Search NASA⌕ Search

SEARCH · Search NASA

Results for “2D organic complexes”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

A simple and highly efficient protocol for 13 C-labeling of plant cell wall for structural and quantitative analyses via solid-state nuclear magnetic resonance

Plant cell walls are made of a complex network of interacting polymers that play a critical role in plant development and responses to environmental changes. Thus, improving plant biomass and fitness requires the elucidation of the structural organization of plant cell walls in their native environment. The 13 C-based multi-dimensional solid-state nuclear magnetic resonance (ssNMR) has been instrumental in revealing the structural information of plant cell walls through 2D and 3D correlation spectral analyses. However, the requirement of enriching plants with 13 C limits the applicability of this method. To our knowledge, there is only a very limited set of methods currently available that achieve high levels of 13 C-labeling of plant materials using 13 CO 2 , and most of them require large amounts of 13 CO 2 in larger growth chambers. In this study, a simplified protocol for 13C-labeling of plant materials is introduced that allows ca 60% labeling of the cell walls, as quantified by comparison with commercially labeled samples. This level of 13 C-enrichment is sufficient for all conventional 2D and 3D correlation ssNMR experiments for detailed analysis of plant cell wall structure. The protocol is based on a convenient and easy setup to supply both 13 C-labeled glucose and 13 CO 2 using a vacuum-desiccator. The protocol does not require large amounts of 13 CO 2 . This study shows that our 13 C-labeling of plant materials can make the accessibility to ssNMR technique easy and affordable. The derived high-resolution 2D and 3D correlation spectra are used to extract structural information of plant cell walls. This helps to better understand the influence of polysaccharide-polysaccharide interaction on plant performance and allows for a more precise parametrization of plant cell wall models.

09 BIOMASS FUELS↗

Raman enhancement induced by exciton hybridization in molecules and 2D materials

Abstract Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for trace-level fingerprinting. Recently, layered two-dimensional (2D) materials have gained significant interest as SERS substrates for providing stable, uniform, and reproducible Raman enhancement with the potential for trace-level detection. Yet, the development of effective 2D SERS substrates is still hindered by the lack of fundamental understanding of the coupling mechanism between target molecules and substrates. Here, we report a systematic excitation-dependent Raman spectroscopy investigation on the coupling between 2D materials such as SnS 2 , MoS 2 , WSe 2 , and graphene and small organic molecules like rhodamine 6G (Rh 6G). Strong coupling between SnS 2 and Rh 6G is found due to their degenerate excitons through Raman excitation profiles (REP), leading to the enhancement of Rh 6G vibrational modes that are observable down to 10 −13 M. Our study shows that exciton coupling in the substrate-adsorbate complex plays a vital role in the Raman enhancement effect, opening a new route for designing SERS substrates for high sensitivity.

Materials Science↗

Revisiting the Role of Entropy for Charge Separation in 1D Pi-Conjugated Semiconductors

Free carrier generation in organic donor/acceptor heterojunctions and redox-doped organic semiconductors is poorly understood, since assumed tight electron-hole binding conflicts with observed high free carrier yields. Cornerstone analyses that have guided the field for over 15 years predict that entropy can stabilize free charges in 2D and 3D pi-conjugated semiconductors but not in 1D systems. Here, the impact of entropy on charge generation in 1D pi-conjugated semiconductors is revisited by exploiting a greatly simplified system where enthalpy considerations alone should not allow for free charge generation. Noncontact solution-phase microwave conductivity is used to investigate the carrier density-dependent conductivity and dielectric constant in isolated chemically doped semiconducting single-walled carbon nanotubes in a low-dielectric solvent. Dopant chemical structure dramatically influences the carrier density-dependent complex conductivity, with bulky dopants facilitating carrier escape even at carrier densities below one carrier per nanotube. Three distinct numerical calculations show that entropic stabilization dramatically lowers the Gibbs energy barrier for free charge generation, explaining the high yield of free carriers, even in 1D. This renewed understanding of entropy's role in carrier generation has important implications for designing organic electronic devices-such as solar cells and thermoelectric energy harvesters-for enhanced carrier yield, conductivity, and performance.

