Tailoring ammonia capture in MOFs and COFs: A multi-scale and machine learning comprehensive investigation of functional group modification

Our study aims to examine the impact of ligand functionalization on the ammonia adsorption properties of MOFs and COFs, by combining multi-scale calculations with machine learning techniques. Density Functional Theory calculations were performed to investigate the interactions between ammonia (NH3) and a comprehensive set of 48 strategically chosen functional groups. In all of the cases, it is observed that functionalized rings exhibit a stronger interaction with ammonia molecule compared to unfunctionalized benzene, while -O2Mg demonstrates the highest interaction energy with ammonia (15 times stronger than the bare benzene). The trend obtained from the thorough DFT screening is verified via Grand Canonical Monte-Carlo calculations by employing interatomic potentials derived from quantum chemical calculations. Isosteric heat of adsorption plots provide a comprehensive elucidation of the adsorption process, and important insights can be taken for studies in fine-tuning materials for ammonia adsorption. Furthermore, a proof of concept machine learning (ML) analysis is conducted, which demonstrates that ML can accurately predict NH3 binding energies despite the limited amount of data. The findings derived from our multi-scale methodology indicate that the functionalization strategy can be utilized to guide synthesis towards MOFs, COFs, or other porous materials for enhanced NH3 adsorption capacity.

Gas adsorption meets deep learning: voxelizing the potential energy surface of metal-organic frameworks

Intrinsic properties of metal-organic frameworks (MOFs), such as their ultra porosity and high surface area, deem them promising solutions for problems involving gas adsorption. Nevertheless, due to their combinatorial nature, a huge number of structures is feasible which renders cumbersome the selection of the best candidates with traditional techniques. Recently, machine learning approaches have emerged as efficient tools to deal with this challenge, by allowing researchers to rapidly screen large databases of MOFs via predictive models. The performance of the latter is tightly tied to the mathematical representation of a material, thus necessitating the use of informative descriptors. In this work, a generalized framework to predict gaseous adsorption properties is presented, using as one and only descriptor the capstone of chemical information: the potential energy surface (PES). In order to be machine understandable, the PES is voxelized and subsequently a 3D convolutional neural network (CNN) is exploited to process this 3D energy image. As a proof of concept, the proposed pipeline is applied on predicting [Formula: see text] uptake in MOFs. The resulting model outperforms a conventional model built with geometric descriptors and requires two orders of magnitude less training data to reach a given level of performance. Moreover, the transferability of the approach to different host-guest systems is demonstrated, examining [Formula: see text] uptake in COFs. The generic character of the proposed methodology, inherited from the PES, renders it applicable to fields other than reticular chemistry.

Effects of Fluorinated Functionalization of Linker on Quercetin Encapsulation, Release and Hela Cell Cytotoxicity of Cu-Based MOFs as Smart pH-Stimuli Nanocarriers

Controlled delivery of target molecules is required in many medical and chemical applications. For such purposes, metal-organic frameworks (MOFs), which possess desirable features such as high porosity, large surface area, and adjustable functionalities, hold great potential as drug carriers. Herein, Quercetin (QU), as an anticancer drug, was loaded on Cu2 (BDC)2 (DABCO) and Cu2 (F4 BDC)2 )DABCO) MOFs (BDC=1,4-benzenedicarboxylate and DABCO=1,4-diazabicyclo[2.2.2]octane). As these Cu-MOFs have a high surface area, an appropriate pore size, and biocompatible ingredients, they can be utilized to deliver QU. The loading efficiency of QU in these MOFs was 49.5 % and 41.3 %, respectively. The drug-loaded compounds displayed sustained drug release over 15 days, remarkably high drug loading capacities and pH-controlled release behavior. The prepared nanostructures were characterized by different characterization technics including FT-IR, PXRD, ZP, TEM, FE-SEM, UV-vis, and BET. In addition, MTT assays were carried out on the HEK-293 and HeLa cell lines to investigate cytotoxicity. Cellular apoptosis analysis was performed to investigate the cell death mechanisms. Grand Canonical Monte Carlo simulations were conducted to analyze the interactions between MOFs and QU. Moreover, the stability of MOFs was also investigated during and after the drug release process. Ultimately, kinetic models of drug release were evaluated.

