Search NASA⌕ Search

SEARCH · Search NASA

Results for “individual molecule structure”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ORNL_AISD_DL-HLgap

This dataset provides supplementary molecular dataset of Deep Learning Workflow for the Inverse Design of Molecules with Specific Optoelectronic Properties. The dataset comprises three main directories such as GDB-9_dataset, Low_HL_Gap_dataset, and High_HL_Gap_dataset which individually has csv files, smiles_txt files, pdb files and xyz files containing information of molecular structures, properties and coordinates generated from deep learning workflow using generative model, surrogate model and DFTB calculation results. GDB-9_dataset contains the molecular data extracted from the original GDB-9 dataset with additional data of DFTB HL gap, surrogate HL gap and molecular property analysis. (the number of atoms, aromaticity and double bond equivalent) Low_HL_Gap_dataset and High_HL_Gap_dataset contains series of dataset for different generations with further split to train and test dataset that were obtained from the iterative workflow described in the manuscript. Additional directory Chemiscope_visualization in Low_HL_Gap_dataset directory contains compressed json files to visualize molecules using chemiscope.org page or application to help readers examine generated molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Theory of strong-field sequential double ionization of polyatomic molecules

Understanding of strong-field sequential double ionization (SDI) of molecules by a highly intense infrared laser pulse could be the key to observing electron motion in molecules in the attosecond to femtosecond timescale. Based on a novel density matrix approach for SDI (DM-SDI), a recent theoretical study has shown that SDI can be used as a probe to monitor the changes in vibronic coherence in homonuclear diatomic molecules. In this article, we extend the DM-SDI model to general molecules that could possess permanent dipole moments and arbitrary symmetry. We apply the model to SDI of a water molecule and identify the formation pathway of individual dication states. We further deduce that kinetic energy release spectra from two- and three-body fragments could carry the signature of vibronic coherence between the lowest two states of the water cation. Furthermore, our results suggest that observables from the SDI probe can be interpreted intuitively with only the knowledge of electronic structures of populated ionic states, making the SDI probe to be a highly desirable probing scheme for vibronic coherence in generic molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗
DOE OSTI2022

Metallurgical alloy approach to two-dimensional supramolecular materials

Alloys are normally mixtures of metallic elements used to search for superior functional properties compared with their individual components. Although a quintessential approach to better materials in metallurgy, the concept of alloying has been expanded to other inorganic materials and covalent polymers. In this work, we report on alloy formation of small organic molecules structured as amphiphilic chromophores in water. Using X-ray scattering, microscopy, and optical spectroscopy, we unambiguously demonstrate the formation of supramolecular alloys with changes in physical, photophysical, and mechanical properties. Additionally, we identify single-crystalline, two-dimensional supramolecular polymers containing multiple molecular species, analogous to intermetallic compounds. The mechanism of alloy formation suggests the possibility of controlled growth in these supramolecular assemblies to create emergent functional structures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Improved Accuracy in Semi-Experimental Structure Determination by Resolving Problems Associated with Rotation of Principal Inertial Axes of Isotopologues: Structures of 1,3-Oxazole ( c -C 3 H 3 NO)

The rotational spectrum of the normal isotopologue of 1,3-oxazole (c-C 3 H 3 NO) was observed from 43 to 750 GHz. Over 3900 transitions for the ground vibrational state are measured, assigned, and least-squares fit to sextic centrifugally distorted-rotor Hamiltonians. The measured frequencies and resulting spectroscopic constants from this extended spectral range, combined with previous measurements of the nuclear quadrupole coupling constants, will facilitate astronomical searches for oxazole across the majority of the range of modern radiotelescopes. Spectra for a set of 30 oxazole isotopologues, which include multiple isotopic substitutions of each atom, are used to determine the first semi-experimental equilibrium ($r$$^{SE}_{e}$) structure and semi-experimental substitution structure ($r$$^{SE}_{e}$), each using CCSD(T) computed values for the vibration–rotation interaction and electron-mass corrections. The large number of isotopologues, including 21 isotopologues observed for the first time, and the redundant substitutions of each atom provide sufficient spectroscopic information to determine the $r$$^{SE}_{e}$ structure with the expected high level of accuracy and precision (0.0001 or 0.0002 Å in bond distances and 0.013 to 0.025° in bond angles). In the course of this study, we analyzed a known issue for some $r$$^{SE}_{e}$ structure determinations of near-oblate asymmetric tops in which inclusion of individual isotopologues degrades the structure determination. We demonstrate that this problem primarily arises from the difference in the values of the computed vibration–rotation interaction corrections as evaluated at the computed re geometry vs the $r$$^{SE}_{e}$ geometry of the “real” molecule. Our solution to this problem substantially improves the $r$$^{SE}_{e}$ structure of oxazole and likely can be generalized to many other molecules.

