Insights into Structure Direction of Microporous Aluminophosphates: Competition between Organic Molecules and Water

A combination of experimental characterisation techniques and computational modelling has allowed us to gain insight into the molecular features governing structure direction in the synthesis of microporous aluminophosphates. The occlusion of three different structure‐directing agents (SDAs), triethylamine (TEA), benzylpyrrolidine (BP) and (S )‐(?)‐N‐benzylpyrrolidine‐2‐methanol (BPM), within the AFI structure during its crystallisation, together with the simultaneous incorporation of water, has been experimentally measured. We found a higher incorporation of organic molecules in the structure obtained with BPM, while a higher water (and lower organic) content is found for the ones obtained with TEA and BP as SDAs. The computational study provides a thermodynamic explanation for the observed behaviour in terms of the relative stabilisation energy of the SDAs and water molecules within the AFI framework compared with when they are in aqueous solution, and demonstrates that a competition for preferential occupation exists between water and organic SDAs, which is a function of the interaction with the inorganic framework. The lower interaction of TEA and BP molecules with the AFI structure promotes the simultaneous incorporation of water molecules in the 12‐membered‐ring (MR) channel, to increase the host–guest interaction energy and thus the thermodynamic stability. The presence of strongly interacting methanol groups in the BPM molecules leads to the incorporation of only organic molecules within the 12‐MR channels. Our results demonstrate the essential role that water molecules play in the stabilisation of hydrophilic microporous aluminophosphates; a minimum amount of organic SDA is, however, essential for a templating role of the microporous architecture.     

Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations

The calculations of NMR properties of molecules using quantum chemical methods have deeply impacted several branches of organic chemistry. They are particularly important in structural or stereochemical assignments of organic compounds, with implications in total synthesis, stereoselective reactions, and natural products chemistry. In studying the evolution of the strategies developed to support (or reject) a structural proposal, it becomes clear that the most effective and accurate ones involve sophisticated procedures to correlate experimental and computational data. Owing to their relatively high mathematical complexity, such calculations (CP3, DP4, ANN‐PRA) are often carried out using additional computational resources provided by the authors (such as applets or Excel files). This Minireview will cover the state‐of‐the‐art of these toolboxes in the assignment of organic molecules, including mathematical definitions, updates, and discussion of relevant examples.     

Predicting Inclusion Behaviour and Framework Structures in Organic Crystals

We have used well‐established computational methods to generate and explore the crystal structure landscapes of four organic molecules of well‐known inclusion behaviour. Using these methods, we are able to generate both close‐packed crystal structures and high‐energy open frameworks containing voids of molecular dimensions. Some of these high‐energy open frameworks correspond to real structures observed experimentally when the appropriate guest molecules are present during crystallisation. We propose a combination of crystal structure prediction methodologies with structure rankings based on relative lattice energy and solvent‐accessible volume as a way of selecting likely inclusion frameworks completely ab initio. This methodology can be used as part of a rational strategy in the design of inclusion compounds, and also for the anticipation of inclusion behaviour in organic molecules.     

Theoretical Characterization of Charge Transport in One‐Dimensional Collinear Arrays of Organic Conjugated Molecules

A great deal of interest has recently focused on host–guest systems consisting of one‐dimensional collinear arrays of conjugated molecules encapsulated in the channels of organic or inorganic matrices. Such architectures allow for controlled charge and energy migration processes between the interacting guest molecules and are thus attractive in the field of organic electronics. In this context, we characterize here at a quantum‐chemical level the molecular parameters governing charge transport in the hopping regime in 1D arrays built with different types of molecules. We investigate the influence of several parameters (such as the symmetry of the molecule, the presence of terminal substituents, and the molecular size) and define on that basis the molecular features required to maximize the charge carrier mobility within the channels. In particular, we demonstrate that a strong localization of the molecular orbitals in push–pull compounds is generally detrimental to the charge transport properties.     