36 MATERIALS SCIENCE↗

Mechanistic Insights into Copper(I) and Copper(II) Cation Exchange Reactions in CdSe Nanoplatelets

In this study, we investigated the synthesis of copper selenide nanoplatelets (NPLs) through a cation exchange reaction (CER) in 5-monolayer-thick CdSe NPLs using Cu(I) and Cu(II) precursors. We discovered that the exposure of CdSe NPLs to a Cu(I) precursor led to the transformation of NPLs into Cu 2-x Se while maintaining their nanoplatelet morphology. The replacement of Cd(II) with Cu(I) prevailed over the formation of doped structures. In the case of the Cu(II) precursor, we observed that Cu(II) was first reduced to Cu(I) before being intercalated into the host lattice, resulting in the synthesis of Cu 2-x Se, similar to CER with Cu(I) precursors but without preservation of the initial morphology of NPLs. Interestingly, the presence of oxygen was found to facilitate the cation exchange processes in CdSe NPLs, whereas a nitrogen atmosphere suppressed the CER. Further, despite the similar ionic sizes of Cu(I) and Cu(II), the substitution of Cd(II) with Cu(II) was found to be challenging, possibly due to the involvement of redox processes resulting in the significant deterioration of initial CdSe NPLs. We demonstrate that CER can achieve near-complete substitution of cadmium atoms with monovalent copper at room temperature. Understanding the processes involved in CERs is crucial for engineering more complex structures, such as high-entropy nanoparticles involving cation exchange with different oxidation states and development of material synthesis using machine learning and artificial intelligence approaches.

2D nanoplatelets↗

Jettison Engineering Trajectory Tool

The Jettison Engineering Trajectory Tool (JETT) performs the jettison analysis function for any orbiting asset. It provides a method to compute the relative trajectories between an orbiting asset and any jettisoned item (intentional or unintentional) or sublimating particles generated by fluid dumps to assess whether an object is safe to jettison, or if there is a risk with an item that was inadvertently lost overboard. The main concern is the interaction and possible recontact of the jettisoned object with an asset. This supports the analysis that jettisoned items will safely clear the vehicle, ensuring no collisions. The software will reduce the jettison analysis task from one that could take days to complete to one that can be completed in hours, with an analysis that is more comprehensive than the previous method. It provides the ability to define the jettison operation relative to International Space Station (ISS) structure, and provides 2D and 3D plotting capability to allow an analyst to perform a subjective clearance assessment with ISS structures. The developers followed the SMP to create the code and all supporting documentation. The code makes extensive use of the object-oriented format of Java and, in addition, the Model-View-Controller architecture was used in the organization of the code, allowing each piece to be independent of updates to the other pieces. The model category is for maintaining data entered by the user and generated by the analysis. The view category provides capabilities for data entry and displaying all or a portion of the analysis data in tabular, 2D, and 3D representation. The controller category allows for handling events that affect the model or view(s). The JETT utilizes orbital mechanics with complex algorithms. Since JETT is written in JAVA, it is essentially platform-independent.

Zaczek, Mariusz↗

Vascular Patterning Analysis by VESGEN 2D/3D with Bioinformatics: Updates for Rodent Tissues