Chemical structure↗
DOE OSTI2020

Domain Separated Density Functional Theory for Reaction Energy Barriers and Optical Excitations

We recently proposed Domain Separated Density Functional Theory (DS-DFT), a framework that allows for the combination of different levels of theory for the computation of the electronic structure of molecules. Here, this work discusses the application of DS-DFT to the computation of transition-state energy barriers and optical absorption spectra. We considered several hydrogen abstraction reactions and optical spectra of molecule/metal cluster systems, including the absorption of individual species such as carbon monoxide, methane, and molecular hydrogen to a Li6 cluster. We present and discuss two domain-separated methods: i), the screened-density approximation (SDA), and, ii), linearly weighted exchange (LWE). We find that SDA, which is applied as a hybridization based on atomic domains, could be useful to computing energy barriers, whereas LWE is suited for the analysis of electronic properties such as ground-state gaps, excitation energies, and oscillator strengths.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Impact of environmental oxygen on nanoparticle formation and agglomeration in aluminum laser ablation plumes

Here, the role of ambient oxygen gas (O 2 ) on molecular and nanoparticle formation and agglomeration was studied in laser ablation plumes. As a lab-scale surrogate to a high explosion detonation event, nanosecond laser ablation of an aluminum alloy (AA6061) target was performed in atmospheric pressure conditions. Optical emission spectroscopy and two mass spectrometry techniques were used to monitor the early to late stages of plasma generation to track the evolution of atoms, molecules, clusters, nanoparticles, and agglomerates. The experiments were performed under atmospheric pressure air, atmospheric pressure nitrogen, and 20% and 5% O 2 (balance N 2 ), the latter specifically with in situ mass spectrometry. Electron microscopy was performed ex situ to identify crystal structure and elemental distributions in individual nanoparticles. We find that the presence of ≈20% O 2 leads to strong AlO emission, whereas in a flowing N 2 environment (with trace O 2 ), AlN and strong, unreacted Al emissions are present. In situ mass spectrometry reveals that as O 2 availability increases, Al oxide cluster size increases. Nanoparticle agglomerates formed in air are found to be larger than those formed under N 2 gas. High-resolution transmission electron microscopy demonstrates that Al 2 O 3 and AlN nanoparticle agglomerates are formed in both environments; indicating that the presence of trace O 2 can lead to Al 2 O 3 nanoparticle formation. The present results highlight that the availability of O 2 in the ambient gas significantly impacts spectral signatures, cluster size, and nanoparticle agglomeration behavior. These results are relevant to understanding debris formation in an explosion event, and interpreting data from forensic investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Correlating Li-Ion Solvation Structures and Electrode Potential Temperature Coefficients

Temperature coefficients (TCs) for either electrochemical cell voltages or potentials of individual electrodes have been widely utilized to study the thermal safety and cathode/anode phase changes of lithium (Li)-ion batteries. However, the fundamental significance of single electrode potential TCs is little known. Here, we discover that the Li-ion desolvation process during Li deposition/intercalation is accompanied by considerable entropy change, which significantly contributes to the measured Li/Li + electrode potential TCs. To explore this phenomenon, we compare the Li/Li + electrode potential TCs in a series of electrolyte formulations, where the interaction between Li-ion and solvent molecules occurs at varying strength as a function of both solvent and anion species as well as salt concentrations. As a result, we establish correlations between electrode potential TCs and Li-ion solvation structures and further verify them by ab initio molecular dynamics simulations. We show that measurements of Li/Li + electrode potential TCs provide valuable knowledge regarding the Li-ion solvation environments and could serve as a screening tool when designing future electrolytes for Li-ion/Li metal batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Site-specific interrogation of an ionic chiral fragment during photolysis using an X-ray free-electron laser

