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Results for “Inorganic Crystallization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Designing Sequence-Defined Peptoids for Biomimetic Control over Inorganic Crystallization

Crystallization defines what the world is all about, ranging from biomineralization in living organisms to various materials in our lives. During these processes, biomineralization set a superexcellent example of the additive-controlled crystallization. However, the high complexity and low stability of peptides and proteins preclude their wide applications in controlling inorganic crystallization beyond the biological systems. Peptoids are one type of sequence-defined biomimetic polymers with a simple structure, high stability, protein-like molecular recognition, and distinctive self-assembly properties. They provide a promising alternative to mimic peptides and proteins for controlling inorganic crystallization and extend its application to predictive materials synthesis. In this review article, we extract the main concepts of peptoid engineering and highlight the recent advances in peptoid-controlled inorganic crystallization. Our focus is to understand the principles of sequence engineering that lead to the predictable physiochemical properties of these substances, which will give insights into other inorganic systems.

36 MATERIALS SCIENCE↗

Programming Amphiphilic Peptoid Oligomers for Hierarchical Assembly and Inorganic Crystallization

Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmarking Coordination Number Prediction Algorithms on Inorganic Crystal Structures

Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning and automatic structural analysis. In this work, we introduce MaterialsCoord, a benchmark suite containing 56 experimentally-derived crystal structures (spanning elements, binaries, and ternary compounds) and their corresponding coordination environments as described in the research literature. We also describe CrystalNN, a novel algorithm for determining near neighbors. We compare CrystalNN against 7 existing near-neighbor algorithms on the MaterialsCoord benchmark, finding CrystalNN to perform similarly to several well-established algorithms. For each algorithm, we also assess computational demand and sensitivity towards small perturbations that mimic thermal motion. Finally, we investigate the similarity between bonding algorithms when applied to the Materials Project database. Finally, we expect that this work will aid the development of coordination prediction algorithms as well as improve structural descriptors for machine learning and other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗

In Situ Thermodynamics and Kinetics of Mixed-Valence Inorganic Crystal Formation

We have found that the established methods to discover and produce earth-abundant iron-containing active layers are very inefficient. The prospective new material iron silicon sulfide, Fe 2 SiS 4 , was previously only synthesized by slow reactions of metallic iron, silicon, and sulfur powders, resulting in poor yield. We found that using an ordered iron-silicon alloy as a feedstock results in a much faster reaction at a lower temperature. We could track this reaction using our unique in-situ X-ray diffractometer, which allows us to heat our encapsulated material up to 1000°C while providing a simultaneous picture of how the atoms in the structure rearrange. We are using this powerful new technique to search for new active layers and optimize their formation by creative use of more complex reagents. Our key accomplishments are mechanisms for improving synthesis, and new materials that result from them. We have demonstrated the utility of high-throughput, DOE-developed infrastructure, such as the Materials Project, to accelerate materials discovery and synthesis. We have pioneered new capabilities of user facilities, such as beamlines 6-BM, 17-BM, and 11-BM at the Advanced Photon Source (APS) and POWGEN and NOMAD at the Spallation Neutron Source.

36 MATERIALS SCIENCE↗

Triel-Defined Helicity in One-Dimensional III–VI–VII van der Waals Crystals

Inorganic extended lattice solids that bear complex helical motifs manifest unusual physical and quantum states that arise due to their noncentrosymmetric or chiral nature. However, the systematic understanding of how elemental composition influences the structure and physical properties in helical inorganic crystals has been precluded by the rarity of these materials and the lack of modular phases that display such motifs. Here, we report the synthesis of AlSeI single crystals, the first aluminum-containing helical crystal in the III-VI-VII 1D van der Waals class. AlSeI completes the experimentally accessible triel series in the helical selene iodides alongside InSeI and GaSeI. Using the Al, Ga, and In triel series in this selene iodide class, we experimentally demonstrate the evolution of the local quasi-tetrahedral building unit geometry, chain packing, helical parameters, and band gaps based primarily on the identity of the triel atom. Our results underscore the chemical modularity of these phases, the broad range of helical parameters, and the spectrum of electronic states from the visible to the ultraviolet range in this emergent class of 1D, exfoliable, and helical extended lattice solids.

