Chemical Correlation Research Articles

Correlations between product distribution and feedstock composition in thermal cracking processes for mixed plastic waste

Thermal conversion can transform the carbon-based waste into valuable chemicals to be further used in the petrochemical industry for a polymeric carbon circular economy. This work’s aim was to identify chemical correlations between the thermal-cracking products and the feedstock polymer composition when using highly blended waste streams. The challenges addressed were to: (i) access a pool of experimental data on the monomer recovery potential of real-life, highly blended waste streams; (ii) estimate the polymer constituents of the mixed waste streams; and (iii) formulate a generic and systematic method to identify correlations between feedstock constituents and cracking products. Different post-consumer waste streams were investigated, including cardboard, automotive shredder residues, cable stripping waste, and textile waste. The cracking experiments were performed in a 2–4MWth industrial-scale Dual Fluidized Bed system at 800 °C using steam as fluidization agent. The polymeric constituents of the feedstocks were estimated using a numerical convex optimization method. To identify correlations between the feedstocks and products, a carbon bond-based classification was introduced. The experimental monomer yield ranged from 0.08 kg/kgf to 0.3 kg/kgf (f = feedstock) for the evaluated materials, corresponding to a carbon feedstock conversion rate between 14 % and 44 %. High yields of valuable monomers were obtained for the materials with the highest polyolefin content. The olefin monomer production correlated positively to the amount of aliphatic carbon in the original material and negatively to the carbon contents of the aromatic rings. From the trends observed, it was concluded that a framework based on carbon bond types is a promising approach to identify such correlations, which could serve as predictive tools for monomer recovery based on material’s composition and overall process conditions.

Conformational ensemble of the NSP1 CTD in SARS-CoV-2: Perspectives from the free energy landscape

The nonstructural protein-1 (NSP1) of the severe acute respiratory syndrome-associated coronavirus 2 plays a crucial role in the translational shutdown and immune evasion inside host cells. Despite its known intrinsic disorder, the C-terminal domain (CTD) of NSP1 has been reported to form a double α-helical structure and block the 40S-ribosomal channel for mRNA translation. Experimental studies indicate that NSP1 CTD functions independently from the globular N-terminal region separated with a long linker domain, underscoring the necessity of exploring the standalone conformational ensemble. In this contribution, we utilize exascale computing resources to yield unbiased molecular dynamics simulation of NSP1 CTD in all-atom resolution starting from multiple initial seed structures. A data-driven approach elicits collective variables (CVs) that are significantly superior to conventional descriptors in capturing the conformational heterogeneity. The free energy landscape as a function of the CV space is estimated using the modified expectation maximized molecular dynamics. Originally developed by us for small peptides, here, we establish the efficacy of expectation maximized molecular dynamics in conjunction with data-driven CV space for a more complex and relevant biomolecular system. The results reveal the existence of two disordered metastable populations in the free energy landscape that are separated from the conformation resembling ribosomal subunit bound state by high kinetic barriers. Chemical shift correlation and secondary structure analysis capture significant differences among key structures of the ensemble. Altogether, these insights can underpin drug development studies and mutational experiments that help induce population shifts to alter translational blocking and understand its molecular basis in further detail.

Mask or Enhance: Data Curation Aiding the Discovery of Piezoresponse Force Microscopy Contributors

AbstractPiezoresponse force microscopy (PFM) is routinely used to probe the nanoscale electromechanical response of ferroelectric and piezoelectric materials. However, many challenges remain in the interpretation of the recovered signal. Specifically, many non‐ferroelectric contributions affect the measured response, ranging from electrostatics, to charge injection and trapping, and topographic cross‐talk. Recently, machine learning (ML) has been utilized to identify multiple contributors within complex data systems, such as PFM response. A substantial advancement in ML approaches for PFM techniques is offered by dimensional stacking, enabling encoding of physical and/or chemical correlations within the materials' response across different data dimensions spanning varying ranges. However, dimensional stacking requires appropriate scaling for each dimension (before ML analysis) to minimize undesired information loss. Here, the impact of clustering globally and locally scaled parameters in polarization switching experiments via resonant PFM (RPFM) are discussed. Specifically, dimensional stacking of scaled parameters can mask or enhance ferroelectric and non‐ferroelectric behaviors, and aid identification of various physical phenomena contributing to the measured RPFM response. This study highlights the importance of data curation for ML, and its role in identifying signal contributors to scanning probe microscopy (SPM)‐based techniques with multidimensional data, such as resonant and/or spectroscopic SPM.