Abstract Short-wavelength free-electron lasers with their ultrashort pulses at high intensities have originated new approaches for tracking molecular dynamics from the vista of specific sites. X-ray pump X-ray probe schemes even allow to address individual atomic constituents with a ‘trigger’-event that preludes the subsequent molecular dynamics while being able to selectively probe the evolving structure with a time-delayed second X-ray pulse. Here, we use a linearly polarized X-ray photon to trigger the photolysis of a prototypical chiral molecule, namely trifluoromethyloxirane (C 3 H 3 F 3 O), at the fluorine K-edge at around 700 eV. The created fluorine-containing fragments are then probed by a second, circularly polarized X-ray pulse of higher photon energy in order to investigate the chemically shifted inner-shell electrons of the ionic mother-fragment for their stereochemical sensitivity. We experimentally demonstrate and theoretically support how two-color X-ray pump X-ray probe experiments with polarization control enable XFELs as tools for chiral recognition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Analytical derivatives of the individual state energies in ensemble density functional theory. II. Implementation on graphical processing units (GPUs)

Conical intersections control excited state reactivity, and thus, elucidating and predicting their geometric and energetic characteristics are crucial for understanding photochemistry. Locating these intersections requires accurate and efficient electronic structure methods. Unfortunately, the most accurate methods (e.g., multireference perturbation theories such as XMS-CASPT2) are computationally challenging for large molecules. The state-interaction state-averaged restricted ensemble referenced Kohn–Sham (SI-SA-REKS) method is a computationally efficient alternative. The application of SI-SA-REKS to photochemistry was previously hampered by a lack of analytical nuclear gradients and nonadiabatic coupling matrix elements. We have recently derived analytical energy derivatives for the SI-SA-REKS method and implemented the method effectively on graphical processing units. We demonstrate that our implementation gives the correct conical intersection topography and energetics for several examples. Furthermore, our implementation of SI-SA-REKS is computationally efficient, with observed sub-quadratic scaling as a function of molecular size. This demonstrates the promise of SI-SA-REKS for excited state dynamics of large molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Manipulating the Assembly and Architecture of Fibrillar Silk

Silk is a unique and exceptionally strong biological material. However, no synthetic method has yet come close to replicating the properties of natural silk. This shortfall is attributed to an insufficient understanding of both silk nanofibril structure and the mechanism of formation. Here in situ atomic force microscopy (AFM) and photo-induced force microscopy (PiFM) is utilized to investigate the formation process and define the basic structural paradigm of individual silk nanofibrils. By visualizing the multistage process of silk nanofibril formation, the importance of conformational transformations along the assembly pathway is revealed. Unfolded silk structures initially accumulate into amorphous clusters, which then evolve into crystal nuclei via conformational transformation into β-crystallites. Nanofibril elongation then occurs through the attachment of silk molecules at a single end of the nanofibril tip; this is facilitated through the formation of a new amorphous cluster that then repeats the aforementioned conformational transformation. However, enzymatic digestion of the amorphous regions leads to direct, rapid elongation of β-crystalline fibers. These findings imply that the energy landscape is characterized by shallow minima associated with intermediate states, which can be eliminated by introducing β-crystallites, and motivate research into the directed modification of the silk assembly pathway to select for features beneficial to specific applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Applying Crystallography and 19 F NMR to investigate dynamics and partner protein interactions in a long chain Flavodoxin

