A dynamical system approach to relaxation in glass-forming liquids

The "classical" thermodynamic and statistical mechanical theories of Gibbs and Boltzmann are both predicated on axiomatic assumptions whose applicability is hard to ascertain. Theoretical objections and an increasing number of observed deviations from these theories have led to sustained efforts to develop an improved mathematical and physical foundation for them, and the search for appropriate extensions that are generally applicable to condensed materials at low temperatures (T) and high material densities where the assumptions of these theories start to become particularly questionable. These theoretical efforts have largely focused on minimal models of condensed material systems, such as the Fermi-Ulam-Pasta-Tsingou model, and other simplified models of condensed materials that are amenable to numerical and analytic treatments and that can serve to illuminate essential features of relaxation processes in condensed materials under conditions approaching integrable dynamics where clear departures from classical thermodynamics and dynamics can be generally expected. These studies indicate an apparently general multi-step relaxation process, corresponding to an initial "fast" relaxation process (termed the fast β-relaxation in the context of cooled liquids), followed by a longer "equipartition time", namely, the α-relaxation time τα in the context of cooled liquids. This relaxation timescale can be enormously longer than the fast β-relaxation time τβ so that τα is the primary parameter governing the rate at which the material comes into equilibrium, and thus is a natural focus of theoretical attention. Since the dynamics of these simplified dynamical systems, originally intended as simplified models of real crystalline materials exhibiting anharmonic interactions, greatly resemble the observed relaxation dynamics of both heated crystals and cooled liquids, we adapt this dynamical system approach to the practical matter of estimating relaxation times in both cooled liquids and crystals at elevated temperatures, which we identify as weakly non-integrable dynamical systems.

Surface Engineering of the Mechanical Properties of Molecular Crystals via an Atomistic Model for Computing the Facet Stress Response of Solids

Dynamic molecular crystals are an emerging class of crystalline materials that can respond to mechanical stress by dissipating internal strain in a number of ways. Given the serendipitous nature of the discovery of such crystals, progress in the field requires advances in computational methods for the accurate and high-throughput computation of the nanomechanical properties of crystals on specific facets which are exposed to mechanical stress. Here, we develop and apply a new atomistic model for computing the surface elastic moduli of crystals on any set of facets of interest using dispersion-corrected density functional theory (DFT-D) methods. The model was benchmarked against a total of 24 reported nanoindentation measurements from a diverse set of molecular crystals and was found to be generally reliable. Using only the experimental crystal structure of the dietary supplement, L-aspartic acid, the model was subsequently applied under blind test conditions, to correctly predict the growth morphology, facet and nanomechanical properties of L-aspartic acid to within the accuracy of the measured elastic stiffness of the crystal, 24.53±0.56 GPa. This work paves the way for the computational design and experimental realization of other functional molecular crystals with tailor-made mechanical properties.

Expanding Color Control of Anodically Coloring Electrochromes Based on Electron-Rich 1,4-Dihydropyrrolo[3,2-b]pyrroles

Anodically coloring electrochromes have received attention in recent years as high-contrast alternatives to cathodically coloring electrochromes due to their superior optical contrast during electrochemical switching. While current systems represent significant progress for organic electrochromics, it is necessary to expand the structural diversity of these materials while simultaneously reducing the hazards associated with synthetic protocols. With these considerations in mind, a family of 1,4-dihydropyrrolo[3,2-b]pyrrole (DHPP) chromophores with varying functionalities along the 2,5-axis was envisioned to accomplish these goals. After predicting different absorbance traits as oxidized molecules with time-dependent density functional theory, DHPP chromophores with varying peripheral functionalities were synthesized in a single aerobic synthetic step via an iron-catalyzed multicomponent reaction and characterized as high-contrast chromophores. In solution, the DHPP chromophores absorb in the ultraviolet region of the electromagnetic spectrum, resulting in color-neutral L*a*b* color coordinates of ∼100, 0, 0. Upon chemical oxidation, each molecule transitions to absorb at various points across the visible spectrum based on the extent of electron-donating ability and can display five distinct colors. Importantly, the chromophores are redox-active and display switching capabilities with an applied electrochemical potential. In conjunction with building fundamental insights into molecular design of DHPP chromophores, the results and synthetic simplicity of DHPPs make them compelling materials for color-controlled high-contrast electrochromes.