Fractally branching vascular systems are a complex physiological requirement shared by humans with all higher terrestrial life forms, including other vertebrates, insects, and higher land plants. Vascular trees, networks, and tree-network composites are therefore mapped and quantified by the VESsel GENeration Analysis (VESGEN) software according to weighted physiological vascular rules that include vessel connectivity, tapering and bifurcational branching. According to fluid dynamics, successful vascular transport depends upon a complex distributed system of highly regulated laminar flow. VESGEN has elucidated changes in vascular patterning resulting from inflammatory, developmental and other signaling pathways within numerous tissues of major model organisms important for Space Biology, especially for rodents. Important early stage regenerative opportunities have been identified by VESGEN vascular analysis for visual impairments in the human retina, and is currently being used for research into astronaut visual and ocular disorders associated with long duration missions. The VESGEN 2D software is a mature, automated, widely published capability for which beta testing and public release by NASA is planned for the upcoming year. Early-stage capabilities for VESGEN 3D analysis are under development for the rodent retina and intestine as prototype tissues. A prototype VESGEN 2D Bioinformatics software capability has also been developed to associate phenotypic changes in molecular expression with vascular structure and function. By new VESGEN bioinformatic innovations, expression patterns of the genetic, transcriptional, protein and other markers for regulatory molecules such as vascular endothelial growth factor (VEGF) and their receptors, often indicators of tissue oxygenation status, are co-localized with alterations in vascular pattern. Biomarkers are therefore mapped and quantified as information dimensions directly correlated with the spatial dimensions of a vascular pattern. Further important technology innovations by NASA include substantial image segmentation advances for more automated binary extraction of the grayscale vascular patterns, together with informative associated image quality assessments. Vascular mapping and quantification capabilities for the rodent retina and intestine are illustrated for VESGEN 2D, along with technology status reports on VESGEN 3D and Bioinformatic capabilities. Research partially supported by Ames Center Innovation Awards.

Parsons-Wingerter, P.↗

The surface chemistry of the atomic layer deposition of metal thin films

Abstract In this perspective we discuss the progress made in the mechanistic studies of the surface chemistry associated with the atomic layer deposition (ALD) of metal films and the usefulness of that knowledge for the optimization of existing film growth processes and for the design of new ones. Our focus is on the deposition of late transition metals. We start by introducing some of the main surface-sensitive techniques and approaches used in this research. We comment on the general nature of the metallorganic complexes used as precursors for these depositions, and the uniqueness that solid surfaces and the absence of liquid solvents bring to the ALD chemistry and differentiate it from what is known from metalorganic chemistry in solution. We then delve into the adsorption and thermal chemistry of those precursors, highlighting the complex and stepwise nature of the decomposition of the organic ligands that usually ensued upon their thermal activation. We discuss the criteria relevant for the selection of co-reactants to be used on the second half of the ALD cycle, with emphasis on the redox chemistry often associated with the growth of metallic films starting from complexes with metal cations. Additional considerations include the nature of the substrate and the final structural and chemical properties of the growing films, which we indicate rarely retain the homogeneous 2D structure often aimed for. We end with some general conclusions and personal thoughts about the future of this field.

Materials Science↗

Isolation of a Cyclopentasilane from Magnesium Reduction of a Linear Hexasilane

The reductive cyclization of two linear hexasilanes is contrasted, where a methylated precursor yielded a cyclohexasilane while the tert-butyl-functionalized analog unexpectedly yielded a cyclopentasilane. A comprehensive analysis using X-ray diffraction, IR, HR, HRMS, and multinuclear (1H, 13C and 29Si) 1D and 2D NMR spectroscopy identified the 1,2-dihydrodisilane tBuPhHSi–SiHPhtBu as an additional product, which was interpreted as supportive of a mechanism involving silylene elimination. Here, the results of this study may prove informative about substituent effects in the practice of complex organosilicon molecular synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Applying Two-Dimensional Correlation Spectroscopy and Principal Component Analysis to Understand How Temperature Affects the Neptunium(V) Absorption Spectrum

The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO 2 + ) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO 2 + ) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy-conserving contact dynamics of nonspherical rigid-body particles

Understanding the contact dynamics of nonspherical particles is crucial for accurately modeling colloidal and granular systems where shape anisotropy dictates structural organization and transport properties. We here introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles by implementing vertex–boundary interactions in 2D and vertex–surface and edge–edge detection in 3D. The established formulation enables continuous force evaluation and prevents particle overlap while conserving total energy during translational and rotational motion. We demonstrate the framework’s stability and its utility to capture packing behavior, anisotropic diffusion, and equations of state of polygonal and polyhedral particles as examples. The framework establishes a robust and extensible foundation for investigating nonequilibrium dynamics of complex nonspherical particulate systems, enabling enhanced understanding of phenomena across spatiotemporal scales in self- and directed-assembly, granular flows, and hydrodynamics, potentially coupled with interactions that represent underlying physical mechanisms.