Flavodoxin (Fld) is a small FMN containing protein that is involved in single electron transfer. The long‐chain flavodoxin in Rhodopseudomonas palustris bacteria replaces ferredoxin as a low‐potential electron carrier when iron is scarce. Thus it is proposed to interact with the bifurcating electron transfer flavoprotein (ETF) that yields low‐potential electrons. A surface loop on Fld interacts with another of Fld's partner proteins, so we hypothesize that it also mediates Fld's interaction with ETF. To monitor interactions with ETF directly and investigate dynamics in this loop, we are using 19 F NMR in solution. 19 F is hyperresponsive to changes in its chemical environment with a chemical shift range of >300 ppm. To provide a static reference point and assess structural heterogeneity, we are also exploiting X‐ray crystallography. In this study we selectively fluorinated the five tyrosine residues in Fld. We obtained resonance assignments from 19 F spectra of Fld variants in which individual tyrosine residues have been replaced. We obtain well resolved signals for each residue, but the resonances' linewidths indicate dynamics that affects some resonances more than others. Y90 residue displays two resonances demonstrating two different conformations that interconvert slowly on an NMR time scale. Meanwhile the crystal structure solved at 2.1Å resolution reveals two molecules per asymmetric unit providing two perspectives on the details of the structure. The crystal symmetry is monoclinic in contrast to most of the other Flds, which are orthorhombic. Interestingly, the long loop bearing Y121 and Y123 is not well resolved in chain B of the crystal structure, and the NMR line of Y123 is exceptionally broad, both indicating that the loop is dynamic and capable of altering its conformation to accomodate binding to a partner protein. Future directions include monitoring the changes in the 19 F NMR of the Fld when titrated with the partner protein, temperature dependence of the NMR spectrum and relaxation studies to evaluate time scales of motions.

Khan, Sharique↗
DOE OSTI2021

Substrate Partitioning into Protein Macromolecular Frameworks for Enhanced Catalytic Turnover

Spatial partitioning of chemical processes is an important attribute of many biological systems, the effect of which is reflected in the high efficiency of enzymes found within otherwise chaotic cellular environments. Barriers, often provided through the formation of compartments or phase segregation, gate the access of macromolecules and small molecules within the cell and provide an added level of metabolic control. Taking inspiration from nature, we have designed virus-like particles (VLPs) as nanoreactor compartments that sequester enzyme catalysts and have used these as building blocks to construct 3D protein macromolecular framework (PMF) materials, which are structurally characterized using small-angle X-ray scattering (SAXS). Additionally, the highly charged PMFs form a separate phase in suspension, and by tuning the ionic strength, we show positively charged molecules preferentially partition into the PMF, while negatively charged molecules are excluded. This molecular partitioning was exploited to tune the catalytic activity of enzymes enclosed within the individual particles in the PMF, the results of which showed that positively charged substrates had turnover rates that were 8500× faster than their negatively charged counterparts. Moreover, the catalytic PMF led to cooperative behavior resulting in charge dependent trends opposite to those observed with individual P22 nanoreactor particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Hybrid-Lipid Bilayers Induce n -Alkyl-Chain Order in Reversed-Phase Chromatographic Surfaces, Impacting their Shape Selectivity for Aromatic Hydrocarbon Partitioning

Shape selectivity is important in reversed-phase liquid chromatographic separations, where stationary phases are capable of separating geometric isomers, thereby resolving solutes based on their three-dimensional structure or shape rather than other chemical differences. Numerous chromatographic studies have been carried out using n-alkyl-chain-modified columns to understand how molecular shape affects retention. For polycyclic aromatic hydrocarbons (PAHs), it was found that planar compounds were selectively retained over non-planar structures of comparable molecular weight on surfaces with longer n-alkyl chains, higher chain-density, or at lower temperatures, where selectivity likely arises with greater ordering of the n-alkyl chains. A limitation of these studies, however, is the small range of chain ordering that can be achieved and lack of a direct measure of the n-alkyl-chain order of the stationary phases. In this work, we employ a C 18 stationary phase modified with a monolayer of phospholipid as a means of significantly varying the n-alkyl chain order. These hybrid-supported lipid bilayers, which have previously been employed as membrane-like stationary phases for measuring lipophilicity, provide a unique approach to control n-alkyl chain ordering by varying the acyl chain length and degree of unsaturation of the phospholipid modifier. The degree of alkyl-chain order of the resulting modified surfaces is determined from the ratio of trans- versus gauche-conformers, measured in situ within individual porous particles by confocal Raman microscopy. This methodology was also used to assess the affinity of these surfaces for planar versus non-planar PAH molecules. The retention selectivity for the planar versus non-planar compounds, thus determined, was found to vary significantly and systematically with the degree of order of the acyl/alkyl chains in the hybrid-supported lipid bilayers. Furthermore, the investigation also demonstrates the utility of confocal Raman microscopy for interrogating the impact of solute partitioning on stationary-phase structure within porous chromatographic particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Exciton Delocalization in Indolenine Squaraine Aggregates Templated by DNA Holliday Junction Scaffolds