Polyimides as Promising Cathodes for Metal-Organic Batteries: A Comparison between Divalent (Ca2+, Mg2+) and Monovalent (Li+, Na+) Cations

Ca- and Mg-based batteries represent a more sustainable alternative to Li-ion batteries. However, multivalent cation technologies suffer from poor cation mass transport. In addition, the development of positive electrodes enabling reversible charge storage currently represents one of the major challenges. Organic positive electrodes, in addition to being the most sustainable and potentially low-cost candidates, compared with their inorganic counterparts, currently present the best electrochemical performances in Ca and Mg cells. Unfortunately, organic positive electrodes suffer from relatively low capacity retention upon cycling, the origin of which is not yet fully understood. Here, 1,4,5,8-naphthalenetetracarboxylic dianhydride-derived polyimide was tested in Li, Na, Mg, and Ca cells for the sake of comparison in terms of redox potential, gravimetric capacities, capacity retention, and rate capability. The redox mechanisms were also investigated by means of operando IR experiments, and a parameter affecting most figures of merit has been identified: the presence of contact ion-pairs in the electrolyte.

Multiscale Theoretical Study of Sulfur Dioxide (SO2) Adsorption in Metal–Organic Frameworks

In the present work, we used DFT in order to study the interaction of SO2 with 41 strategically functionalized benzenes that can be incorporated in MOF linkers. The interaction energy of phenyl phosphonic acid (–PO3H2) with SO2 was determined to be the strongest (−10.1 kcal/mol), which is about 2.5 times greater than the binding energy with unfunctionalized benzene (−4.1 kcal/mol). To better understand the nature of SO2 interactions with functionalized benzenes, electron redistribution density maps of the relevant complexes with SO2 were created. In addition, three of the top performing functional groups were selected (–PO3H2, –CNH2NOH, –OSO3H) to modify the IRMOF-8 organic linker and calculate its SO2 adsorption capacity with Grand Canonical Monte Carlo (GCMC) simulations. Our results showed a great increase in the absolute volumetric uptake at low pressures, indicating that the suggested functionalization technique can be used to enhance the SO2 uptake capability not only in MOFs but in a variety of porous materials.

Water-Stable etb-MOFs for Methane and Carbon Dioxide Storage

We utilized the etb platform of MOFs for the synthesis of two new water-stable compounds based on amide functionalized trigonal tritopic organic linkers H₃BTBTB (L1), H₃BTCTB (L2) and Al³⁺ metal ions, namely, Al(L1) and Al(L2). The mesoporous Al(L1) material exhibits an impressive methane (CH₄) uptake at high pressures and ambient temperature. The corresponding values of 192 cm³ (STP) cm^-3, 0.254 g g^-1 at 100 bar, and 298 K are among the highest reported for mesoporous MOFs, while the gravimetric and volumetric working capacities (between 80 bar and 5 bar) can be well compared to the best MOFs for CH₄ storage. Furthermore, at 298 K and 50 bar, Al(L1) adsorbs 50 wt % (304 cm³ (STP) cm^-3) CO₂, values among the best recorded for CO₂ storage using porous materials. To gain insight into the mechanism accounting for the resultant enhanced CH₄ storage capacity, theoretical calculations were performed, revealing the presence of strong CH₄ adsorption sites near the amide groups. Our work demonstrates that amide functionalized mesoporous etb-MOFs can be valuable for the design of versatile coordination compounds with CH₄ and CO₂ storage capacities comparable to ultra-high surface area microporous MOFs.

Data-driven prediction of in situ CO2 foam strength for enhanced oil recovery and carbon sequestration

Carbon dioxide foam injection is a promising enhanced oil recovery (EOR) method, being at the same time an efficient carbon storage technology. The strength of CO₂ foam under reservoir conditions plays a crucial role in predicting the EOR and sequestration performance, yet, controlling the strength of the foam is challenging due to the complex physics of foams and their sensitivity to operational conditions and reservoir parameters. Data-driven approaches for complex fluids such as foams can be an alternative method to the time-consuming experimental and conventional modeling techniques, which often fail to accurately describe the effect of all important related parameters. In this study, machine learning (ML) models were constructed to predict the oil-free CO₂ foam apparent viscosity in the bulk phase and sandstone formations. Based on previous experimental data on various operational and reservoir conditions, predictive models were developed by employing six ML algorithms. Among the applied algorithms, neural network algorithms provided the most precise predictions for bulk and porous media. The established models were then used to compute the critical foam quality under different conditions and determine the maximum apparent foam viscosity, effectively controlling CO₂ mobility to co-optimize EOR and CO₂ sequestration.