Geochemical Characteristics of Rare-Metal, Rare-Dispersed, and Rare-Earth Elements and Depositional Environments in the Shanxi Formation Coal, Huainan Coalfield, Anhui, China

Coal, being one of the major energy sources for power generation, contains several critical trace elements. There is a growing scarcity and expense of these critical elements as a result of the increased demand and limitation of mining sources. To explore the geochemical characteristics of the rare-metal, rare-dispersed (scattered), and rare-earth elements (TREs) in coal, 25 coal seam samples of the Shanxi Formation in the Huainan coalfield were collected. The major element oxides, minerals, and TREs were analyzed by X-ray fluorescence spectroscopy (XRF), X-ray diffraction (XRD), and inductively coupled plasma-mass spectrometry (ICP-MS). The results revealed that the coal of the Shanxi Formation had ultra-low moisture and low ash yield and was medium-high-volatility with low sulfur content and high calorific value. Concerning minerals, the coal was mainly composed of kaolinite, illite, quartz, calcite, dolomite, and pyrite. Compared with Chinese coal and world hard coal, rare-metal element Li and rare-dispersed element Se were enriched, whereas Ga and Ta were only slightly enriched. The average content of REYs was 51.34 μg/g, which is lower than the average content of REYs in Chinese coal. It has the enrichment characteristics of light REYs. In the vertical direction, the content of most TREs was higher in the roof and floor of the coal seam and the parting, indicating that the sedimentary microenvironment plays an important role in controlling the migration and enrichment of elements. The experimental results of sequential chemical extraction and correlation analysis showed that the TREs in the Shanxi Formation coal mainly exist in a residual and carbonate bound state, and occur in clay minerals and carbonate minerals. The enrichment of Se may be due to its high organic form ratio. The C-value, B content, w(Sr)/w(Ba), and REY geochemical parameters indicated that the Shanxi Formation Coal seam was developed in a transitional, semi-saline, deltaic sedimentary environment. With their development affected by seawater, REYs in coal are greatly supplied by terrigenous clastics. The complex sedimentary environment is an important reason for the varying occurrence states of TREs in the Shanxi Formation coals.

Impallidane skeleton as a novel triterpenoid methyl ether from rhizomes of Imperata cylindrica var. koenigii f. pallida.

ABSTRUCT: n-Hexane extract of rhizomes of Imperata cylindrica var. koenigii f. pallida yielded five novel skeletal triterpenoids, designed as impallidin (1), impallidol (2), impallidin ozonide (3a, 3b), trisnorimpallidin aldehyde (4), tetranorimpallidin aldehyde (5). Structures of novel compounds were elucidated by mainly 2D NMR and other spectroscopic analysis and chemical correlations. Alternatively, compound 3a, 3b was derivatized from 1 under ozone oxidation condition.

Unambiguous Identification of Glucose-Induced Glycation in mAbs and other Proteins by NMR Spectroscopy