Self-energy correction and numerical simulation for efficient lead-free double perovskite solar cells

Inorganic double perovskites have garnered significant attention due to their desirable characteristics, such as low-toxicity, stability and long charge-carrier lifetimes. However, most double perovskites, especially Cs2AgBiBr6, have wide bandgaps, which limits power conversion efficiencies. In this work, through the first principles method corrected by self-energy, we investigate the mechanical, electric and optical properties of Cs2B'B''Br6 (B' = Ag, Au, Cu; B'' = Bi, Al, Sb, In). Based on performance screening, three kinds of materials with good toughness, high carrier mobility and wide visible-light absorption (around 105 cm-1) are obtained, which are compared with Cs2AgBiBr6. Meanwhile, we use a SACPS-1D simulation to design lead-free double perovskites with excellent properties suitable for photovoltaic solar cell devices, which are made into a planar perovskite heterojunction. Ultimately, the optimal structure is determined to be FTO/WS2/Cs2CuBiBr6/spiro-OMeTAD/Ag, which achieves a power conversion efficiency of 14.08%, surpassing the conventional structure efficiency of 6.1%. It provides valuable guidance for the structure design of a lead-free double perovskite device and offers new insights into the development of optoelectronic devices for solar energy utilization.

Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials

The reliability of organic molecular crystal structure prediction has improved tremendously in recent years. Crystal structure predictions for small, mostly rigid molecules are quickly becoming routine. Structure predictions for larger, highly flexible molecules are more challenging, but their crystal structures can also now be predicted with increasing rates of success. These advances are ushering in a new era where crystal structure prediction drives the experimental discovery of new solid forms. After briefly discussing the computational methods that enable successful crystal structure prediction, this perspective presents case studies from the literature that demonstrate how state-of-the-art crystal structure prediction can transform how scientists approach problems involving the organic solid state. Applications to pharmaceuticals, porous organic materials, photomechanical crystals, organic semi-conductors, and nuclear magnetic resonance crystallography are included. Finally, efforts to improve our understanding of which predicted crystal structures can actually be produced experimentally and other outstanding challenges are discussed.

Recent Advances in Nanomechanical Measurements and Their Application for Pharmaceutical Crystals

Mechanical behavior of pharmaceutical crystals directly impacts the formulation development and manufacturing of drug products. The understanding of crystal structure-mechanical behavior of pharmaceutical and molecular crystals has recently gained substantial attention among pharmaceutical and materials scientists with the advent of advanced nanomechanical testing instruments like nanoindentation. For the past few decades, instrumented nanoindentation was a popular technique for measuring the mechanical properties of thin films and small-length scale materials. More recently it is being implemented to investigate the mechanical properties of pharmaceutical crystals. Integration of correlative microscopy techniques and environmental control opened the door for advanced structure-property correlation under processing conditions. Preventing the degradation of active pharmaceutical ingredients from external factors such as humidity, temperature, or pressure is important during processing. This review deals with the recent developments in the synchronized nanomechanical measurements of pharmaceutical crystals toward the fast and effective development of high-quality pharmaceutical drug products. This review also summarizes some recent reports to intensify how one can design and control the nanomechanical properties of pharmaceutical solids. Measurement challenges and the scope for studying nanomechanical properties of pharmaceutical crystals using nanoindentation as a function of crystal structure and in turn to develop fundamental knowledge in the structure-property relationship with the implications for drug manufacturing and development are discussed in this review. This review further highlights recently developed capabilities in nanoindentation, for example, variable temperature nanoindentation testing, in situ imaging of the indented volume, and nanoindentation coupled Raman spectroscopy that can offer new quantitative details on nanomechanical behavior of crystals and will play a decisive role in the development of coherent theories for nanomechanical study of pharmaceutical crystal.

Equation of state predictions for ScF3 and CaZrF6 with neural network-driven molecular dynamics

In silico property prediction based on density functional theory (DFT) is increasingly performed for crystalline materials. Whether quantitative agreement with experiment can be achieved with current methods is often an unresolved question, and may require detailed examination of physical effects such as electron correlation, reciprocal space sampling, phonon anharmonicity, and nuclear quantum effects (NQE), among others. In this work, we attempt first-principles equation of state prediction for the crystalline materials ScF3 and CaZrF6, which are known to exhibit negative thermal expansion (NTE) over a broad temperature range. We develop neural network (NN) potentials for both ScF3 and CaZrF6 trained to extensive DFT data, and conduct direct molecular dynamics prediction of the equation(s) of state over a broad temperature/pressure range. The NN potentials serve as surrogates of the DFT Hamiltonian with enhanced computational efficiency allowing for simulations with larger supercells and inclusion of NQE utilizing path integral approaches. The conclusion of the study is mixed: while some equation of state behavior is predicted in semiquantitative agreement with experiment, the pressure-induced softening phenomenon observed for ScF3 is not captured in our simulations. We show that NQE have a moderate effect on NTE at low temperature but does not significantly contribute to equation of state predictions at increasing temperature. Overall, while the NN potentials are valuable for property prediction of these NTE (and related) materials, we infer that a higher level of electron correlation, beyond the generalized gradient approximation density functional employed here, is necessary for achieving quantitative agreement with experiment.