Surface Modification Strategy for Enhanced NO2 Capture in Metal-Organic Frameworks

The interaction strength of nitrogen dioxide (NO₂) with a set of 43 functionalized benzene molecules was investigated by performing density functional theory (DFT) calculations. The functional groups under study were strategically selected as potential modifications of the organic linker of existing metal–organic frameworks (MOFs) in order to enhance their uptake of NO₂ molecules. Among the functional groups considered, the highest interaction energy with NO₂ (5.4 kcal/mol) was found for phenyl hydrogen sulfate (-OSO₃H) at the RI-DSD-BLYP/def2-TZVPP level of theory—an interaction almost three times larger than the corresponding binding energy for non-functionalized benzene (2.0 kcal/mol). The groups with the strongest NO₂ interactions (-OSO₃H, -PO₃H₂, -OPO₃H₂) were selected for functionalizing the linker of IRMOF-8 and investigating the trend in their NO₂ uptake capacities with grand canonical Monte Carlo (GCMC) simulations at ambient temperature for a wide pressure range. The predicted isotherms show a profound enhancement of the NO₂ uptake with the introduction of the strongly-binding functional groups in the framework, rendering them promising modification candidates for improving the NO₂ uptake performance not only in MOFs but also in various other porous materials.

A Universal Machine Learning Algorithm for Large-Scale Screening of Materials

Application of machine learning (ML) methods for the determination of the gas adsorption capacities of nanomaterials, such as metal-organic frameworks (MOF), has been extensively investigated over the past few years as a computationally efficient alternative to time-consuming and computationally demanding molecular simulations. Depending on the thermodynamic conditions and the adsorbed gas, ML has been found to provide very accurate results. In this work, we go one step further and we introduce chemical intuition in our descriptors by using the "type" of the atoms in the structure, instead of the previously used building blocks, to account for the chemical character of the MOF. ML predictions for the methane and carbon dioxide adsorption capacities of several tens of thousands of hypothetical MOFs are evaluated at various thermodynamic conditions using the random forest algorithm. For all cases examined, the use of atom types instead of building blocks leads to significantly more accurate predictions, while the number of MOFs needed for the training of the ML algorithm in order to achieve a specified accuracy can be reduced by an order of magnitude. More importantly, since practically there are an unlimited number of building blocks that materials can be made of but a limited number of atom types, the proposed approach is more general and can be considered as universal. The universality and transferability was proved by predicting the adsorption properties of a completely different family of materials after the training of the ML algorithm in MOFs.

Review of computer simulations on anti-cancer drug delivery in MOFs

Metal–organic frameworks (MOFs) have been recently used as potential nanocarrier platforms in biomedical applications such as drug storage and delivery, due to their low toxicity, biodegradability, high internal surface area, widely tunable composition, high payloads and controlled drug release.

Reticular Chemistry and the Discovery of a New Family of Rare Earth (4, 8)-Connected Metal-Organic Frameworks with csq Topology Based on RE4(μ3-O)2(COO)8 Clusters

In recent years, the design and discovery of new metal-organic framework (MOF) platforms with distinct structural features and tunable chemical composition has remarkably enhanced by applying reticular chemistry rules and the molecular building block (MBB) approach. We targeted the synthesis of new rare earth (RE)-MOF platforms based on a rectangular-shaped 4-c linker, acting as a rigid organic MBB. Accordingly, we designed and synthesized the organic ligand 1,2,4,5-tetrakis(4-carboxyphenyl)-3,6-dimethyl-benzene (H₄L), in which the two methyl groups attached to the central phenyl ring lock the four peripheral carboxyphenyl groups to an orthogonal/vertical position. We report here a new family of RE-MOFs featuring the novel inorganic building unit, RE₄(μ₃-O)₂ (RE: Y³⁺, Tb³⁺, Dy³⁺, Ho³⁺, Er³⁺, and Yb³⁺), with planar D_2h symmetry. The rigid 4-c linker, H₄L, directs the in situ assembly of the unique 8-c RE₄(μ₃-O)₂(COO)₈ cluster, resulting in the formation of the first (4, 8)-c RE-MOFs with csq topology, RE-csq-MOF-1. The structures of the yttrium (Y-csq-MOF-1) and holmium (Ho-csq-MOF-1) analogues were determined by single-crystal X-ray diffraction analysis. Y-csq-MOF-1 was successfully activated and tested for Xe/Kr separation. The results show that Y-csq-MOF-1 has high isosteric heat of adsorption for Xe (33.8 kJ mol^-1), with high Xe/Kr selectivity (IAST 12.1, Henry 12.9) and good Xe uptake (1.94 mmol g^-1 at 298 K and 1 bar), placing this MOF among the top-performing adsorbents for Xe/Kr separation.