ObjectiveGlycation is a non-enzymatic and spontaneous post-translational modification (PTM) generated by the reaction between reducing sugars and primary amine groups within proteins. Because glycation can alter the properties of proteins, it is a critical quality attribute of therapeutic monoclonal antibodies (mAbs) and should therefore be carefully monitored. The most abundant product of glycation is formed by glucose and lysine side chains resulting in fructoselysine after Amadori rearrangement. In proteomics, which routinely uses a combination of chromatography and mass spectrometry to analyze PTMs, there is no straight-forward way to distinguish between glycation products of a reducing monosaccharide and an additional hexose within a glycan, since both lead to a mass difference of 162 Da.MethodsTo verify that the observed mass change is indeed a glycation product, we developed an approach based on 2D NMR spectroscopy spectroscopy and full-length protein samples denatured using high concentrations of deuterated urea.ResultsThe dominating β-pyranose form of the Amadori product shows a characteristic chemical shift correlation pattern in 1H-13C HSQC spectra suited to identify glucose-induced glycation. The same pattern was observed in spectra of a variety of artificially glycated proteins, including two mAbs, as well as natural proteins.ConclusionBased on this unique correlation pattern, 2D NMR spectroscopy can be used to unambiguously identify glucose-induced glycation in any protein of interest. We provide a robust method that is orthogonal to MS-based methods and can also be used for cross-validation.

Comparative study on chemical composition of ancient glass based on machine learning and deep learning

In this paper, a BP neural network was established based on the deep learning framework to determine the category of ancient glass under the influence of weathering.Compared with random forest and support vector machine, the accuracy reached 100%, in which random forest and BP neural network predicted the same results. The convolutional neural network model was proposed to solve the classification problem, and the applicability of the convolutional algorithm in one-dimensional data was verified.Then, through the visualization of the chemical composition correlation of different categories of glass cultural relics, it is concluded that high-potassium glass has a strong correlation with silica, and lead-barium glass has a strong correlation with lead oxide.For the difference of chemical composition correlation between different types of glass cultural relics, the conclusion that silica in high-potassium glass is negatively correlated with other components was obtained by constructing knowledge map analysis.

Composition analysis and identification of glass products based on Pearson correlation analysis

Ancient glass objects record the cultural exchanges between East and West along the Silk Road, but they have been subjected to varying degrees of weathering over time. First, to investigate the relationship between surface weathering and glass type, decoration and color of glass artifacts, this paper investigated the correlation using Kappa consistency test and judged the difference using chi-square test, and found that there was significant correlation and difference between surface weathering and glass type. For the statistical pattern between the presence or absence of weathering on the surface and the chemical composition content, the content of each chemical composition was compared between weathered and unweathered on the surface by visualizing its chemical composition content. Secondly, to analyze the classification pattern of high potassium and lead-barium glass, it is subclassed. In this paper, the chemical constituents relevant to the classification were first selected by Pearson correlation analysis, followed by subclassification of the two types of glass artifacts by establishing a K-Means clustering subclassification model based on the elbow method to determine the number of cluster centroids. Thirdly, in order to identify the unknown types of glass artifacts, this paper establishes a random forest regression algorithm for glass type identification model and derives the results by prediction. Finally, different categories of glass artifacts are analyzed to distinguish glass from four specific categories in terms of decoration, type, color and surface weathering, and the differences in chemical composition correlation relationships between different categories are obtained by comparing the chemical composition correlation tables of different categories.

K-means++ clustering-based composition analysis and identification model for glass products

Ancient glass is susceptible to weathering by environmental influences, causing changes in its compositional proportions and thus affecting the correct judgment of its elemental categories. In this paper, the study on the analysis and identification of ancient glass composition applies gray correlation analysis, K-means++ cluster analysis and principal component analysis to analyze the relationship between weathering on the surface of cultural relics and their glass types, ornamentation, and color; the content pattern of chemical composition with and without weathering on the surface of cultural relics is statistically analyzed by glass type, and the content of its chemical composition before weathering is predicted based on the weathering point detection data. Will be high potassium glass, and lead barium glass classification laws for analysis; appropriate chemical composition of each category for subcategory division, giving the division method and division results and analysis of its reasonableness and sensitivity. Analysis of the chemical composition of unknown categories of artifacts, identification of the types, and the sensitivity of the results are analyzed. The correlations between the chemical composition of glass artifacts of different categories are analyzed and the differences in their chemical composition correlations are compared.