Structural Changes in 2‐Diarylthiophene‐Substituted Starburst Compounds upon Charging: A Theoretical and Spectroelectrochemical Study

The role of charging in structural changes of 2‐diarylaminothiophene‐substituted starburst compounds is clarified by combining theoretical and spectroelectrochemical studies. A systematic and comparative theoretical calculation based on density functional theory and semiempirical Austin Model 1 (AM1) calculations is performed on the neutral and charged states of four model tris(5‐diarylamino‐5‐thienyl)‐terminated starburst compounds with a central triphenylamine and 1,3,5‐triphenylbenzene moiety. Our results indicate that the charging of molecules leads to structural changes by quinoid‐type components mostly on the dendrimers terminated by phenothiazinyl fragments. Based on the optimal geometries, the spectroscopic properties were calculated using the semiempirical Zerner’s intermediate neglect overlap method. The presented theoretical results and the spin electron distributions of charged states and their spectra are supported by the spectroelectrochemical observations caused by the different electron localization within the studied molecules after charging. The satisfactory agreement between theoretical electronic transitions and experimental values indicates that a rational design of tunable molecular layers in organic devices based on the starburst compounds described is possible.     

An efficient fragment-based approach for predicting the ground-state energies and structures of large molecules

An efficient fragment-based approach for predicting the ground-state energies and structures of large molecules at the Hartree-Fock (HF) and post-HF levels is described. The physical foundation of this approach is attributed to the "quantum locality" of the electron correlation energy and the HF total energy, which is revealed by a new energy decomposition analysis of the HF total energy proposed in this work. This approach is based on the molecular fractionation with conjugated caps (MFCC) scheme (Zhang, D. W.; Zhang, J. Z. H. J. Chem. Phys. 2003, 119, 3599), by which a macromolecule is partitioned into various capped fragments and conjugated caps formed by two adjacent caps. We find that the MFCC scheme, if corrected by the interaction between non-neighboring fragments, can be used to predict the total energy of large molecules only from energy calculations on a series of small subsystems. The approach, named as energy-corrected MFCC (EC-MFCC), computationally achieves linear scaling with the molecular size. Our test calculations on a broad range of medium- and large molecules demonstrate that this approach is able to reproduce the conventional HF and second-order Moller-Plesset perturbation theory (MP2) energies within a few millihartree in most cases. With the EC-MFCC optimization algorithm described in this work, we have obtained the optimized structures of long oligomers of trans-polyacetylene and BN nanotubes with up to about 400 atoms, which are beyond the reach of traditional computational methods. In addition, the EC-MFCC approach is also applied to estimate the heats of formation for a series of organic compounds. This approach provides an appealing approach alternative to the traditional additivity rules based on either bond or group contributions for the estimation of thermochemical properties.     

Accuracy and efficiency of electronic energies from systematic molecular fragmentation

A systematic method for approximating the ab initio electronic energy of molecules from the energies of molecular fragments is tested on a large sample of typical organic molecular structures. The detailed methods, including some additional refinements for molecular rings and long range interactions, are described. The accuracy and computational efficiency of the systematic hierarchy of methods are reported.     

Linear‐scaling self‐consistent field calculations based on divide‐and‐conquer method using resolution‐of‐identity approximation on graphical processing units

Graphical processing units (GPUs) are emerging in computational chemistry to include Hartree?Fock (HF) methods and electron‐correlation theories. However, ab initio calculations of large molecules face technical difficulties such as slow memory access between central processing unit and GPU and other shortfalls of GPU memory. The divide‐and‐conquer (DC) method, which is a linear‐scaling scheme that divides a total system into several fragments, could avoid these bottlenecks by separately solving local equations in individual fragments. In addition, the resolution‐of‐the‐identity (RI) approximation enables an effective reduction in computational cost with respect to the GPU memory. The present study implemented the DC‐RI‐HF code on GPUs using math libraries, which guarantee compatibility with future development of the GPU architecture. Numerical applications confirmed that the present code using GPUs significantly accelerated the HF calculations while maintaining accuracy. © 2014 Wiley Periodicals, Inc.     

