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Experimental observation of thermoplasmonic heat transfer at the nanoscale by polymerization. A step towards nanoscale heat sources.
No full textThe thermoplasmonic effect, arising from the relaxation of a metal nanostructure excited at plasmon resonance, has garnered significant interest in recent years. While this effect has been extensively studied across various spatial and temporal scales, there is currently no experimental technique for investigating the spatial distribution of heat exchange at the nanoscale. In this paper, we introduce a chemical approach to map the temperature distribution around nanoparticles. Formulations that crosslink at specific temperatures are placed in contact with gold nanotriangles and irradiated under controlled power and polarization conditions. At moderate power, the polymerized regions, corresponding to the zones of maximum field, exhibit local temperatures exceeding the polymerization temperature. At higher power, anisotropic melting of the gold within the gold nanotriangles was observed. This new methodology reveals that, contrary to common assumptions, significant heat exchange occurs between the nanoparticle and the surrounding medium before temperature homogenization within the nanoparticle. We have thus demonstrated the potential to generate nanoscale heat sources, representing a major advance on a fundamental level and opening up numerous new prospects in nanofabrication
Laboratory Mass Spectrometry of Intact Atmospherically-Relevant Particles
No full textThe physical and chemical properties of atmospheric aerosols profoundly impact the climate and human health. With diameters from sub-nanometer to tens of microns, a multitude of different experimental techniques suited to specific size ranges must be employed to characterize them. While mass spectrometry can be performed on particles of any size by destroying them and characterizing their molecular and atomic compositions, the masses of atmospheric nanoparticles with sizes below 10 nm can be measured with enough precision to observe discrete changes of their chemical composition while they remain intact. This enables direct study of their structure and reactivity in well-controlled laboratory experiments, complementing ambient field measurements. Here, we review the application of mass spectrometry and unique experiments based on mass spectrometers to measure the composition, stability, structure, and formation mechanisms of aerosol particles. We discuss the instrumentation employed in these experiments, including ion mobility separation, ion trap reactivity, and laser spectroscopy, that are often combined with mass spectrometry, and highlight illustrative examples of these techniques to prototypical atmospheric nanoparticles. We also highlight emerging mass spectrometry techniques that could extend these studies to larger nanoparticles and enable new insights into current unsolved problems involving atmospheric nanoparticles
Automated database generation and electron density analysis for NOS bond identification
No full textNitrogen-oxygen-sulfur (NOS) linkages between lysine and cysteine residues represent novel chemical patterns crucial for cellular redox regulation and signalling. Despite their significance, automated identification of these linkages in protein structures remains challenging. Here, we present an algorithm that integrates geometric and electron density screening to detect likely NOS bonds in protein structures. We use a combination of two approaches: a Mid-point approach and a quantum mechanics-informed (QM-point) approach, each applied with varying search radii. We evaluated the algorithm using two datasets: one containing structures which upon manual inspection are confirmed as likely NOS candidates, and a control set where although the N-S distances are within established thresholds, there are is no evidence of NOS formation. The Mid-point method demonstrated strong performance across different search radii, with success rates ranging from 48% to 55% for likely NOS structures. The QM-point approach showed high specificity (99% success rate) for unlikely-NOS structures at a 2.0 Å radius. We propose a two-step screening process that uses the strengths of both methods to optimize NOS bond detection. This approach is an initial step towards automated identification of chemical patterns in protein structures, potentially uncovering previously overlooked linkages and contributing to a deeper understanding of chemical bonds in protein structures
