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At least 397 records · Page 22

Influence of growth temperature of KTiOAsO{sub 4} single crystals on their physicochemical parameters and formation of domain structures

A potassium titanyl arsenate (KTiOAsO{sub 4}, KTA) crystal 50 × 80 × 60 mm in size has been grown by upgraded Czochralski method from flux (TGGS) with a decrease in temperature from 900 to 770 °C during pulling. It is shown that the spectroscopic properties of the parts of KTA crystals grown at 900 and 770 °C are close, whereas the electrical conductivity of the low-temperature (770 °C) KTA part turned out to be an order of magnitude lower than that of the high-temperature part. Visualisation of the domain structure by second-harmonic generation microscopy revealed a more efficient domain intergrowth (throughout the sample) in the low-temperature KTA, which is important for forming a regular domain structure (RDS) in a KTA-based nonlinear optical element. It is established that the quantum efficiency of parametric generation of light in the RDS formed in low-temperature KTA is several times higher than in the case of high-temperature KTA. The results obtained are important for optimising RDS parameters. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Organic nanoparticles with tunable size and rigidity by hyperbranching and cross-linking using microemulsion ATRP

Unlike inorganic nanoparticles, organic nanoparticles (oNPs) offer the advantage of “interior tailorability,” thereby enabling the controlled variation of physicochemical characteristics and functionalities, for example, by incorporation of diverse functional small molecules. In this study, a unique inimer-based microemulsion approach is presented to realize oNPs with enhanced control of chemical and mechanical properties by deliberate variation of the degree of hyperbranching or cross-linking. The use of anionic cosurfactants led to oNPs with superior uniformity. Benefitting from the high initiator concentration from inimer and preserved chain-end functionality during atom transfer radical polymerization (ATRP), the capability of oNPs as a multifunctional macroinitiator for the subsequent surface-initiated ATRP was demonstrated. This facilitated the synthesis of densely tethered poly(methyl methacrylate) brush oNPs. Detailed analysis revealed that exceptionally high grafting densities (~1 nm −2 ) were attributable to multilayer surface grafting from oNPs due to the hyperbranched macromolecular architecture. The ability to control functional attributes along with elastic properties renders this “bottom-up” synthetic strategy of macroinitiator-type oNPs a unique platform for realizing functional materials with a broad spectrum of applications.

ATRP↗

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗

In situ analysis of the nucleation of O- and Zn-polar ZnO nanowires using synchrotron-based X-ray diffraction

The selection of the polarity of ZnO nanowires grown by chemical bath deposition offers a great advantage for their integration into a wide variety of engineering devices. However, the nucleation process of ZnO nanowires and its dependence on their polarity is still unknown despite its importance for optimizing their morphology and properties and thus to enhance the related device performances. To tackle this major issue, we combine an in situ analysis of the nucleation process of O- and Zn-polar ZnO nanowires on O- and Zn-polar ZnO single crystals, respectively, using synchrotron radiation-based grazing incidence X-ray diffraction with ex situ transmission and scanning electron microscopy. We show that the formation of ZnO nanowires obeys three successive phases from the induction, through nucleation to growth phases. Additionally, the characteristics of each phase, including the nucleation temperature, the shape and dimension of nuclei, as well as their radial and axial development are found to depend on the polarity of ZnO nanowires. A comprehensive description reporting the dominant physicochemical processes in each phase and their dependence on the polarity of ZnO nanowires is presented, revisiting their formation process step-by-step. These findings provide a deeper understanding of the phenomena at work during the growth of ZnO nanowires by chemical bath deposition and open the perspective to develop a more accurate control of their properties at each step of the formation process.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Fundamental Studies of the Vibrational, Electronic, and Photophysical Properties of Tetrapyrrolic Architectures