Phlegcarines A-C, three Lycopodium alkaloids from Phlegmariurus carinatus (Desv. ex Poir.) Ching

Three undescribed Lycopodium alkaloids, phlegcarines A-C, along with nine known alkaloids, were isolated from the aerial parts of a gardening clubmoss Phlegmariurus carinatus (Desv. ex Poir.) Ching. Phlegcarine A is an undescribed Lycopodium alkaloid possessing an unprecedented 5/9/6/6 fused-tetracyclic ring system consisting of an oxa-cyclononanone, a piperidine, a methylcyclohaxane and an oxazolidine. Phlegcarine B is the first N-chloromethyl piperidinium Lycopodium alkaloid of (+)-lycoflexine. The semi-synthesis of phlegcarine B was investigated from (+)-fawcettimine. Phlegcarine C, an undescribed epimer of 12-epilycodoline, is a rare lycopodine-type alkaloid with β-oriented H-4. Transformation of phlegcarine C and lycodoline to 12-epilycopodine N-oxide via keto-enol tautomerization was investigated using m-CPBA. The structural assignments were established through comprehensive spectroscopic techniques and chemical correlations. Phlegcarines A-C were assayed for their anti-acetylcholinesterase activity, but none of them exhibited biological activity more potent than that of huperzine A.

Chemical composition correlation between high potassium glass and lead-barium glass

The Silk Road was a channel for cultural exchange between China and the West in ancient times, of which glass was a valuable physical evidence of early trade exchanges. Early glass was often made into bead-shaped ornaments in the West Asian and Egyptian regions into our country, and our ancient glass was made locally after absorbing its technology, so it was similar in appearance to foreign glass products, but the chemical composition was not the same. As glass is highly susceptible to weathering by the burial environment, during the weathering process, a large number of internal elements are exchanged with environmental elements, resulting in a change in its composition ratio, which affects the correct judgment of its category. According to the proportion of chemical composition of glass artifacts, it was split into high potassium glass data and lead-barium glass data, and the Pearson correlation coefficient was studied by using matlab software for high potassium glass data and lead-barium glass data respectively, so as to analyze the correlation between each chemical composition.

From Relative to Absolute Stereochemistry of Secondary Metabolites: Applications in Plant Chemistry

Structural elucidation of specialized metabolites or natural plant products, especially the stereochemical features of chiral bioactive metabolites, is the most important stage for all investigations in pharmacognosy and phytochemistry. Numerous methods have been established to solve the absolute configuration of natural products, including direct methods such as X-ray diffraction, chiroptical spectroscopy, stereo-controlled partial or total organic synthesis, and chemical correlation by simple organic reactions for derivatization, as well as indirect methods using a standard chiral compound or a derivatizing agent with known absolute configuration, for example, nuclear magnetic resonance by utilization of anisotropic effects of chiral agents. Once the relative configuration of a natural product is resolved, the absolute stereochemistry can be determined with the assistance of chiroptical spectroscopies supported by quantum mechanical-NMR prediction of chemical shifts, scalar coupling constants and simulation of optical rotatory dispersion, in addition to electronic and vibrational circular dichroism spectra. This review summarizes the most practical methods employed in the assignment of absolute stereochemistry of natural plant products with selected examples focused on multichiral center bioactive small molecules from the mega-diverse Brazilian and Mexican flora.

Water Chemical Characteristics and Safety Assessment of Irrigation Water in the Northern Part of Hulunbeier City, Grassland Area in Eastern China