Discrete element method↗

Single-Particle Spectroscopy as a Versatile Tool to Explore Lower-Dimensional Structures of Inorganic Perovskites

The remarkable defect tolerant nature of inorganic cesium halide perovskites leading to near unity photoluminescence (PL) quantum yield (QY) and narrow emission linewidth across the entire visible spectrum, have provided a tantalizing platform for a development of a plethora of light-emitting applications. Recently, lower dimensional (2D, 1D, and 0D) perovskites have attracted further attention due to the enhanced thermal, photo and chemical stability as compared to their three-dimensional (3D) analogues. Combination of the external size quantization and internal octahedral organization provides a unique opportunity to study and harness “multidimensional” electronic properties engineered both on atomic scale and the nanoscale. However, crucial research to understand the elementary charge carrier dynamics in lower dimensional perovskites lags far behind the enormous effort to incorporate them into optoelectronic devices. In this Perspective, we provide a review of recent developments that focus on studies of the dynamics of excitonic complexes in Cs-based perovskite nanocrystals using single-particle time-resolved PL spectroscopy and photon correlation measurements. Single photon statistical studies not only offer the unprecedented level of detail to directly assess various recombination pathways but also provide insights into specifics of carrier’s localization. Further, we discuss the underlying physicochemical processes that govern PL emission and draw attention to a number of attributes within this class of the materials, especially lower-dimensional perovskites that may indicate the common origin of the PL emission, as well as provide a route map for the vast unexplored territories where single particle spectroscopy can be a powerful tool to unravel crucial information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Screw-Dislocation-Driven Growth of 2D Perovskite Spiral Microplates

Two-dimensional (2D) organic–inorganic halide perovskites are solution-processable semiconductors that are promising for optoelectronic applications. Understanding crystallization mechanisms to achieve control over nanostructures is important for optimizing desired properties. Here we introduce a versatile strategy to synthesize spiral microplates of diverse 2D perovskites at the air–water interface through screw-dislocation-driven growth. Spirals of 11 2D perovskite compositions (LA) 2 (A) n−1 Pb n X 3n+1 with different spacer (LA) cations, A-cations, halide (X) anions, and n-number can be grown. They typically consist of single- or few-layer perovskite step heights but exhibit stacking complexity when multiple dislocations interact. The spiral microplates exhibit the characteristic optical properties (photoluminescence and second-harmonic generation) of the underlying 2D perovskites. Fluorescence-detected circular dichroism imaging shows that the chirality of the spiral center does not translate to the observed chiroptical properties of the microplate, consistent with the length scale of the chiral distortion. Furthermore, this solution growth of perovskite spirals diversifies the perovskite microstructures for optoelectronics and other applications.

2D halide perovskites↗

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗

Detecting Reactive Products in Carbon Capture Polymers with Chemical Shift Anisotropy and Machine Learning

Aminopolymers are attractive sorbents for CO 2 direct air capture applications due to their high density of amine groups, which can readily react with atmospheric levels of CO 2 to form chemisorbed species. The identity of these chemisorbed species and the functional groups that form upon oxidative degradation depends on both material properties and processing conditions, forming a variety of carbonyl-type sites such as ammonium carbamates, bicarbonates, carbonates, carbamic acids, ureas, and amides. 13 C solid-state nuclear magnetic resonance (NMR) is often used to help elucidate the identity of these reacted species, but it is challenging due to the narrow chemical shift range of carbonyl sites. Herein, we demonstrate the application of a two-dimensional (2D) chemical shift anisotropy (CSA) recoupling pulse sequence (ROCSA) to obtain CSA tensor values at each isotropic chemical shift, overcoming limitations of isotropic peak resolution. CSA tensor values describe the local chemical environment and can readily differentiate between the chemisorbed and degradation products. To aid identification, we also developed a k-nearest neighbor (kNN) classification model to distinguish the functional groups via their CSA tensor parameters. This methodology was demonstrated on poly(ethylenimine) in γ-Al 2 O 3 exposed to CO 2 and showed that the chemisorbed products are ammonium carbamate and a mixed carbamate–carbamic acid species. The sample was analyzed again after desorption at 100 °C inducing mild degradation, and the remaining products were strongly bound carbamate and urea species. In conclusion, the combination of 2D CSA measurements coupled with a kNN classification model enhances the ability to accurately identify chemisorbed or degradation products in complex carbon capture materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complex Formation and Dissociation Dynamics on Amorphous Silica Surfaces