Desorption Dynamics,Internal Energies,and Imaging of Organic Molecules from Surfaces with Laser Desorption and Vacuum Ultraviolet (VUV) Photoionization

There is enormous interest in visualizing the chemical composition of organic material that comprises our world. A convenient method to obtain molecular information with high spatial resolution is imaging mass spectrometry. However, the internal energy deposited within molecules upon transfer to the gas phase from a surface can lead to increased fragmentation and to complications in analysis of mass spectra. Here it is shown that in laser desorption with postionization by tunable vacuum ultraviolet (VUV) radiation, the internal energy gained during laser desorption leads to minimal fragmentation of DNA bases. The internal temperature of laser‐desorbed triacontane molecules approaches 670 K, whereas the internal temperature of thymine is 800 K. A synchrotron‐based VUV postionization technique for determining translational temperatures reveals that biomolecules have translational temperatures in the range of 216–346 K. The observed low translational temperatures as well as their decrease with increased desorption laser power is explained by collisional cooling. An example of imaging mass spectrometry on an organic polymer by using laser‐desorption VUV postionization shows 5 μm feature details while using a 30 μm laser spot size and 7 ns pulse duration. Applications of laser‐desorption postionization to the analysis of cellulose, lignin, and humic acids are briefly discussed.     

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from‐scratch construction of molecules is not limited to compounds in pre‐existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X‐ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug‐like compounds (generic libraries), and (3) application to a challenging protein‐protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.     

Expedited analysis of DFT outputs: Introducing moanalyzer

MOAnalyzer, a Matlab‐based program, has been developed to facilitate the analysis of density functional theory output files from ORCA. The program allows the user to define fragments within a molecule and then provides information on the contribution of each fragment to the molecular orbitals based on the Loewdin population analysis. Correlations to spectroscopy (X‐ray absorption and X‐ray emission) are also obtained, and the resulting information can be visualized in tables or MO diagrams. © 2012 Wiley Periodicals, Inc.     

Rapid anharmonic vibrational corrections derived from partial Hessian analysis

Vibrational analysis within a partial Hessian framework can successfully describe the vibrational properties of a variety of systems where the vibrational modes of interest are localized within a specific region of the system. We have developed a new approach to calculating anharmonic frequencies based on vibrational frequencies and normal modes obtained from a partial Hessian analysis using second-order vibrational perturbation theory and the transition optimized shifted Hermite method. This allows anharmonic frequencies for vibrational modes that are spatially localized to be determined at a significantly reduced computational cost. Several molecular systems are examined in order to demonstrate the effectiveness of this method including organic molecules adsorbed on the Si(100)-2×1 surface, model peptides in solution, and the C-H stretching region of polycyclic aromatic hydrocarbons. Overall, for a range of systems, anharmonic frequencies calculated using the partial Hessian approach are found to be in close agreement with the results obtained using full anharmonic calculations while providing a significant reduction in computational cost.     

A General Strategy to Enhance Donor‐Acceptor Molecules Using Solvent‐Excluding Substituents

While organic donor‐acceptor (D‐A) molecules are widely employed in multiple areas, the application of more D‐A molecules could be limited because of an inherent polarity sensitivity that inhibits photochemical processes. Presented here is a facile chemical modification to attenuate solvent‐dependent mechanisms of excited‐state quenching through addition of a β‐carbonyl‐based polar substituent. The results reveal a mechanism wherein the β‐carbonyl substituent creates a structural buffer between the donor and the surrounding solvent. Through computational and experimental analyses, it is demonstrated that the β‐carbonyl simultaneously attenuates two distinct solvent‐dependent quenching mechanisms. Using the β‐carbonyl substituent, improvements in the photophysical properties of commonly used D‐A fluorophores and their enhanced performance in biological imaging are shown.     

Automated and efficient quantum chemical determination and energetic ranking of molecular protonation sites

We present an automated quantum chemical protocol for the determination of preferred protonation sites in organic and organometallic molecules containing up to a few hundred atoms. It is based on the Foster–Boys orbital localization method, whereby we automatically identify lone pairs and π orbitals as possible protonation sites. The method becomes efficient in conjunction with the robust and fast GFN‐xTB semiempirical method proposed recently (Grimme et al ., J. Chem. Theory Comput . 2017, 13 , 1989). The protonated isomers that are found within a few seconds to minutes of computational wall‐time on a standard desktop computer are then energetically refined using density functional theory (DFT), where we use a high‐level double‐hybrid reference method to benchmark GFN‐xTB and low‐cost DFT approaches. The proposed DFT/GFN‐xTB/LMO composite protocol is generally applicable to almost arbitrary molecules including transition metal complexes. Importantly it is found that even in electronically complicated cases, the GFN‐xTB optimized protomer structures are reasonable and can safely be used in single‐point DFT calculations. Corrections from energy to free energy mostly have a small effect on computed protomer populations. The resulting protomer equilibrium is valuable, for example, in the context of electrospray ionization mass spectrometry where it may help identify the ionized species and assist the interpretation of the experiment. © 2017 Wiley Periodicals, Inc.     