Hulun Buir Grassland is a world-famous natural pasture. The Chenbalhu Banner coalfield, the hinterland of the grassland, is located on the west slope of the Great Khingan Mountains and on the north bank of the Hailar River in China. The proven geological reserves of coal are 17 billion tons. Hulun Buir Grassland plays a role in the ecological barrier, regional coal industry, power transmission from west to east and power transmission from north to south. The proportion of local groundwater in irrigation, domestic and industrial production water sources is about 86%. The large-scale exploitation of coal resources and the continuous emergence of large unit and coal-fired power plants have consumed a large amount of local water resources, resulting in the decrease of the local groundwater level and changing the natural flow field of groundwater. This paper studies the background hydrochemical values and evaluates the irrigatibility of the whole Chenbaerhu Banner coalfield, and studies the impact of coal industry chains such as mining areas and coal chemical plants on the hydrochemistry characteristics of groundwater. The above two studies provide important guiding values for guiding local economic structure planning, groundwater resources exploitation and ecological governance. The study found that Na+ and HCO3− in the groundwater in the study area occupy a dominant position. Referring to the comparison of the lowest values of three types of water standards in the Quality Standards for Groundwater (GB/T14848-2017), the amount of NH4+, Na+ and NO2− exceeding the standard is close to more than 30%. The main chemical types of river water in the study area are HCO3− Na and HCO3− Ca·Na, the main chemical types of surface water are HCO3− Na and HCO3− Na·Ca, and the main chemical type of confined water is HCO3−Na. The formation of hydrochemical types is mainly affected by the dissolution, filtration and evaporation of rocks, specifically the dissolution and filtration of sodium and calcium salts. The chemical correlation analysis of groundwater shows that there are abnormal values at many points in the study area. Further combining with the horizontal comparison of surface human activities in the study area, it shows that the influence scope of coal mine production and coal chemical plants on groundwater is extremely limited. The local groundwater is mainly polluted by a large quantity of local cattle and sheep manure, industrial and domestic sewage pollution and farmland fertilizer.

Multiple acquisitions in a single scan: exhausting abundant 1H polarization at fast MAS

Proton-detected solid-state NMR spectroscopy is emerging as a unique tool for atomic characterization of organic solids due to the boost of resolution and sensitivity afforded by the combined use of high magnetic field and ultrafast magic angle spinning (MAS). Here, we proposed a new set of proton-detected solid-state NMR sequences that hybrid multi-dimensional 1H–1H homonuclear chemical shift correlation (HOMCOR) and two-dimensional 1H–13C heteronuclear chemical shift correlation (HETCOR) sequences into a single experiment, enabling the simultaneous acquisition of multidimensional HOMCOR and HETCOR spectra and thus significant time savings. Based on the core idea of exhausting 1H polarization in each transient scan, we firstly demonstrated that 3D 1H multiple-quantum (MQ) HOMCOR sequence can be combined with 2D HETCOR sequence into a single experiment, leading to the simultaneous acquisition of a 3D 1H MQ HOMCOR and a 2D 1H–13C HETCOR spectrum. Besides, we also showed that 2D 1H/1H double-quantum/single-quantum (DQ/SQ) and single-quantum/single-quantum (SQ/SQ) HOMCOR sequence can be simultaneously combined with HETCOR sequence either, and thus three spectra can be simultaneously obtained from one experiment, including 2D 1H DQ/SQ, 2D 1H SQ/SQ and 2D 1H–13C HETCOR spectra. Since there is only one recycle delay in each experiment, experimental time is substantially reduced compared to separate acquisition of each multi-dimensional solid-state NMR spectrum. Furthermore, those new sequences can be implemented on any standard solid-state spectrometer with only one receiver. Thus, we foresee that these approaches can be valuable for the study of a broad range of molecular systems, including polymers, pharmaceuticals, covalent-organic frameworks (COF) and so on.

Learning the relationship between nanoscale chemical patterning and hydrophobicity

The hydrophobicity of proteins and similar surfaces, which display chemical heterogeneity at the nanoscale, drives countless aqueous interactions and assemblies. However, predicting how surface chemical patterning influences hydrophobicity remains a challenge. Here, we address this challenge by using molecular simulations and machine learning to characterize and model the hydrophobicity of a diverse library of patterned surfaces, spanning a wide range of sizes, shapes, and chemical compositions. We find that simple models, based only on polar content, are inaccurate, whereas complex neural network models are accurate but challenging to interpret. However, by systematically incorporating chemical correlations between surface groups into our models, we are able to construct a series of minimal models of hydrophobicity, which are both accurate and interpretable. Our models highlight that the number of proximal polar groups is a key determinant of hydrophobicity and that polar neighbors enhance hydrophobicity. Although our minimal models are trained on particular patch size and shape, their interpretability enables us to generalize them to rectangular patches of all shapes and sizes. We also demonstrate how our models can be used to predict hot-spot locations with the largest marginal contributions to hydrophobicity and to design chemical patterns that have a fixed polar content but vary widely in their hydrophobicity. Our data-driven models and the principles they furnish for modulating hydrophobicity could facilitate the design of novel materials and engineered proteins with stronger interactions or enhanced solubilities.