The ability to capture and utilize light in the near-ultraviolet (NUV), visible and near-infrared (NIR-I and NIR-II) spectral regions (i.e., 320–400, 400–700, 700–1000, 1000–1700 nm) is essential for any solar-energy conversion scheme. Nature employs chlorophylls and bacteriochlorophylls in light-harvesting architectures to absorb light in the blue and red/NIR regions. Accessory pigments (carotenoids, bilins) augment absorption of the (bacterio)chlorophylls in the green region. The harvested energy is funneled to a reaction center protein, where charge separation occurs. Subsequent migration of the electron and the hole stabilizes and stores the energy from light via redox chemistry. The long-term objective of the Bocian/Holten&Kirmaier/Lindsey research program under this DOE grant has been to develop tetrapyrrole-based molecular architectures that absorb sunlight, funnel energy and separate charge with high efficiency. Integral to the program has been iterative cycles of design, synthesis and characterization that provided deep insights into the relationships between chemical composition, electronic structure, and key static and dynamic properties (vibrational, redox, photophysical, energy/charge transfer) of tetrapyrrolic systems. Such architectures included monomers, dyads, larger arrays, and complexes with accessory components. The objective was to develop molecular designs and guiding principles to enhance current and future energy-conversion schemes. Molecular arrays targeted to address one or more fundamental questions concerning light harvesting and energy/charge transfer were constructed from analogues of the naturally occurring hemes, chlorophylls and bacteriochlorophylls. Diverse, tunable synthetic building blocks were prepared that spanned the three respective tetrapyrrole families, which are the porphyrins, chlorins and bacteriochlorins. Thus, the research focused on porphyrins as well as synthetic surrogates for chlorophylls (chlorins, 13 1 -oxophorbines and chlorin-imides) and bacteriochlorophylls (bacteriochlorins, bacterio-13 1 -oxophorbines and bacteriochlorin-imides), generically termed hydroporphyrins. Although the three tetrapyrrole classes (porphyrins, chlorins and bacteriochlorins) absorb light strongly in the violet-blue spectral region, the long-wavelength absorption band typically lies in the green-orange, red, and NIR regions, respectively, with increasing intensity. Understanding the spectra, electronic structure, and energy/charge-transfer properties of such tetrapyrrolic macrocycles is of central importance for the rational design of molecular architectures for solar-energy conversion. Our integrated program of molecular design and synthesis coupled with a variety of spectroscopic, electrochemical, and computational studies have probed from first principles how structural and electronic properties of tetrapyrrolic macrocycles dictate spectral properties as well as the rates of ground-state hole/electron transfer and excited-state energy flow in multicomponent architectures. Individual molecules and multicomponent architectures were designed to test ideas of fundamental importance, often requiring the development of new synthetic methodology. The members of the collaborative team had almost daily discussions by phone and/or e-mail concerning design of molecules, flow of compounds between the labs, planning of physical characterization studies, discussing results and analysis and integrating into design of next generation architectures, and the preparation of manuscripts. Furthermore, students and postdocs in the different labs routinely communicated with one another to facilitate the advancement of the research activities. In short, a highly integrated and collaborative research program was well established among the groups. The research effort involved molecular design and synthesis of synthetic molecular architectures by the Lindsey group integrated with physicochemical and photophysical characterization by the Bocian group and the Holten&Kirmaier group (Figure 2). The Bocian group carried out electrochemical, electron paramagnetic resonance (EPR), resonance Raman (RR), and Fourier-transform infrared (FT-IR) studies, as well as density functional theory (DFT) calculations and the time-dependent extension (TDDFT) to gain insight into excited-state properties. The Holten&Kirmaier group carried out static and time-resolved absorption and fluorescence spectroscopy studies and simulated absorption spectra using molecular orbital (MO) energies from DFT as input to the four-orbital model to complement the TDDFT calculations. The combined measurements provided understanding of the vibrational/electronic properties of the individual molecules and the changes that occur upon incorporation into multicomponent architectures. This information underpinned elucidating the mechanisms and timescales of ground-state hole/electron transfer and excited-state energy and charge transfer.

14 SOLAR ENERGY↗

Out-of-equilibrium processes in crystallization of organic-inorganic perovskites during spin coating

Complex phenomena are prevalent during the formation of materials, which affect their processing-structure-function relationships. Thin films of methylammonium lead iodide (CH 3 NH 3 PbI 3 , MAPI) are processed by spin coating, antisolvent drop, and annealing of colloidal precursors. The structure and properties of transient and stable phases formed during the process are reported, and the mechanistic insights of the underlying transitions are revealed by combining in situ data from grazing-incidence wide-angle X-ray scattering and photoluminescence spectroscopy. Here, we report the detailed insights on the embryonic stages of organic-inorganic perovskite formation. The physicochemical evolution during the conversion proceeds in four steps: i) An instant nucleation of polydisperse MAPI nanocrystals on antisolvent drop, ii) the instantaneous partial conversion of metastable nanocrystals into orthorhombic solvent-complex by cluster coalescence, iii) the thermal decomposition (dissolution) of the stable solvent-complex into plumboiodide fragments upon evaporation of solvent from the complex and iv) the formation (recrystallization) of cubic MAPI crystals in thin film.