Directed assembly of a high surface area 2D metal–organic framework displaying the augmented “kagomé dual” (kgd-a) layered topology with high H2and CO2uptake

A high surface area layered MOF withkgd-atopology, based on a nanosized and highly aromatic hexagonal linker, shows high H₂and CO₂uptake.

Multiscale simulations reveal IRMOF-74-III as a potent drug carrier for gemcitabine delivery

Kotzabasaki et al. use a multiscale computational approach to investigate the microscopic behaviour of gemcitabine stored in (OH)-IRMOF-74-III. The principles can be exploited for nano-carrier screening purposes prior to experimental investigation.

Insight on the formation of chitosan nanoparticles through ionotropic gelation with tripolyphosphate

This work reports details pertaining to the formation of chitosan nanoparticles that we prepare by the ionic gelation method. The molecular interactions of the ionic cross-linking of chitosan with tripolyphosphate have been investigated and elucidated by means of all-electron density functional theory. Solvent effects have been taken into account using implicit models. We have identified primary-interaction ionic cross-linking configurations that we define as H-link, T-link, and M-link, and we have quantified the corresponding interaction energies. H-links, which display high interaction energies and are also spatially broadly accessible, are the most probable cross-linking configurations. At close range, proton transfer has been identified, with maximum interaction energies ranging from 12.3 up to 68.3 kcal/mol depending on the protonation of the tripolyphosphate polyanion and the relative coordination of chitosan with tripolyphosphate. On the basis of our results for the linking types (interaction energies and torsion bias), we propose a simple mechanism for their impact on the chitosan/TPP nanoparticle formation process. We introduce the β ratio, which is derived from the commonly used α ratio but is more fundamental since it additionally takes into account structural details of the oligomers.

Multi-scale theoretical investigation of hydrogen storage in covalent organic frameworks

The quest for efficient hydrogen storage materials has been the limiting step towards the commercialization of hydrogen as an energy carrier and has attracted a lot of attention from the scientific community. Sophisticated multi-scale theoretical techniques have been considered as a valuable tool for the prediction of materials storage properties. Such techniques have also been used for the investigation of hydrogen storage in a novel category of porous materials known as Covalent Organic Frameworks (COFs). These framework materials are consisted of light elements and are characterized by exceptional physicochemical properties such as large surface areas and pore volumes. Combinations of ab initio, Molecular Dynamics (MD) and Grand Canonical Monte-Carlo (GCMC) calculations have been performed to investigate the hydrogen adsorption in these ultra-light materials. The purpose of the present review is to summarize the theoretical hydrogen storage studies that have been published after the discovery of COFs. Experimental and theoretical studies have proven that COFs have comparable or better hydrogen storage abilities than other competitive materials such as MOF. The key factors that can lead to the improvement of the hydrogen storage properties of COFs are highlighted, accompanied with some recently presented theoretical multi-scale studies concerning these factors.

Enhanced hydrogen storage by spillover on metal-doped carbon foam: an experimental and computational study

A lightweight, oxygen-rich carbon foam was prepared and doped with Pd/Hg alloy nanoparticles. The composite revealed high H2 sorption capacity (5 wt%) at room temperature and moderate pressure (2 MPa). The results were explained on the basis of the H2 spillover mechanism using Density Functional Theory.

Designing 3D COFs with enhanced hydrogen storage capacity

Hydrogen storage properties have been studied on newly designed three-dimensional covalent-organic framework (3D-COF). The design of these materials was based on the ctn network of the ultralow density COF-102. The structures were optimized by multiscale techniques and the optimized structures were checked for their storage capacities by grand canonical Monte Carlo simulations. Our simulations demonstrate that the gravimetric uptake of one of these new COFs can overpass the value of 25 wt % in 77 K and reach the Department of Energy's target of 6 wt % in room temperature, classifying them between the top hydrogen storage materials.

The effect of structural and energetic parameters of MOFs and COFs towards the improvement of their hydrogen storage properties

Open-framework materials have been proposed as potential materials for hydrogen storage. Metal-organic framework (MOF) and covalent-organic framework (COF) materials are under extensive study to discover their storage abilities. In particular the IRMOF family of materials have been considered as ideal to study the effect of different factors that affect the hydrogen storage capacity. In this paper, we analyse the effect of different factors such as surface area, pore volume and the interaction of hydrogen with the molecular framework on the hydrogen uptake of such materials. Through this analysis we propose guidelines to enhance hydrogen storage capacity of already synthesized materials and recommend advanced materials for this application.