Short- and medium range order in GeTe4-Ag glasses

Short- and medium range order glasses of GeTe4-Ag approximate composition have been studied by neutron diffraction, X-ray diffraction and extended X-ray absorption fine structure spectroscopy. Chemical correlations have been determined by fitting multiple datasets simultaneously with the reverse Monte Carlo simulation technique. It has been found that Ge atoms remain basically fourfold coordinated by Te while Te atoms have mostly two Ge/Te neighbours. The topology of the GeTe4 host network does not change upon adding Ag. Similarly to binary Ge-Te glasses, neighbouring GeTe4 tetrahedra are predominantly in corner sharing configuration in all investigated GeTe4-Ag compositions. Ag atoms bind mostly to Te and the average total coordination number of Ag does not change significantly with increasing Ag content.

Evolution of the Piauí Laterite, Brazil: Mineralogical, Geochemical and Geomicrobiological Mechanisms for Cobalt and Nickel Enrichment

The Piauí laterite (NE Brazil) was initially evaluated for Ni but also contains economic concentrations of Co. Our investigations aimed to characterise the Co enrichment within the deposit; by understanding the mineralogy we can better design mineral processing to target Co recovery. The laterite is heterogeneous on the mineralogical and lithological scale differing from the classic schematic profiles of nickel laterites, and while there is a clear transition from saprolite to more ferruginous units, the deposit also contains lateral and vertical variations that are associated with both the original intrusive complex and also the nature of fluid flow, redox cycling and fluctuating groundwater tables. The deposit is well described by the following six mineralogical and geochemical units: SAPFE, a clay bearing ferruginous saprolite; SAPSILFE, a silica dominated ferruginous saprolite; SAPMG, a green magnesium rich chlorite dominated saprolite; SAPAL, a white-green high aluminium, low magnesium saprolite; saprock, a serpentine and chlorite dominated saprolite and the serpentinite protolith. Not all of these units are ‘ore bearing’. Ni is concentrated in a range of nickeliferous phyllosilicates (0.1–25 wt%) including serpentines, talc and pimelite, goethite (up to 9 wt%), magnetite (2.8–14 wt%) and Mn oxy-hydroxides (0.35–19 wt%). Lower levels of Ni are present in ilmenites, chromites, chlorite and distinct small horizons of nickeliferous silica (up to 3 wt% Ni). With respect to Co, the only significant chemical correlation is with Mn, and Mn oxy-hydroxides contain up to 14 wt% Co. Cobalt is only present in goethite when Mn is also present, and these goethite grains contain an average of 0.19 wt% Co (up to a maximum of 0.65 wt%). The other main Co bearing minerals are magnetite (0.41–1.89 wt%), chlorite (up to 0.45 wt%) and ilmenite (up to 0.35 wt%). Chemically there are three types of Mn oxy-hydroxide, asbolane, asbolane-lithiophorite intermediates and romanechite. Spatially resolved X-ray absorption spectroscopy analysis suggests that the Co is present primarily as octahedrally bound Co3+ substituted directly into the MnO6 layers of the asbolane-lithiophorite intermediates. However significant levels of Co2+ are evident within the asbolane-lithiophorite intermediates, structurally bound along with Ni in the interlayer between successive MnO6 layers. The laterite microbial community contains prokaryotes and few fungi, with the highest abundance and diversity closest to ground level. Microorganisms capable of metal redox cycling were identified to be present, but microcosm experiments of different horizons within the deposit demonstrated that stimulated biogeochemical cycling did not contribute to Co mobilisation. Correlations between Co and Mn are likely to be a relic of parent rock weathering rather than due to biogeochemical processes; a conclusion that agrees well with the mineralogical associations.