36 MATERIALS SCIENCE↗

Future changes in isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) under the Shared Socioeconomic Pathways: the importance of physicochemical dependency

Abstract. Secondary organic aerosol (SOA) is a dominant contributor of fine particulate matter in the atmosphere, but the complexity of SOA formation chemistry hinders the accurate representation of SOA in models. Volatility-based SOA parameterizations have been adopted in many recent chemistry modeling studies and have shown a reasonable performance compared to observations. However, assumptions made in these empirical parameterizations can lead to substantial errors when applied to future climatic conditions as they do not include the mechanistic understanding of processes but are rather fitted to laboratory studies of SOA formation. This is particularly the case for SOA derived from isoprene epoxydiols (IEPOX SOA), for which we have a higher level of understanding of the fundamental processes than is currently parameterized in most models. We predict future SOA concentrations using an explicit mechanism and compare the predictions with the empirical parameterization based on the volatility basis set (VBS) approach. We then use the Community Earth System Model 2 (CESM2.1.0) with detailed isoprene chemistry and reactive uptake processes for the middle and end of the 21st century under four Shared Socioeconomic Pathways (SSPs): SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5. With the explicit chemical mechanism, we find that IEPOX SOA is predicted to increase on average under all future SSP scenarios but with some variability in the results depending on regions and the scenario chosen. Isoprene emissions are the main driver of IEPOX SOA changes in the future climate, but the IEPOX SOA yield from isoprene emissions also changes by up to 50 % depending on the SSP scenario, in particular due to different sulfur emissions. We conduct sensitivity simulations with and without CO2 inhibition of isoprene emissions that is highly uncertain, which results in factor of 2 differences in the predicted IEPOX SOA global burden, especially for the high-CO2 scenarios (SSP3–7.0 and SSP5–8.5). Aerosol pH also plays a critical role in the IEPOX SOA formation rate, requiring accurate calculation of aerosol pH in chemistry models. On the other hand, isoprene SOA calculated with the VBS scheme predicts a nearly constant SOA yield from isoprene emissions across all SSP scenarios; as a result, it mostly follows isoprene emissions regardless of region and scenario. This is because the VBS scheme does not consider heterogeneous chemistry; in other words, there is no dependency on aerosol properties. The discrepancy between the explicit mechanism and VBS parameterization in this study is likely to occur for other SOA components as well, which may also have dependencies that cannot be captured by VBS parameterizations. This study highlights the need for more explicit chemistry or for parameterizations that capture the dependence on key physicochemical drivers when predicting SOA concentrations for climate studies.

54 ENVIRONMENTAL SCIENCES↗

Impact of low-chemical storage pretreatment of loblolly pine bark on biochar from microwave pyrolysis

Forest product residues such as bark represent a low-cost, abundant feedstock for bioenergy, but their high ash and alkali and alkaline earth metal (AAEM) content limit thermochemical conversion efficiency. This study evaluates the use of low-severity chemical pretreatments during anaerobic storage to improve the performance of microwave pyrolysis for loblolly pine bark. Bark was treated with dilute sulfuric acid (0.1% and 1%, w/w) or sodium hydroxide (4%, w/w) and incubated anaerobically for one or two weeks to simulate in-pile biorefinery storage. The most effective treatment—1% H2SO4 for two weeks—reduced AAEM content by 35.7% and increased bio-oil yield by 11% compared to untreated controls, while also reducing pyrolysis gas production. In contrast, alkali treatment did not reduce AAEM levels and led to decreased bio-oil yields with increased gas formation. Although biochar yields were relatively stable across treatments, their physicochemical characteristics varied significantly. Acid-treated bark yielded biochars with higher carbon content, lower O/C and H/C ratios, greater surface area, and enhanced heating values. These improvements suggest that chemical pretreatment during storage can tailor biochar quality for specific end uses. Biochars produced under optimized conditions exhibited properties suitable for soil amendment, carbon sequestration, and solid fuel applications. This integrated approach—combining storage, mild chemical conditioning, and microwave pyrolysis—provides a viable pathway to enhance the value and sustainability of bark-derived bioenergy products.