Exciton delocalization plays a prominent role in the photophysics of molecular aggregates, ultimately governing their particular function or application. DNA is a compelling scaffold in which to template molecular aggregates and promote exciton delocalization. As individual dye molecules are the basis of exciton delocalization in molecular aggregates, their judicious selection is important. Motivated by their excellent photostability and spectral properties, here we examine the ability of squaraine dyes to undergo exciton delocalization when aggregated via a DNA Holliday junction (HJ) template. A commercially available indolenine squaraine dye was chosen for the study given its strong structural resemblance to Cy5, a commercially available cyanine dye previously shown to undergo exciton delocalization in DNA HJs. Three types of DNA-dye aggregate configurations—transverse dimer, adjacent dimer, and tetramer—were investigated. Signatures of exciton delocalization were observed in all squaraine-DNA aggregates. Specifically, strong blue shift and Davydov splitting were observed in steady-state absorption spectroscopy and exciton-induced features were evident in circular dichroism spectroscopy. Strongly suppressed fluorescence emission provided additional, indirect evidence for exciton delocalization in the DNA-templated squaraine dye aggregates. To quantitatively evaluate and directly compare the excitonic Coulombic coupling responsible for exciton delocalization, the strength of excitonic hopping interactions between the dyes were obtained by simultaneous fitting the experimental steady-state absorption and CD spectra via a Holstein-like Hamiltonian in which, following the theoretical approach of Kühn, Renger, and May, the dominant vibrational mode is explicitly considered. The excitonic hopping strength within indolenine squaraines was found to be comparable to that of the analogous Cy5 DNA-templated aggregate. The squaraine aggregates adopted primarily an H-type (dyes oriented parallel to each other) spatial arrangement. Extracted geometric details of dye mutual orientation in the aggregates enabled close comparison of aggregate configurations and the elucidation of the influence of dye angular relationship on excitonic hopping interactions in squaraine aggregates. Furthermore, these results encourage the application of squaraine-based aggregates in next generation systems driven by molecular excitons.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pore space partition of metal-organic frameworks for gas storage and separation

Pore space partition (PSP) concept is a synthetic design concept and can also serve as a structure analysis method useful for next-step synthetic planning and execution. PSP provides an integrated chemistry-topology-focused tool to design new materials platforms. While PSP is no less effective for making large-pore materials, the growing importance of small-molecule gas storage and separation for green-energy applications provides impetus for developing small-pore materials for which the PSP strategy is uniquely suited. Currently, the best embodiment of the PSP concept is the partitioned-acs (pacs) platform in which both fine or coarse adjustments to the building blocks have sparked a transformation of a prototype framework into a huge and continuously expanding family of chemically robust materials with controllable pore metrics and functionalities suitable for tailored applications. The pacs compositional diversity results from the platform’s intrinsic multi-module nature, geometric flexibility and tolerance towards individual module variations, and mutual structure-directing effects among various modules, all of which combine to enable the molecular-level uniform co-assemblies of chemical components rarely seen together elsewhere. Here, in this contribution, we present an overview of different pore space engineering methods and how different MOF materials have contributed to important advances in chemical stability, industrial gas storage and gas separation. In particular, we will focus on synthetic assembly of the pacs system, highlighting the differences of pacs materials from other MOF platforms and advantages of pacs materials in enhancing various MOF properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