Exploiting Vector Pattern Diversity of Molecular Scaffolds for Cheminformatics Tasks in Drug Discovery.

Chemical diversity is challenging to describe objectively. Despite this, various notions of chemical diversity are used throughout the medicinal chemistry optimization process in drug discovery. In this work, we show the usefulness of considering exploited vectors during different phases of the drug design process to provide a quantitative and objective description of chemical diversity. We have developed a concise and fast approach to enumerate and analyze the exploited vector patterns (EVPs) of molecular compound series, which can then be used in archetypal compound selection tasks, from hit matter identification to hit expansion and lead optimization. We first show that EVPs can be used to assess the progressibility of compounds in a fragment library design exercise. By considering EVPs, we then show how a set of compounds can be prioritized for hit expansion using EVP-based, customizable diversity sampling approaches, reducing the time taken and mitigating human biases. We also show that EVPs are a useful tool to analyze SAR data, offering the chance to uncover correlations between different vectors without predetermining the molecular scaffold structures. The codes used to perform these tasks are presented as easy-to-use Jupyter notebooks, which can be readily adapted for further related tasks.

Correction: Investigation of factors affecting the stability of compounds formed by isovalent substitution in layered oxychalcogenides, leading to identification of Ba3Sc2O5Cu2Se2, Ba3Y2O5Cu2Se2, Ba3Sc2O5Ag2Se2 and Ba3In2O5Ag2Se2.

[This corrects the article DOI: 10.1039/D1TC05051F.].

Accessible chemical space for metal nitride perovskites.

Building on the extensive exploration of metal oxide and metal halide perovskites, metal nitride perovskites represent a largely unexplored class of materials. We report a multi-tier computational screening of this chemical space. From a pool of 3660 ABN3 compositions covering I-VIII, II-VII, III-VI and IV-V oxidation state combinations, 279 are predicted to be chemically feasible. The ground-state structures of the 25 most promising candidate compositions were explored through enumeration over octahedral tilt systems and global optimisation. We predict 12 dynamically and thermodynamically stable nitride perovskite materials, including YMoN3, YWN3, ZrTaN3, and LaMoN3. These feature significant electric polarisation and low predicted switching electric field, showing similarities with metal oxide perovskites and making them attractive for ferroelectric memory devices.

Mechanical properties and peculiarities of molecular crystals.

In the last century, molecular crystals functioned predominantly as a means for determining the molecular structures via X-ray diffraction, albeit as the century came to a close the response of molecular crystals to electric, magnetic, and light fields revealed that the physical properties of molecular crystals were as rich as the diversity of molecules themselves. In this century, the mechanical properties of molecular crystals have continued to enhance our understanding of the colligative responses of weakly bound molecules to internal frustration and applied forces. Here, the authors review the main themes of research that have developed in recent decades, prefaced by an overview of the particular considerations that distinguish molecular crystals from traditional materials such as metals and ceramics. Many molecular crystals will deform themselves as they grow under some conditions. Whether they respond to intrinsic stress or external forces or interactions among the fields of growing crystals remains an open question. Photoreactivity in single crystals has been a leading theme in organic solid-state chemistry; however, the focus of research has been traditionally on reaction stereo- and regio-specificity. However, as light-induced chemistry builds stress in crystals anisotropically, all types of motions can be actuated. The correlation between photochemistry and the responses of single crystals-jumping, twisting, fracturing, delaminating, rocking, and rolling-has become a well-defined field of research in its own right: photomechanics. The advancement of our understanding requires theoretical and high-performance computations. Computational crystallography not only supports interpretations of mechanical responses, but predicts the responses itself. This requires the engagement of classical force-field based molecular dynamics simulations, density functional theory-based approaches, and the use of machine learning to divine patterns to which algorithms can be better suited than people. The integration of mechanics with the transport of electrons and photons is considered for practical applications in flexible organic electronics and photonics. Dynamic crystals that respond rapidly and reversibly to heat and light can function as switches and actuators. Progress in identifying efficient shape-shifting crystals is also discussed. Finally, the importance of mechanical properties to milling and tableting of pharmaceuticals in an industry still dominated by active ingredients composed of small molecule crystals is reviewed. A dearth of data on the strength, hardness, Young's modulus, and fracture toughness of molecular crystals underscores the need for refinement of measurement techniques and conceptual tools. The need for benchmark data is emphasized throughout.