Chemical structure↗

CSD 2078665: Experimental Crystal Structure Determination

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Cell Parameters↗

CSD 2312746: Experimental Crystal Structure Determination

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Cell Parameters↗

CSD 2374310: Experimental Crystal Structure Determination

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Cell Parameters↗

Reversible and Irreversible Layer Edge Relaxation in Laser–Radiation–Hardened 2D Organic–Inorganic Perovskite Crystals

The layer edge states or low energy state (LES) in 2D hybrid organic–inorganic perovskites demonstrate a prolonged carrier lifetime for better performance of optoelectronic devices. However, the fundamental understanding of LES in 2D perovskites is still inconclusive. Herein, a photoluminescence (PL) study of LES in 2D Ruddlesden–Popper perovskites is presented with n = 2 and n = 3 from their cleaved cross sections that are more stable than the natural edge. The PL measurements clearly observe reversible, and irreversible surface relaxations (case I and case II) in three laser intensity ranges, further supported by a PL excitation cycle from low to high laser intensity, and vice versa. The PL wavelength of LES is tunable with laser intensity and blueshifts with increasing laser intensity during irreversible surface relaxation process (case I). Fluorescence lifetime imaging (FLIM) shows that the LES has a longer lifetime than the band-edge emission in the sample without a photodegradation, while the BE lifetime becomes relatively longer in the area with a photodegradation. Furthermore, the presented laser tunable LES and the related irreversible relaxation process provide a new insight that can help improve the photostability in 2D perovskites and understand roles of LESs in optoelectronic device performance.

2D organic-inorganic perovskite↗

Co-templating of polyoxoniobates and silicate/germanate trimer-rings in crystals and inorganic gels

Polyoxometalate (POM) supramolecular gels are a growing family of materials, both for understanding fundamental self-assembly and fabricating flexible monolithic materials that retain the function of metal oxides. Here, we exploited the pH-dependent speciation of polyoxoniobates (PONbs), targeting the formation of PONb-containing supramolecular gels that contain other low molecular weight components (silicate, germanate, phosphate, and carbonate). The introduction of gaseous CO 2 into aqueous hexaniobate solutions resulted in the formation of both new crystalline phases and highly transparent gels. The crystalline phases, formulated Cs 24 [Nb 7 O 22 (NbO(CO 3 ) 2 ) 9 (Si 3 O 9 )]·19.6H 2 O and Cs 21 Na 3 [Nb 7 O 22 (NbO(CO 3 ) 2 ) 9 (Ge 3 O 9 )]·33.6H 2 O are templated by a rare planar [X 3 O 9 ] 6− (X = Si, Ge) ring. Crystalline phases were not obtained with phosphate; instead, the gels contain a mixture of phosphate-centred PONbs and network-forming phosphate. POM speciation within the gels, physical properties, and assembly mechanisms were benchmarked by solution and solid-state nuclear magnetic resonance (NMR) spectroscopy, vibrational spectroscopies, small-angle X-ray scattering (SAXS), and thermogravimetry-mass spectroscopy. Optical analysis and dielectric behavior of the gels confirmed that they are highly transparent ionic and electronic conductors. The alkali and hydroxide concentration controls the formation of crystalline materials or supramolecular gels while maintaining the same network building blocks, providing a rare opportunity to describe the molecular-level structure of inorganic amorphous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles is presented and a high-efficiency approach of discovering low κ L materials by screening the local coordination environments of crystalline compounds is developed. The resulting first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from 13 prototype crystal structures contained in the Inorganic Crystal Structure Database. Furthermore, an approach of rationally designing high-performance thermoelectrics is demonstrated by additionally incorporating cations with stereochemically active lone-pair electrons. Here these results not only provide atomic-level insights into the physical origin of the low lattice thermal conductivity in a large family of copper/silver-based compounds but also offer an efficient approach to discover and design materials with targeted thermal transport properties.

36 MATERIALS SCIENCE↗