Regulating photosalient behavior in dynamic metal-organic crystals

Dynamic photoactuating crystals have become a sensation due to their potential applications in developing smart medical devices, molecular machines, artificial muscles, flexible electronics actuators, probes and microrobots. Here we report the synthesis of two iso-structural metal-organic crystals, [Zn(4-ohbz)₂(4-nvp)₂] (1) and [Cd(4-ohbz)₂(4-nvp)₂] (2) {H4-ohbz = 4-hydroxy benzoic acid; 4-nvp = 4-(1-naphthylvinyl)pyridine} which undergo topochemical [2 + 2] cycloaddition under UV irradiation as well as sunlight to generate a dimerized product of discrete metal-complex [Zn(4-ohbz)₂(rctt-4-pncb)] {rctt-4-pncb = 1,3-bis(4'-pyridyl)-2,4-bis(naphthyl)cyclobutane} (1') and one-dimensional coordination polymer (1D CP) [Cd(4-ohbz)₂(rctt-4-pncb)] (2') respectively, in a single-crystal-to-single-crystal (SCSC) process. The Zn-based compound demonstrates photosalient behaviour, wherein crystals show jumping, splitting, rolling, and swelling upon UV irradiation. However, the Cd-based crystals do not show such behaviour maintaining the initial supramolecular packing and space group. Thus the photomechanical behaviour can be induced by choosing a suitable metal ion. The above findings are thoroughly validated by quantitative density functional theory (DFT) calculations which show that the Zn-based crystal shifts towards an orthorhombic structure to resolve the anisotropic UV-induced mechanical strain. Furthermore, the mechano-structure-property relationship has been established by complimentary nanoindentation measurements, which are in-line with the DFT-predicted single crystal values.

Gas-Phase Interaction of CO, CO2, H2S, NH3, NO, NO2, and SO2 with Zn12O12 and Zn24 Atomic Clusters

Atmospheric pollutants pose a high risk to human health, and therefore it is necessary to capture and preferably remove them from ambient air. In this work, we investigate the intermolecular interaction between the pollutants such as CO, CO₂, H₂S, NH₃, NO, NO₂, and SO₂ gases with the Zn₂₄ and Zn₁₂O₁₂ atomic clusters, using the density functional theory (DFT) at the meta-hybrid functional TPSSh and LANl2Dz basis set. The adsorption energy of these gas molecules on the outer surfaces of both types of clusters has been calculated and found to have a negative value, indicating a strong molecular-cluster interaction. The largest adsorption energy has been observed between SO₂ and the Zn₂₄ cluster. In general, the Zn₂₄ cluster appears to be more effective for adsorbing SO₂, NO₂, and NO than Zn₁₂O₁₂, whereas the latter is preferable for the adsorption of CO, CO₂, H₂S, and NH₃. Frontier molecular orbital (FMO) analysis showed that Zn₂₄ exhibits higher stability upon adsorption of NH₃, NO, NO₂, and SO₂, with the adsorption energy falling within the chemisorption range. The Zn₁₂O₁₂ cluster shows a characteristic decrease in band gap upon adsorption of CO, H₂S, NO, and NO₂, suggesting an increase in electrical conductivity. Natural bond orbital (NBO) analysis also suggests the presence of strong intermolecular interactions between atomic clusters and the gases. This interaction was recognized to be strong and noncovalent, as determined by noncovalent interaction (NCI) and quantum theory of atoms in molecules (QTAIM) analyses. Overall, our results suggest that both Zn₂₄ and Zn₁₂O₁₂ clusters are good candidate species for promoting adsorption and, thus, can be employed in different materials and/or systems for enhancing interaction with CO, H₂S, NO, or NO₂.

Electronic and optical properties of C16S8 and C16S4Se4 molecules and crystals

Here we report electronic and optical properties of C16S8 and C16S4Se4 molecules and crystals and resolve previously reported experimental inconsistencies.

Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials

Artificial intelligence (AI) approaches continue to spread in almost every research and technology branch. However, a simple adaptation of AI methods and algorithms successfully exploited in one area to another field may face unexpected problems. Accelerating the discovery of new functional materials in chemical self-driving laboratories has an essential dependence on previous experimenters' experience. Self-driving laboratories help automate and intellectualize processes involved in discovering nanomaterials with required parameters that are difficult to transfer to AI-driven systems straightforwardly. It is not easy to find a suitable design method for self-driving laboratory implementation. In this case, the most appropriate way to implement is by creating and customizing a specific adaptive digital-centric automated laboratory with a data fusion approach that can reproduce a real experimenter's behavior. This paper analyzes the workflow of autonomous experimentation in the self-driving laboratory and distinguishes the core structure of such a laboratory, including sensing technologies. We propose a novel data-centric research strategy and multilevel data flow architecture for self-driving laboratories with the autonomous discovery of new functional nanomaterials.

Integrating Elastic Tensor and PC-SAFT Modeling with Systems-Based Pharma 4.0 Simulation, to Predict Process Operations and Product Specifications of Ternary Nanocrystalline Suspensions

Comminution of BCS II APIs below the 1 μm threshold followed by solidification of the obtained nanosuspensions improves their dissolution properties. The breakage process reveals new crystal faces, thus creating altered crystal habits of improved wettability, facilitated by the adsorption of stabilizing polymers. However, process-induced transformations remain unpredictable, mirroring the current limitations of our atomistic level of understanding. Moreover, conventional equations of estimating dissolution, such as Noyes–Whitney and Nernst–Brunner, are not suitable to quantify the solubility enhancement due to the nanoparticle formation; hence, neither the complex stabilizer contribution nor the adsorption influence on the interfacial tension occurring between the water and APIs is accounted for. For such ternary mixtures, no numeric method exists to correlate the mechanical properties with the interfacial energy, capable of informing the key process parameters and the thermodynamic stability assessment of nanosuspensions. In this work, an elastic tensor analysis was performed to quantify the API stability during process implementation. Moreover, a novel thermodynamic model, described by the stabilizer-coated nanoparticle Gibbs energy anisotropic minimization, was structured to predict the material’s system solubility quantified by the application of PC-SAFT modeling. Comprehensively merging elastic tensor and PC-SAFT analysis into the systems-based Pharma 4.0 algorithm provided a validated, multi-level, built-in method capable of predicting the critical material quality attributes and corresponding key process parameters.

Quantifying Mechanical Properties of Molecular Crystals: A Critical Overview of Experimental Elastic Tensors

This review presents a critical and comprehensive overview of current experimental measurements of complete elastic constant tensors for molecular crystals. For a large fraction of these molecular crystals, detailed comparisons are made with elastic tensors obtained using the corrected small basis set Hartree-Fock method S-HF-3c, and these are shown to be competitive with many of those obtained from more sophisticated density functional theory plus dispersion (DFT-D) approaches. These detailed comparisons between S-HF-3c, experimental and DFT-D computed tensors make use of a novel rotation-invariant spherical harmonic description of the Young's modulus, and identify outliers among sets of independent experimental results. The result is a curated database of experimental elastic tensors for molecular crystals, which we hope will stimulate more extensive use of elastic tensor information-experimental and computational-in studies aimed at correlating mechanical properties of molecular crystals with their underlying crystal structure.

Computational investigation of enhanced properties in functionalized carbon nanotube doped polyvinyl alcohol gel electrolyte systems

Recently, functionalized carbon nanotubes (fCNTs) were shown to increase the mechanical strength, thermal stability, and ionic conductivity in polyvinyl alcohol (PVA) based gel electrolytes (GE) for Zn ion batteries. However, questions remain about the origin of the property enhancement and the interactions between components of GEs. In this work, we employ density functional theory calculations to analyze the interactions between fCNT, PVA, and Zn ions. CNTs with increasing numbers of carboxyl (-COOH) functional groups and PVA chains with varying lengths were studied. We found that increasing the number of -COOH on the CNTs enhanced the adsorption energies (E_ads) of PVA, and E_ads also increased as the number of monomers increased. We then modelled the coordination of a Zn ion in fCNT-PVA complexes. Our results suggest that strong fCNT-PVA interactions contribute to the enhanced mechanical strength, while the enhanced ionic conductivity is partly owing to weak Zn adsorption.