Investigation of factors affecting the stability of compounds formed by isovalent substitution in layered oxychalcogenides, leading to identification of Ba3Sc2O5Cu2Se2, Ba3Y2O5Cu2S2, Ba3Sc2O5Ag2Se2 and Ba3In2O5Ag2Se2.

Four novel compositions containing chalcogenide layers, adopting the Ba3M2O5M'2Ch2 layered structure have been identified: Ba3Sc2O5Cu2Se2, Ba3Y2O5Cu2S2, Ba3Sc2O5Ag2Se2 and Ba3In2O5Ag2Se2. A comprehensive comparison of experimental and computational results providing the crystallographic and electronic structure of the compounds under investigation has been conducted. Materials were synthesised at 800 °C under vacuum using a conventional ceramic synthesis route with combination of binary oxide and chalcogenide precursors. We report their structures determined by Rietveld refinement of X-ray powder diffraction patterns, and band gaps determined from optical measurements, which range from 1.44 eV to 3.04 eV. Through computational modelling we can also present detailed band structures and propose that, based on their predicted transport properties, Ba3Sc2O5Ag2Se2 has potential as a visible light photocatalyst and Ba3Sc2O5Cu2Se2 is of interest as a p-type transparent conductor. These four novel compounds are part of a larger series of sixteen compounds adopting the Ba3M2O5M'2Ch2 structure that we have considered, of which approximately half are stable and can be synthesized. Analysis of the compounds that cannot be synthesized from this group allows us to identify why compounds containing either M = La, or silver sulfide chalcogenide layers, cannot be formed in this structure type.

Not All Aggregates Are Made the Same: Distinct Structures of Solution Aggregates Drastically Modulate Assembly Pathways, Morphology, and Electronic Properties of Conjugated Polymers.

Tuning structures of solution-state aggregation and aggregation-mediated assembly pathways of conjugated polymers is crucial for optimizing their solid-state morphology and charge-transport property. However, it remains challenging to unravel and control the exact structures of solution aggregates, let alone to modulate assembly pathways in a controlled fashion. Herein, aggregate structures of an isoindigo-bithiophene-based polymer (PII-2T) are modulated by tuning selectivity of the solvent toward the side chain versus the backbone, which leads to three distinct assembly pathways: direct crystallization from side-chain-associated amorphous aggregates, chiral liquid crystal (LC)-mediated assembly from semicrystalline aggregates with side-chain and backbone stacking, and random agglomeration from backbone-stacked semicrystalline aggregates. Importantly, it is demonstrated that the amorphous solution aggregates, compared with semicrystalline ones, lead to significantly improved alignment and reduced paracrystalline disorder in the solid state due to direct crystallization during the meniscus-guided coating process. Alignment quantified by the dichroic ratio is enhanced by up to 14-fold, and the charge-carrier mobility increases by a maximum of 20-fold in films printed from amorphous aggregates compared to those from semicrystalline aggregates. This work shows that by tuning the precise structure of solution aggregates, the assembly pathways and the resulting thin-film morphology and device properties can be drastically tuned.

Drastic Modulation of Molecular Packing and Intrinsic Dissolution Rates by Meniscus-Guided Coating of Extremely Confined Pharmaceutical Thin Films.

Nanosizing has emerged as one of the most effective formulation strategies for enhancement of dissolution properties of active pharmaceutical ingredients (APIs). In addition to enhancing the specific area of the dissolving solids, nanosizing can also capture and stabilize the metastable form of the API, which can further enhance the solubility by drastic modulation of surface energies. Herein, we employ meniscus-guided coating to fabricate nanothin films of three APIs that show anticancer properties and are poorly soluble:10-HCPT, SN-38, and amonafide. By modulating the coating speed, we systematically deposited the APIs in films ranging from ∼200 nm thickness to extreme confinement of ∼10 nm (<10 molecular layers). In all three APIs, we observe a general order-to-disorder transition with semicrystalline (10-HCPT and amonafide) or amorphous (SN-38) form of API solids trapped in thin films when the thickness decreases below a critical value of ∼25-30 nm. The existence of a critical thickness highlights the importance of nanoconfinement in tuning molecular packing. In the case of 10-HCPT, we demonstrate that the disordered form of the API occurs largely due to lack of incorporation of water molecules in thinner films below the critical thickness, thereby disrupting the three-dimensional hydrogen-bonded network held by water molecules. We further developed a dissolution model that predicts variation of the intrinsic dissolution rate (IDR) with API film thickness, which also closely matched with experimental results. We achieved drastic improvement in the IDR of ∼240% in 10-HCPT by decreasing film thickness alone. Further leveraging the order-to-disorder transition led to 2570% modulation of the IDR for amonafide. Our work demonstrates, for the first time, opportunities to largely modulate API dissolution by precisely controlling the dimensionality of thin films.