[1,n]-Metal migrations for directional translational motion at the molecular level
No full textThe controlled translational motion displayed by nature’s motor proteins underpins a wealth of processes integral to life, from organelle transport to muscle contraction. The motor proteins move along one dimensional cytoskeletal tracks, with their motion characterised by high association of the enzyme to the biopolymer combined with highly dynamic motion along the track. Efforts to mimic this dynamic association and control translational motion in fully synthetic systems have been dominated by rotaxane-based systems, where the properties of the mechanical bond ensure complete association between the moving component (the macrocycle) and the track it encircles, while allowing high rates of translation through shuttling of the moving component under Brownian motion. In addition to the dynamic association displayed by many rotaxane systems, by careful design of the track and macrocyclic component, elegant strategies have been employed to further control the motion in these mechanically interlocked systems, with both energy and information ratchet mechanisms allowing directional translational motion to be achieved. Other than mechanical bonds, alternative platforms for achieving controlled translational motion in fully synthetic systems have had more limited success, with bipedal walker systems that exhibit dynamic association lacking mechanisms to achieve inherent directionality, and bipedal systems that do display high levels of directionality requiring stepwise intervention of an experimentalist (i.e., they lack the dynamic autonomous behaviour that underpins nature’s walkers). Here we introduce carbon-to-carbon metal migration as a new platform for dynamic association and show how such migrations, in combination with the incorporation of a simple hydrocarbon fuel, can be harnessed to achieve autonomous directional translational motion of a metal centre along the length of a polyaromatic thread
Compatibilization of polyolefin blends through acid–base interactions
No full textPolyolefins are ubiquitous in consumer products but are notoriously difficult to recycle due to the inherent incompatibility of their common varieties. Existing approaches to addressing this challenge either require complex syntheses or compromise the properties of the parent materials. Here, a new method to compatibilize mixed polyolefins is developed. With a single-step photocatalysis, acid or base functionality can be readily installed onto polyolefins. The combination of acid- and base-modified polyolefins functions as compatibilizers. Incorporating them into polyolefin blends results in excellent mechanical strength, with up to an 82-fold increase in ductility. Importantly, compatibilization can be readily achieved on post-consumer polyolefin mixtures. Furthermore, direct functionalization and compatibilization of polyolefin blends is achieved. This strategy promises to transform polyolefin recycling and will likely find broad applications
Temperature Correction of Near-Infrared Spectra of Raw Milk
No full textAccurate milk composition analysis is crucial for improving product quality, economic efficiency, and animal health in the dairy industry. Near-infrared (NIR) spectroscopy can quantify milk composition quickly and nondestructively. However, external factors, such as temperature fluctuations, can alter the molecular vibrations and hydrogen bonding in milk, altering the NIR spectra and leading to errors in predicting key constituents such as fat, protein, and lactose. This study compares the effectiveness of Piecewise Direct Standardization (PDS), Continuous PDS (CPDS), External Parameter Orthogonalization (EPO), and Dynamic Orthogonal Projection (DOP in correcting the impact of temperature-induced variations on predictions in milk long-wave NIR spectra (LW-NIR, 1000 to 1700 nm).
A total of 270 raw milk samples were analyzed, collecting both reflectance and transmittance spectra at five different temperatures (20°C, 25°C, 30°C, 35°C, and 40°C). The experimental setup ensured precise temperature control and accurate spectral measurements. PLSR models were calibrated at 30°C to predict milk fat, protein, and lactose content. The performance of these models was assessed before and after applying the temperature correction methods, with a primary focus on reflectance spectra.