09 - BIOMASS FUELS↗

Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here based on a silica cell bio-replication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: size, biconcave shape, deformability, oxygen carrying capacity, long circulation time. Four successive nano-scale processing steps: RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicles fusion are employed for RRBC construction. A panel of physicochemical analyses including zeta potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirrned the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex-ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures in which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

59 BASIC BIOLOGICAL SCIENCES↗

Bridging molecular-scale interfacial science with continuum-scale models

Solid–water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid–water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗

Highly Coupled Heterobicycle‐Fused Porphyrin Dimers: Excitonic Coupling and Charge Separation with Coordinated Fullerene, C 60

Abstract Porphyrin dimers have been widely explored and studied owing to their importance in photosynthetic systems. A vast variety of dimers linked by different groups and at different angles have been synthesized and studied; however, the means by which to synthesize rigidly fused porphyrins with direct conjugation of the chromophores remains limited. Such a class of porphyrins may possess interesting properties that unconjugated or stacked dimers may not exhibit. In this study, bisbenzimidazole‐fused porphyrin dimers and their mono‐ and bis−zinc derivatives are synthesized and characterized. As a consequence of excitonic coupling, these dimers exhibit a split Soret band irrespective of the metal ion in the porphyrin cavity. Steady‐state fluorescence and excitation spectra followed by femtosecond transient absorption spectral studies of the heterometallated dimer, (free‐base and zinc porphyrin) reveals the occurrence of efficient singlet‐singlet energy transfer (>95 % efficiency and rate constant >10 12 s −1 ) within the dyad. Further, donor‐acceptor conjugates were formed by metal‐ligand axial coordination of phenyl imidazole functionalized C 60 and were characterized by a variety of physicochemical techniques. Excited state charge separation from both singlet and triplet excited states of ZnP in the conjugates has been established. The lifetime of the final charge‐separated state was in the 30–40 μs range revealing charge stabilization. Interestingly, no charge separation in the conjugate derived from the heterometallated dimer was observed wherein excitation transfer dominated the process. The present study brings out the importance of the rigid π‐spacer connecting porphyrin dimers in governing the energy and electron transfer events when coupled with an electron acceptor.

Chemistry↗

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe↗

Structure refinement and anisotropic atomic displacement parameters of 1M Illite: Rietveld and pair distribution function analysis using synchrotron X-ray radiation

Illite, a widespread clay mineral, plays a pivotal role in geological processes, notably as an indicator in diagenetic and hydrothermal alteration environments, and possesses significant industrial relevance in applications including ceramics, construction and catalysis. However, challenges including its nanoscale crystallinity, structural disorder and frequent interstratification with other clay minerals have hindered detailed structural characterization using conventional X-ray diffraction (XRD) techniques. This study employs integrated synchrotron XRD and pair distribution function (PDF) analysis to elucidate the crystal structure of the 1M illite polytype, yielding the first determination of its anisotropic atomic displacement parameters (U aniso ). TheseU aniso parameters provide critical insights into atomic dynamics and static disorder within the structure, enabling a more refined understanding of structure–property relationships. This integrated approach, combining synchrotron XRD, Rietveld refinement and PDF analysis, yields a comprehensive structural characterization, capturing both average crystallographic and local atomic arrangements. Considering illite's widespread geological occurrence and industrial importance, this high-precision structural dataset, especially the determinedU aniso values, provides a crucial benchmark for future modeling and simulation efforts targeting accurate prediction of its physicochemical behavior.