Modulation of π-stacking modes and photophysical properties of an organic semiconductor through isosteric cocrystallization.

We report on the control of π-stacking modes (herringbone vs slipped-stack) and photophysical properties of 9,10-bis((E)-2-(pyridin-4-yl)vinyl)anthracene (BP4VA), an anthracene-based organic semiconductor (OSC), by isosteric cocrystallization (i.e., the replacement of one functional group in a coformer with another of "similar" electronic structure) with 2,4,6-trihalophenols (3X-ph-OH, where X = Cl, Br, and I). Specifically, BP4VA organizes as slipped-stacks when cocrystallized with 3Cl-ph-OH and 3Br-ph-OH, while cocrystallization with 3I-ph-OH results in a herringbone mode. The photoluminescence and molecular frontier orbital energy levels of BP4VA were effectively modulated by the presence of 3X-ph-OH through cocrystallization. We envisage that the cocrystallization of OSCs with minimal changes in cocrystal formers can provide access to convenient structural and property diversification for advanced single-crystal electronics.

Modeling the dielectric constants of crystals using machine learning.

The relative permittivity of a crystal is a fundamental property that links microscopic chemical bonding to macroscopic electromagnetic response. Multiple models, including analytical, numerical, and statistical descriptions, have been made to understand and predict dielectric behavior. Analytical models are often limited to a particular type of compound, whereas machine learning (ML) models often lack interpretability. Here, we combine supervised ML, density functional perturbation theory, and analysis based on game theory to predict and explain the physical trends in optical dielectric constants of crystals. Two ML models, support vector regression and deep neural networks, were trained on a dataset of 1364 dielectric constants. Analysis of Shapley additive explanations of the ML models reveals that they recover correlations described by textbook Clausius-Mossotti and Penn models, which gives confidence in their ability to describe physical behavior, while providing superior predictive power.

Spin-coated fluorinated PbS QD superlattice thin film with high hole mobility.

Motivated by the oleophobic and electron-withdrawing nature of perfluorocarbons, we explore the effect of a trifluoromethyl coating on lead sulfide quantum dots (PbS QDs) in thin film transistor (TFT) geometry. The low surface energy conferred by the oleophobic perfluorocarbons creates QDs packed in a primitive cubic lattice with long range order, as confirmed by grazing incidence small angle X-ray scattering (GISAXS) and transmission electron microscopy (TEM). Hole mobilities as high as 0.085 cm2 V-1 s-1 were measured in the TFTs. No electron transport was observed. This suggests that the electron-withdrawing nature of the trifluoromethyl ligand is eclipsed by the excess holes present in the PbS QDs that likely stem from cation vacancies induced by the thiol group.

A Reversible Structural Phase Transition by Electrochemically-Driven Ion Injection into a Conjugated Polymer.

We find that conjugated polymers can undergo reversible structural phase transitions during electrochemical oxidation and ion injection. We study poly[2,5-bis(thiophenyl)-1,4-bis(2-(2-(2-methoxyethoxy)ethoxy)ethoxy)benzene] (PB2T-TEG), a conjugated polymer with glycolated side chains. Using grazing incidence wide-angle X-ray scattering (GIWAXS), we show that, in contrast to previously known polymers, this polymer switches between two structurally distinct crystalline phases associated with electrochemical oxidation/reduction in an aqueous electrolyte. Importantly, we show that this unique phase change behavior has important physical consequences for ion-polaron pair transport. Notably, using moving front experiments visualized by both optical microscopy and super-resolution photoinduced force microscopy (PiFM), we show that a laterally propagating ion-polaron pair front in PB2T-TEG exhibits non-Fickian transport, retaining a sharp step-edge profile, in stark contrast to the Fickian diffusion more commonly observed in polymers like P3MEEMT. This structural phase transition is reminiscent of those accompanying ion uptake in inorganic materials like LiFePO4. We propose that the engineering of similar properties in future conjugated polymers may enable the realization of new materials with superior performance in electrochemical energy storage or neuromorphic memory applications.

Super- and Ferroelastic Organic Semiconductors for Ultraflexible Single-Crystal Electronics.