Pillared graphene: a new 3-D network nanostructure for enhanced hydrogen storage

A multiscale theoretical approach was used to investigate hydrogen storage in a novel three-dimensional carbon nanostructure. This novel nanoporous material has by design tunable pore sizes and surface areas. Its interaction with hydrogen was studied thoroughly via ab initio and grand canonical Monte Carlo calculations. Our results show that, if this material is doped with lithium cations, it can store up to 41 g H2/L under ambient conditions, almost reaching the DOE volumetric requirement for mobile applications.

Improving hydrogen storage capacity of MOF by functionalization of the organic linker with lithium atoms

A combination of quantum and classical calculations have been performed in order to investigate hydrogen storage in metal-organic frameworks (MOFs) modified by lithium alkoxide groups. Ab initio calculations showed that the interaction energies between the hydrogen molecules and this functional group are up to three times larger compared with unmodified MOF. This trend was verified by grand canonical Monte Carlo (GCMC) simulations in various thermodynamic conditions. The gravimetric capacity of the Li-modified MOFs reached the value of 10 wt % at 77 K and 100 bar, while our results are very promising at room temperature, too, with 4.5 wt %.

Assessing the density functional theory in the hydrogen storage problem

A variety of high and low level ab-initio calculations have been performed to calculate hydrogen's physisorption binding energy on carbon nanotube's walls. This study focuses on the performance of several functionals on treating the H2-carbon nanotube interaction within the Density Functional Theory. Our results show that the behavior of the exchange functional in the low density region plays an important role in describing this weak van der Waals type of interaction. By comparing the binding energy values obtained on each theoretical level and interpreting the results in terms of %wt percentages of hydrogen storage using the Langmuir isotherms, we proposed possible ways to treat computationally the hydrogen storage problem within the DFT.

Carbon nanoscrolls: a promising material for hydrogen storage

A multiscale theoretical approach was used for the investigation of hydrogen storage in the recently synthesized carbon nanoscrolls. First, ab initio calculations at the density functional level of theory (DFT) were performed in order to (a) calculate the binding energy of H2 molecules at the walls of nanoscrolls and (b) fit the parameters of the interatomic potential used in Monte Carlo simulations. Second, classical Monte Carlo simulations were performed for estimating the H2 storage capacity of "experimental size" nanoscrolls containing thousands of atoms. Our results show that pure carbon nanoscrolls cannot accumulate hydrogen because the interlayer distance is too small. However, an opening of the spiral structure to approximately 7 A followed by alkali doping can make them very promising materials for hydrogen storage application, reaching 3 wt % at ambient temperature and pressure.

Effect of curvature and chirality for hydrogen storage in single-walled carbon nanotubes: A Combined ab initio and Monte Carlo investigation

Combined ab initio and grand canonical Monte Carlo simulations have been performed to investigate the dependence of hydrogen storage in single-walled carbon nanotubes (SWCNTs) on both tube curvature and chirality. The ab initio calculations at the density functional level of theory can provide useful information about the nature of hydrogen adsorption in SWCNT selected sites and the binding under different curvatures and chiralities of the tube walls. Further to this, the grand canonical Monte Carlo atomistic simulation technique can model large-scale nanotube systems with different curvature and chiralities and reproduce their storage capacity by calculating the weight percentage of the adsorbed material (gravimetric density) under thermodynamic conditions of interest. The author's results have shown that with both computational techniques, the nanotube's curvature plays an important role in the storage process while the chirality of the tube plays none.

A multi scale theoretical study of Li+ interaction with carbon nanotubes

We investigated the effect of the curvature in lithium storage at single-walled carbon nanotubes, with both ab-initio and Molecular Dynamics simulations. Our results show that the carbon rings of nanotubes develop strong cation-pi- interactions with Li ion. These interactions result in positioning the alkali metal cation on top of a phenyl group. By using different types of carbon nanotubes it was revealed that the interaction is not affected by the type or the curvature of the nanotubes. Molecular Dynamics simulations of lithium intercalated nanotube bundles pointed at the fact that the cations remain attached to the nanotubes even at room temperature, with a maximum Li to C ratio of 1:2.1.