Benzene complex formation and dissociation dynamics with silanols on the amorphous silica surfaces of nanoporous SiO 2 , from a benzene/carbon tetrachloride solution, were measured by the growth of off-diagonal peaks in the two dimensional infrared (2D IR) chemical exchange spectrum of the isolated Si-OD stretch. The presence of two types of isolated silanols, referred to as type I and II, was revealed, with dissociation time constants of 82 ps and 4.0 ps for type I and II complexes, respectively. The type I silanols are associated with the main IR absorption feature in the Si-OD stretching region, while the type II silanols give rise to a broader shoulder to lower frequency. Polarization selective pump-probe (PSPP) measurements provided the vibrational lifetimes and orientational relaxation rates of the two silanols in the CCl 4 (free) and benzene (complex) environments. The type II silanols constitute roughly 30% of the isolated silanol population and exhibit a substantially faster rate of vibrational relaxation, making the type I dynamics the dominant contribution to the PSPP and 2D IR signals. From the measured dissociation times, the enthalpies of formation for the two surface complexes were obtained; the formation of the type I complex being significantly more exothermic. Furthermore, as the type II site is preferentially removed from the amorphous silica surface with increasing activation temperature, the results provide a reasonable explanation for the increased exothermicity of benzene adsorption on silica with increasing activation temperature in previous calorimetry experiments.

14 SOLAR ENERGY↗

Coupled Lattice Boltzmann Modeling Framework for Pore-Scale Fluid Flow and Reactive Transport

In this paper, we propose a modeling framework for pore-scale fluid flow and reactive transport based on a coupled lattice Boltzmann model (LBM). We develop a modeling interface to integrate the LBM modeling code parallel lattice Boltzmann solver and the PHREEQC reaction solver using multiple flow and reaction cell mapping schemes. The major advantage of the proposed workflow is the high modeling flexibility obtained by coupling the geochemical model with the LBM fluid flow model. Consequently, the model is capable of executing one or more complex reactions within desired cells while preserving the high data communication efficiency between the two codes. Meanwhile, the developed mapping mechanism enables the flow, diffusion, and reactions in complex pore-scale geometries. We validate the coupled code in a series of benchmark numerical experiments, including 2D single-phase Poiseuille flow and diffusion, 2D reactive transport with calcite dissolution, as well as surface complexation reactions. The simulation results show good agreement with analytical solutions, experimental data, and multiple other simulation codes. In addition, we design an AI-based optimization workflow and implement it on the surface complexation model to enable increased capacity of the coupled modeling framework. Compared to the manual tuning results proposed in the literature, our workflow demonstrates fast and reliable model optimization results without incorporating pre-existing domain knowledge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Access to Advanced Functional Materials through Postmodification of Biomimetic Assemblies via Click Chemistry

The design, synthesis, and fabrication of functional nanomaterials with specific properties remain a long-standing goal for many scientific fields. The self-assembly of sequence-defined biomimetic synthetic polymers presents a fundamental strategy to explore the chemical space beyond biological systems to create advanced nanomaterials. Moreover, subsequent chemical modification of existing nanostructures is a unique approach for accessing increasingly complex nanostructures and introducing functionalities. Of these modifications, covalent conjugation chemistries, such as the click reactions, have been the cornerstone for chemists and materials scientists. Herein, we highlight some recent advances that have successfully employed click chemistries for the postmodification of assembled one-dimensional (1D) and two-dimensional (2D) nanostructures to achieve applications in molecular recognition, mineralization, and optoelectronics. Specifically, biomimetic nanomaterials assembled from sequence-defined macromolecules such as peptides and peptoids are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