Chemistry↗

Microbiological, Physicochemical, and Immunological Analysis of a Commercial Cashew Nut-Based Yogurt

Nut-based milks and yogurts are gaining popularity, but may not offer the same benefits as dairy yogurts to consumers. Cashew nuts often cause severe allergic reactions, and cashew nut allergens are stable to several types of processing. To compare its characteristics to dairy yogurt and characterize the effects of fermentation on the Ana o 1–3 cashew nut allergens, a commercial yogurt made from cashew nuts (Cashewgurt) was evaluated for microbiological, physiochemical, and immunological properties. Average counts for lactobacilli and Streptococcus thermophilus were greater than 10 million colony forming units per milliliter, indicating the capacity to provide a health benefit. Cashewgurt pH and viscosity values were comparable to cow milk yogurts, and it was off white in color. SDS-PAGE analysis indicated a clear reduction in Ana o 1 and 2, and immuno-assay with polyclonal anti-cashew IgG antibody and cashew-allergic IgE indicated an overall reduction in allergen content. In contrast, SDS-PAGE, mass spectrometry, immunoblot, and ELISA all revealed that Ana o 3 was relatively unaffected by the fermentation process. In conclusion, Ana o 1 and Ana o 2 are sensitive to degradation, while Ana o 3 survives lactic acid bacterial fermentation during yogurt production. The analysis presented here indicates that cashew nut yogurt is not suitable for those with cashew nut allergy.

59 BASIC BIOLOGICAL SCIENCES↗

Electronic impact of Ni2P nanoparticle size on hydrogenation rates

Nickle phosphide, Ni2P, nanoparticles supported on SiO2 show a marked volcano shaped size dependence. Kinetic analysis and physicochemical characterization shows the electron density of Ni to increase with increasing Ni2P size, enhancing in turn the H2 adsorption strength. For particles below 15 nm, H adsorbs weakly causing a low surface coverage of H, gradually increasing with particle size. For large particles, hydrogen binds too strongly causing a high coverage but low catalytic activity. The remarkable size dependence of the electronic properties show that Ni2P particle size can be used to fine-tune its activity for hydrogenation.

Ni2P size effect, Electron density, H2 adsorption ↗

Thermodynamic and Kinetic Transitions of Liquids in Nanoconfinement

Core principles of chemistry are ubiquitously invoked to shed light on the nature of molecular level interactions in nanoconfined fluids, which play a pivotal role in a wide range of processes in geochemistry, biology, and engineering. A detailed understanding of the physicochemical processes involved in the flow, structural transitions, and freezing or melting behavior of fluids confined within nanometer-sized pores of solid materials is thus of enormous importance for both basic research and technological applications. This Account provides a perspective on new insights into the thermodynamic and kinetic transitions of nanoconfined fluids in their stable and metastable forms. After briefly introducing the unique properties of mesoporous silicas from the SBA, MCM, and FDU families that serve as the confinement matrices, combining highly ordered single and bimodal mesopore architectures with tunable pore sizes in the ~2-15 nm range and narrow size distributions, recent studies on melting/freezing behavior of water confined in these host matrices are reviewed. While differential scanning calorimetry (DSC) reveals a linear relationship between melting point depression and pore size (independent of the pore shape), as predicted by the Gibbs-Thomson relation, variable temperature 2 H wide-line nuclear magnetic resonance (NMR) spectroscopy studies confirm the core-shell model of water and give evidence for a layer-by-layer freezing mechanism, which gives rise to an apparent fragile-to-strong transition in the solidification dynamics. In contrast to the freezing/melting behavior of water, the effect of nanoconfinement on the glass transition of supercooled liquids is nonuniversal and the glass transition temperature T g can either increase or decrease with the dimensionality and extent of confinement. This nonuniversal behavior is exemplified by the two glass-forming molecular liquids, glycerol and ortho-terphenyl (OTP). While glycerol shows an increase in T g and a pronounced slowdown of the rotational dynamics of the constituent molecules due to a change in the molecular packing between the bulk and the confined liquid, OTP displays a linear and confining-media-dependent depression of T g with increased confinement that is strongly influenced by the pore-liquid interface characteristics. This Account concludes with a focus on recent experimental evidence of extreme spatial and dynamical heterogeneity in both freezing and glass transition processes. This discovery was enabled by the unique mesoporous structures of SBA-16 and FDU-5, possessing bimodal architectures with two interconnected pore types of different size and shape (spherical and cylindrical). For the very first time, two melting points for water and two glass transitions for supercooled OTP, corresponding to a specific pore type, were observed. Collectively, these observations strongly suggest a close mechanistic connection between the local fluctuations in the structure and dynamics of nanoconfined liquids. Finally, while the findings reviewed in this Account provide new insights into thermodynamic and kinetic transitions of fluids, there remain many unanswered questions regarding the effects of nanoconfinement on the fundamental properties of fluids, which offer exciting future opportunities in chemical research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