This unit is the first of its kind where equilibrium data are collected during operation as a PTx (pressure–temperature–composition) cell while kinetic data are collected simultaneously with an internal mini wetted-wall contactor (WWC) using controlled adjustments of CO 2 injections to allow for measurements of gas flux (in and out of the liquid). Additionally, in situ measurements of viscosity data are also continuously collected while a solvent is in circulation during gas absorption. This cell empowers comprehensive testing of critical CO 2 capture solvent properties in a single measurement, ensuring all data are collected at the same temperature, pressure, and CO 2 loading. This apparatus also expedites screening of materials since less than 50 mL of sample is needed as compared to 2–3 L needed to get similar data from a conventional WWC. In conclusion, we describe here the methodology of data collected on this new PVT cell, nicknamed “Gary” in honor of Professor Gary Rochelle, for multiple water-lean amine solvents, which we compare to data collected from conventional instrumentation for amine testing.

Zheng, Richard [STARS Technology Corporation, Rich↗

Quantum Orbital Minimization Method for Excited States Calculation on a Quantum Computer

Herein we propose a quantum-classical hybrid variational algorithm, the quantum orbital minimization method (qOMM), for obtaining the ground state and low-lying excited states of a Hermitian operator. Given parametrized ansatz circuits representing eigenstates, qOMM implements quantum circuits to represent the objective function in the orbital minimization method and adopts a classical optimizer to minimize the objective function with respect to the parameters in ansatz circuits. The objective function has an orthogonality constraint implicitly embedded, which allows qOMM to apply a different ansatz circuit to each input reference state. We carry out numerical simulations that seek to find excited states of H 2 , LiH, and a toy model consisting of four hydrogen atoms arranged in a square lattice in the STO-3G basis with UCCSD ansatz circuits. Comparing the numerical results with existing excited states methods, qOMM is less prone to getting stuck in local minima and can achieve convergence with more shallow ansatz circuits.

97 MATHEMATICS AND COMPUTING↗

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C 60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Passivating Nucleobases Bring Charge Transfer Character to Optically Active Transitions in Small Silver Nanoclusters

DNA-wrapped silver nanoclusters (DNA–AgNCs) are known for their efficient luminescence. However, their emission is highly sensitive to the DNA sequence, the cluster size, and its charge state. To get better insights into photophysics of these hybrid systems, simulations based on density functional theory (DFT) are performed. Our calculations elucidate the effect of the structural conformations, charges, solvent polarity, and passivating bases on optical spectra of DNA–AgNCs containing five and six Ag atoms. It is found that inclusion of water in calculations as a polar solvent media results in stabilization of nonplanar conformations of base-passivated clusters, while their planar conformations are more stable in vacuum, similar to the bare Ag5 and Ag6 clusters. Cytosines and guanines interact with the cluster twice stronger than thymines, due to their larger dipole moments. In addition to the base–cluster interactions, hydrogen bonds between bases notably contribute to the structure stabilization. While the relative intensity, line width, and the energy of absorption peaks are slightly changing depending on the cluster charge, conformations, and base types, the overall spectral shape with five well-resolved bands at 2.5–5.5 eV is consistent for all structures. Independent of the passivating bases and the cluster size and charge, the low energy optical transitions at 2.5–3.5 eV exhibit a metal to ligand charge transfer (MLCT) character with the main contribution emerging from Ag-core to the bases. Cytosines facilitate the MLCT character to a larger degree comparing to the other bases. However, the doublet transitions in clusters with the open shell electronic structure (Ag5 and Ag6 + ) result in appearance of additional red-shifted (<2.5 eV) and optically weak band with negligible MLCT character. The passivated clusters with the closed shell electronic structure (Ag5 + and Ag6) exhibit higher optical intensity of their lowest transitions with much higher MLCT contribution, thus having better potential for emission, than their open shell counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic Structure of the Complete Series of Gas-Phase Manganese Acetylacetonates by X-ray Absorption Spectroscopy

Metal centers in transition metal–ligand complexes occur in a variety of oxidation states causing their redox activity and therefore making them relevant for applications in physics and chemistry. The electronic state of these complexes can be studied by X-ray absorption spectroscopy, which is, however, due to the complex spectral signature not always straightforward. Here, we study the electronic structure of gas-phase cationic manganese acetylacetonate complexes Mn(acac) 1–3 + using X-ray absorption spectroscopy at the metal center and ligand constituents. The spectra are well reproduced by multiconfigurational wave function theory, time-dependent density functional theory as well as parameterized crystal field and charge transfer multiplet simulations. This enables us to get detailed insights into the electronic structure of ground-state Mn(acac) 1–3 + and extract empirical parameters such as crystal field strength and exchange coupling from X-ray excitation at both the metal and ligand sites. By comparison to X-ray absorption spectra of neutral, solvated Mn(acac) 2,3 complexes, we also show that the effect of coordination on the L 3 excitation energy, routinely used to identify oxidation states, can contribute about 40–50% to the observed shift, which for the current study is 1.9 eV per oxidation state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chloride Oxidation as an Alternative to the Oxygen-Evolution Reaction on H x WO 3 Photoelectrodes

Oxidizing chloride anion to chlorine or hypochlorous acid in water shows 100% current efficiency on H x WO 3 photoelectrodes. Water oxidation is less than 90% efficient in strong acid and gets worse as the solution becomes less acidic. Accordingly, oxidizing chloride leads to a stable photocurrent, indicating that the catalysis is sustainable for long periods without degrading the H x WO 3 material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption and Catalytic Activity of Gold Nanoparticles in Mesoporous Silica: Effect of Pore Size and Dispersion Salinity

The assembled state of nanoparticles (NPs) within porous matrices plays a governing role in directing their biological, electronic, and catalytic properties. However, the effects of the spatial confinement and environmental factors, such as salinity, on the NP assemblies within the pores are poorly understood. In this study, we use adsorption isotherms, spectrophotometry, and small-angle neutron scattering to develop a better understanding of the effect of spatial confinement on the assembled state and catalytic performance of gold (Au) NPs in propylamine-functionalized SBA-15 and MCM-41 mesoporous silica materials (mSiO 2 ). We carry out a detailed investigation of the effect of pore diameter and ionic strength on the packing and spatial distribution of AuNPs within mSiO 2 to get a comprehensive insight into the structure, functioning, and activity of these NPs. We demonstrate the ability of the adsorbed AuNPs to withstand aggregation under high salinity conditions. We attribute the observed preservation of the adsorbed state of AuNPs to the strong electrostatic attraction between oppositely charged pore walls and AuNPs. The preservation of the structure allows the AuNPs to retain their catalytic activity for a model reaction in high salinity aqueous solution, here, the reduction of p-nitrophenol to p-aminophenol, which otherwise is significantly diminished due to bulk aggregation of the AuNPs. This fundamental study demonstrates the critical role of confinement and dispersion salinity on the adsorption and catalytic performance of NPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