Like silicon, single crystals of organic semiconductors are pursued to attain intrinsic charge transport properties. However, they are intolerant to mechanical deformation, impeding their application in flexible electronic devices. Such contradictory properties, namely exceptional molecular ordering and mechanical flexibility, are unified in this work. We found that bis(triisopropylsilylethynyl)pentacene (TIPS-P) crystals can undergo mechanically induced structural transitions to exhibit superelasticity and ferroelasticity. These properties arise from cooperative and correlated molecular displacements and rotations in response to mechanical stress. By utilizing a bending-induced ferroelastic transition of TIPS-P, flexible single-crystal electronic devices were obtained that can tolerate strains (ϵ) of more than 13 % while maintaining the charge carrier mobility of unstrained crystals (µ>0.7 µ0 ). Our work will pave the way for high-performance ultraflexible single-crystal organic electronics for sensors, memories, and robotic applications.

Descriptors for Electron and Hole Charge Carriers in Metal Oxides.

Metal oxides can act as insulators, semiconductors, or metals depending on their chemical composition and crystal structure. Metal oxide semiconductors, which support equilibrium populations of electron and hole charge carriers, have widespread applications including batteries, solar cells, and display technologies. It is often difficult to predict in advance whether these materials will exhibit localized or delocalized charge carriers upon oxidation or reduction. We combine data from first-principles calculations of the electronic structure and dielectric response of 214 metal oxides to predict the energetic driving force for carrier localization and transport. We assess descriptors based on the carrier effective mass, static polaron binding energy, and Fröhlich electron-phonon coupling. Numerical analysis allows us to assign p- and n-type transport of a metal oxide to three classes: (i) band transport with high mobility; (ii) small polaron transport with low mobility; and (iii) intermediate behavior. The results of this classification agree with observations regarding carrier dynamics and lifetimes and are used to predict 10 candidate p-type oxides.

Machine learning for molecular and materials science.

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

Materials discovery by chemical analogy: role of oxidation states in structure prediction.

The likelihood of an element to adopt a specific oxidation state in a solid, given a certain set of neighbours, might often be obvious to a trained chemist. However, encoding this information for use in high-throughput searches presents a significant challenge. We carry out a statistical analysis of the occurrence of oxidation states in 16 735 ordered, inorganic compounds and show that a large number of cations are only likely to exhibit certain oxidation states in combination with particular anions. We use this data to build a model that ascribes probabilities to the formation of hypothetical compounds, given the proposed oxidation states of their constituent species. The model is then used as part of a high-throughput materials design process, which significantly narrows down the vast compositional search space for new ternary metal halide compounds. Finally, we employ a machine learning analysis of existing compounds to suggest likely structures for a small subset of the candidate compositions. We predict two new compounds, MnZnBr4 and YSnF7, that are thermodynamically stable according to density functional theory, as well as four compounds, MnCdBr4, MnRu2Br8, ScZnF5 and ZnCoBr4, which lie within the window of metastability.

Computer-aided design of metal chalcohalide semiconductors: from chemical composition to crystal structure.

The standard paradigm in computational materials science is INPUT: Structure; OUTPUT: Properties, which has yielded many successes but is ill-suited for exploring large areas of chemical and configurational hyperspace. We report a high-throughput screening procedure that uses compositional descriptors to search for new photoactive semiconducting compounds. We show how feeding high-ranking element combinations to structure prediction algorithms can constitute a pragmatic computer-aided materials design approach. Techniques based on structural analogy (data mining of known lattice types) and global searches (direct optimisation using evolutionary algorithms) are combined for translating between chemical composition and crystal structure. The properties of four novel chalcohalides (Sn5S4Cl2, Sn4SF6, Cd5S4Cl2 and Cd4SF6) are predicted, of which two are calculated to have bandgaps in the visible range of the electromagnetic spectrum.

Computational Screening of All Stoichiometric Inorganic Materials.

Forming a four-component compound from the first 103 elements of the periodic table results in more than 1012 combinations. Such a materials space is intractable to high-throughput experiment or first-principle computation. We introduce a framework to address this problem and quantify how many materials can exist. We apply principles of valency and electronegativity to filter chemically implausible compositions, which reduces the inorganic quaternary space to 1010 combinations. We demonstrate that estimates of band gaps and absolute electron energies can be made simply on the basis of the chemical composition and apply this to the search for new semiconducting materials to support the photoelectrochemical splitting of water. We show the applicability to predicting crystal structure by analogy with known compounds, including exploration of the phase space for ternary combinations that form a perovskite lattice. Computer screening reproduces known perovskite materials and predicts the feasibility of thousands more. Given the simplicity of the approach, large-scale searches can be performed on a single workstation.