Results indicate that EPO and DOP significantly enhance model robustness and prediction accuracy across all temperatures, outperforming PDS and CPDS, especially for lactose prediction. These orthogonalization methods were compared against PLSR models calibrated with spectra from all temperatures. EPO and DOP showed comparable or superior performance, highlighting their effectiveness without requiring extensive temperature-specific calibration data. These findings suggest that orthogonalization methods are particularly suitable for in-line milk quality measurements under farm conditions where temperature control is challenging. This study highlights the potential of advanced chemometric techniques to improve real- time, on-farm milk composition analysis, facilitating better farm management and enhanced dairy product quality
Confined hot-pressurized water in Brønsted-acidic Beta zeolite speeds up the O-demethylation of guaiacol
No full textNew lignocellulose biorefinery technologies that enable the conversion of lignin into platform chemicals are essential to reduce our future dependence on fossil resources. In this study, we investigate the Brønsted acid-catalyzed O-demethylation of guaiacol in hot-pressurized water (HPW) as a model reaction for transforming lignin-derived phenolic substrates featuring ortho methoxy groups. We compare the effects of Brønsted mineral acid (HCl) and microporous solid acid (H-BEA zeolite) in water to elucidate the hydrolysis mechanism and the impact of zeolite microporosity on reaction rates. Operando molecular modeling combined with experimental kinetic studies reveals that, regardless of the catalyst type, O-demethylation follows a concerted, one-step O-activated SN2 mechanism. This mechanism involves a strong hydrogen bond between guaiacol and a hydronium ion as an ionic contact pair. Protons confined within the zeolite form more active undercoordinated hydronium ions, which are associated with lower enthalpic requirements and thus accelerate the hydrolysis. The molecular organization of solvent and reactants around the confined catalytic active site plays a crucial role in modulating the association of the reacting species. These proof-of-concept results demonstrate the significant influence of solvent (water) coordination on acid-catalyzed bimolecular reactions, such as hydrolysis, within confined spaces
Fe-Catalyzed Structurally Divergent γ-Polyhaloalkylation of Si- loxydienes
No full textRegioselective γ-polyhaloalkylation is achieved using tetrahalomethanes or α,α,α-trihaloalkyl compounds and siloxydienes via Fe(II) catalysis. A range of siloxydienes are functionalized in good yield and high stereoselectivity under mild reaction conditions. Structural divergence is observed as either haloalkylated or haloalkenylated products are formed based on substitution pattern of the siloxydiene. The halogenated products show utility in further synthetic transformations selec- tive reduction and cross coupling reactions
Implications of weaving pattern on the material properties of two-dimensional molecularly woven fabrics
No full textSimilar to macroscopic woven fabrics, molecularly woven polymers constructed from identical molecular strands but different weaving architectures are anticipated to display diverse physical and mechanical characteristics. Nonetheless, identifying these distinctions and comprehending the underlying mechanisms poses a significant challenge. Herein, we evaluate the impacts of different weaving patterns—plain, mix, and basket—on the characteristics of two-dimensional (2D) organic woven polymers through systematic all-atom simulation. Three weaves, consisting of the same molecular strands, are produced by adjusting the connections of the enantiomers of an inherently chiral 2×2 interwoven grid. Among the tested patterns, the plain weave exhibits superior stability, minimal structural deformation, and the most consistent pore size compared to others. The maintenance of the weaves in kinetically stable high-energy states is attributed to both aromatic stacking and hydrogen bonding interactions between warp and weft strands, while the alteration of weaving patterns leads to variations in the type and strength of these weak interactions. Despite the differences on the weaving pattern, the mechanical stress tends to localize at the contact field. Further analysis on impact resistance and in-plane stretchability highlights how weaving architectures influence the energy dissipation pathways and reinforce the mechanical properties of individual molecular chains. Simulation outcomes indicate that the disparities resulting from various weave patterns primarily stem from the total number and density of entanglements, as well as the interstrand non-covalent interactions. This research highlights the critical influence of weaving architecture on molecularly interlacing material properties, providing valuable insights for future invention and engineering of molecular-level weaving
Exascale Quantum Mechanical Simulations: Navigating the Shifting Sands of Hardware and Software
No full textThe era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant role of graphical processing units (GPUs), demands a fundamental shift in software development strategies. This review examines the changing landscape of hardware and software for exascale computing, highlighting the limitations of traditional algorithms and software implementations in light of the increasing use of heterogeneous architectures in high-end systems. We discuss the challenges of adapting quantum chemistry software to these new architectures, including the fragmentation of the software stack, the need for more efficient algorithms (including reduced precision versions) tailored for GPUs, and the importance of developing standardized libraries and programming models