SiC nanotubes: A novel material for hydrogen storage

A multiscale theoretical approach is used for the investigation of hydrogen storage in silicon-carbon nanotubes (SiCNTs). First, ab initio calculations at the density functional level of theory (DFT) showed an increase of 20% in the binding energy of H2 in SiCNTs compared with pure carbon nanotubes (CNTs). This is explained by the alternative charges that exist in the SiCNT walls. Second, classical Monte Carlo simulation of nanotube bundles showed an even larger increase of the storage capacity in SiCNTs, especially in low temperature and high-pressure conditions. Our results verify in both theoretical levels that SiCNTs seem to be more suitable materials for hydrogen storage than pure CNTs.

Glycine Interaction with Carbon Nanotubes: An ab Initio Study

The interaction of the glycine radical on the side walls of both armchair and zigzag single walled carbon nanotubes is investigated by density functional theory. It is found that the interaction potential of the N-centered glycine radical with the tubes has a minimum of 16.9 (armchair) and 20.2 (zigzag) kcal/mol with respect to the dissociation products. In contrast, the C-centered radical, which is 22.7 kcal/mol lower in energy than the N-centered radical, does not form stable complexes with both types of carbon nanotubes.

Magnetic enhancement and magnetic reduction in binary clusters of transition metal atoms

Electronic and magnetic properties of small binary clusters containing one or two transition metal atoms are investigated using ab initio calculations with a view to explain the experimentally observed magnetic enhancement/reduction in these systems. As the present investigations do not rely on spin-orbit effects, our results reveal the enhancement or reduction in the magnetic moment to depend on two main factors; namely geometry and, most importantly, the d-band filling. The results can be used as a guide in the experimental synthesis of high density magnetic grains.

Ene hydroperoxidation of isobutenylarenes within dye-exchanged zeolite Na-Y: control of site selectivity by cation-arene interactions

The site selectivity in the singlet oxygen ene reaction of several deuterium-labeled isobutenylarenes depends on the position and the electronic nature of the aryl substitutents. For example, 1-(4-trifluoromethylphenyl)-2-methylpropene gives 82% twin selectivity whereas the isomeric 1-(2-trifluoromethylphenyl)-2-methylpropene gives 68% twix selectivity. If photooxygenation of these CF(3)-substituted compounds is carried out in solution, the opposite selectivity trends are found. On the basis of DFT calculations, these results are rationalized in terms of oxygen-cation and cation-arene interactions.

Stereochemistry in the Reaction of 4-Methyl-1,2,4-triazoline-3,5-dione (MTAD) with β,β-Dimethyl-p-methoxystyrene. Are Open Biradicals the Reaction Intermediates?

The reaction of 4-methyl-1,2,4-triazoline-3,5-dione (MTAD) with beta,beta-dimethyl-p-methoxystyrene (1) in chloroform affords four adducts: the ene, two stereoisomeric [4 + 2]/ene diadducts, and a minor product that is probably the double Diels-Alder diadduct. In methanol, only one regioisomeric methoxy adduct is formed. The stereochemistry of the reaction was examined by specific labeling of the anti methyl group of 1 as CD(3). In chloroform, the ene adduct is formed with >97% synselectivity, while the [4 + 2]/ene diadducts are formed with 20% loss of stereochemistry at the methyl groups. In methanol, the methoxy adducts are formed with almost complete loss of stereochemistry. A mechanism involving open biradicals is inconsistent with the experimental results. It is likely that the reaction proceeds through the formation of an aziridinium imide and an open zwitterionic intermediate. The aziridinium imide leads to the formation of the ene adduct. The open zwitterion, which has sufficient lifetime to rotate around the C-C bond, leads to the formation of a [4 + 2] cycloadduct, which reacts with a second molecule of MTAD in an ene-type mode to afford two stereoisomeric [4 + 2]/ene diadducts. In methanol, solvent captures the zwitterionic intermediate and forms the methoxy adduct. The relative distribution of the products in chloroform depends on the reaction temperature. Lower temperatures favor the ene reaction (entropically favorable), whereas at higher temperatures the [4 + 2]/ene diadducts become the major products.

Cis- and trans-N-benzyl-octahydrobenzo[g]quinolines. Adrenergic and dopaminergic activity studies

In vitro assays on a series of cis- and trans-octahydrobenzo[g]quinolines indicated an unusual trend of affinities at the dopaminergic receptors and alpha adrenoceptors. The trans N-benzyl analogues exhibited affinity at the alpha2 as well as the D1-like receptors whereas their N-unsubstituted congeners showed a distinct preference for the alpha2 adrenoceptor. Enhanced activity for the alpha2 receptors was also exhibited by the cis N-benzylated isomers. These observations are interpreted by theoretical calculations.