Copper(I) iodide complex with 4-pyridinecarboxaldehyde ligand: Synthesis, spectroscopic characterisation, AIM and NCI analysis combined with molecular docking and antibacterial activity studies

In this article, we synthesized a [CuI(4-pyridinecarboxaldehyde)4] complex characterized by CHN analyses, FT-IR, UV-Vis, and DFT. The spectroscopic characteristics and biological activities of the synthesized complex were investigated using quantum mechanical methods using combined experimental and computational approaches. The orbital NBO and topological AIM approaches were used to investigate intermolecular interactions. According to the second-order perturbation energy analysis, the majority of the E(2) stabilization energies of of LP(N) → LP∗(Cu) are higher than those of LP(I) → LP∗(Cu), implying that the nitrogen atom in the complex is the main contributor to coordination. In addition, the biological activities of the title complex were investigated by using molecular docking analysis. In this investigation, the title Cu (I) complex was the most active molecule, with the maximum antibacterial activity against S. aureus and S. epidermidis infections that should be further clinically investigated due to its effective anti and anti-quorum sensing properties. The title complex showed good antiquorum-sensing activity when tested against C. violaceum ATCC 12472. Furthermore, in-silico molecular docking investigations corroborated the chemical activity correlations. The Cu (I) combination has a maximum dock score for some of the active chemicals.

Two New Abietane Diterpenes From the Stems of Clerodendrum trichotomum Thunb

Two new abietane diterpenoids (4 S, 5 S, 10 S)-12-( β-D-glucopyranosyl)oxy-11-hydroxyabieta-8,11,13-triene-19-oic acid β-D-glucopyranosyl-(1→6)- β-D-glucopyranosyl ester (1) and (3 S, 5 S, 10 S, 15 S)-3 β-[ β-D-glucopyranosyl-(1→6)- β-D-glucopyranosyl]oxy-12-( β-D-glucopyranosyl)oxyabieta-8,11,13-triene-11,16-diol (2), along with 5 known terpene glycosides (3–7) were isolated from the n-butanol extract of the stems of Clerodendrum trichotomum Thunb. The structures of the new compounds were determined by analysis of spectroscopic data, chemical correlations, and electronic circular dichroism calculations. Besides, all compounds were evaluated for cytotoxic activities against cultured K562, MCF-7, A549, and HepG2 cell lines. None of them showed good antitumor activities.

Solid‐state NMR investigation of fast sodium ion‐conducting glass–ceramics: The system Na3+3x−yRE1−xPySi3−yO9 (RE = Sc, Y)

AbstractGlasses and glass–ceramics of composition Na3+3x−yRE1−xPySi3−yO9 were synthesized using RE = Sc and Y, x = 0.4, and y = 0.0 and 0.3 to obtain multiple‐phase glass–ceramics containing the highly conducting Na5RESi4O12 (N5) phase. In addition, the two model compounds Na5ScSi4O12 and Na5InSi4O12 were synthesized. Samples were characterized at two distinct annealing stages using X‐ray powder diffraction, electrical conductivity measurements, and multinuclear solid‐state magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy. The N5 phase is dominantly formed for Sc‐containing glass–ceramics (both with y = 0.0 and 0.3) at crystallization temperatures above 900°C. For the other glass–ceramics, the crystallized phases were dominantly Na3RESi2O7 (N3), RE = Sc and Y, and Na9YSi6O18 (N9) phases. 29Si MAS‐NMR peak assignments were done with the aid of 29Si{45Sc} rotational echo adiabatic passage double resonance (REAPDOR) experiments. 29Si and 23Na MAS‐NMR spectra reveal complex phase compositions and local environment distributions, which could be largely assigned based on known semiempirical chemical shift correlations with average Si–O and Na–O bond distances. 31P MAS and 31P{45Sc} REAPDOR NMR results suggest the presence of orthophosphate groups, arguing against the literature model of isostructural substitution of silicon by phosphorus in the N5 phase.