Infrared Fingerprint Engineering: A Molecular‐Design Approach to Long‐Wave Infrared Transparency with Polymeric Materials

Optical technologies in the long‐wave infrared (LWIR) spectrum (7–14 μm) offer important advantages for high‐resolution thermal imaging in near or complete darkness. The use of polymeric transmissive materials for IR imaging offers numerous cost and processing advantages but suffers from inferior optical properties in the LWIR spectrum. A major challenge in the design of LWIR‐transparent organic materials is that nearly all organic molecules absorb in this spectral window which lies within the so‐called IR‐fingerprint region. We report on a new molecular‐design approach to prepare high refractive index polymers with enhanced LWIR transparency. Computational methods were used to accelerate the design of novel molecules and polymers. Using this approach, we have prepared chalcogenide hybrid inorganic/organic polymers (CHIPs) with enhanced LWIR transparency and thermomechanical properties via inverse vulcanization of elemental sulfur with new organic co‐monomers.     

Bayesian molecular design with a chemical language model

The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes’ law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.     

Cerium‐Based M4L4 Tetrahedra as Molecular Flasks for Selective Reaction Prompting and Luminescent Reaction Tracing

The application of metal–organic polyhedra as “molecular flasks” has precipitated a surge of interest in the reactivity and property of molecules within well‐defined spaces. Inspired by the structures of the natural enzymatic pockets, three metal–organic neutral molecular tetrahedral, Ce‐TTS, Ce‐TNS and Ce‐TBS (H₆TTS: N′,N′′,N′′′‐nitrilotris‐4,4′,4′′‐(2‐hydroxybenzylidene)‐benzohydrazide; H₆TNS: N′,N′′,N′′′‐nitrilotris‐6,6′,6′′‐(2‐hydroxybenzylidene)‐2‐naphthohydrazide; H₆TBS: 1,3,5‐ phenyltris ‐4,4′,4′′‐(2‐hydroxybenzylidene)benzohydrazide), which exhibit different size of the edges and cavities, were achieved through self‐assembly by incorporating robust amide‐containing tridentate chelating sites into the fragments of the ligands. They acted as molecular flasks to prompt the cyanosilylation of aldehydes with excellent selectivity towards the substrates size. The amide groups worked as trigger sites and catalytic driven forces to achieve efficient guest interactions, enforcing the substrates proximity within the cavity. Experiments on catalysts with the different cavity radii and substrates with the different molecular size demonstrated that the catalytic performance exhibited enzymatical catalytic mechanism and occurred in the molecular flask. These amides were also able to amplify guest‐bonding events into the measurable outputs for the detection of concentration variations of the substrates, providing the possibility for metal–organic hosts to work as smart molecular flasks for the luminescent tracing of catalytic reactions.     

Lattice sum calculations for 1/rp interactions via multipole expansions and Euler summation

A method is developed here for doing multiple calculations of lattice sums when the lattice structure is kept fixed, while the molecular orientations or the molecules within the unit cells are altered. The approach involves a two‐step process. In the first step, a multipole expansion is factored in such a way as to separate the geometry from the multipole moments. This factorization produces a formula for generating geometry constants that uniquely define the lattice structure. A direct calculation of these geometry constants, for all but the very smallest of crystals, is computationally impractical. In the second step, an Euler summation method is introduced that allows for efficient calculation of the geometry constants. This method has a worst case computational complexity of O(( log N)²/N), where N is the number of unit cells. If the lattice sum is rapidly converging, then the computational complexity can be significantly less than N. Once the geometry constants have been calculated, calculating a lattice sum for a given molecule becomes computationally very fast. Millions of different molecular orientations or molecules can quickly be evaluated for the given lattice structure. © 2000 John Wiley & Sons, Inc. J Comput Chem 22: 208–215, 2001