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At least 91 records · Page 5

Unraveling two distinct polymorph transition mechanisms in one n-type single crystal for dynamic electronics

Cooperativity is used by living systems to circumvent energetic and entropic barriers to yield highly efficient molecular processes. Cooperative structural transitions involve the concerted displacement of molecules in a crystalline material, as opposed to typical molecule-by-molecule nucleation and growth mechanisms which often break single crystallinity. Cooperative transitions have acquired much attention for low transition barriers, ultrafast kinetics, and structural reversibility. However, cooperative transitions are rare in molecular crystals and their origin is poorly understood. Crystals of 2-dimensional quinoidal terthiophene (2DQTT-o-B), a high-performance n-type organic semiconductor, demonstrate two distinct thermally activated phase transitions following these mechanisms. Here we show reorientation of the alkyl side chains triggers cooperative behavior, tilting the molecules like dominos. Whereas, nucleation and growth transition is coincident with increasing alkyl chain disorder and driven by forming a biradical state. We establish alkyl chain engineering as integral to rationally controlling these polymorphic behaviors for novel electronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging Exchange Kinetics for the Synthesis of Atomically Precise Porous Catalysts

Metal-organic frameworks (MOFs) have attracted significant attention as porous catalyst platforms due to the synthetic modularity of these materials and the diversity of lattice-confined catalytic active sites that are readily embedded within periodic crystalline frameworks. MOFs offer platforms to heterogenize molecular catalysts, stabilize novel coordination motifs, and leverage confinement effects in catalysis. Crystallinity allows diffraction-based methods to be employed in the characterization of these catalysts. Access to crystalline MOFs typically requires reversible construction of the metal-ligand (M-L) bonds that connect the SBUs, which provides a mechanism to anneal defects during crystallization. While the required M-L bond reversibility is often promoted by synthesis at elevated temperature, access to crystalline materials based on either transition metals with characteristic slow exchange kinetics or highly basic donor ligands remains a synthetic challenge. Here in this paper, we highlight synthetic strategies that leverage M-L exchange kinetics to access MOFs based on kinetically inert ions and extensions of these strategies to the assembly of atomically precise multimetallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning

This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.

Biagioni, David↗

Moving closer to experimental level materials property prediction using AI

Abstract While experiments and DFT-computations have been the primary means for understanding the chemical and physical properties of crystalline materials, experiments are expensive and DFT-computations are time-consuming and have significant discrepancies against experiments. Currently, predictive modeling based on DFT-computations have provided a rapid screening method for materials candidates for further DFT-computations and experiments; however, such models inherit the large discrepancies from the DFT-based training data. Here, we demonstrate how AI can be leveraged together with DFT to compute materials properties more accurately than DFT itself by focusing on the critical materials science task of predicting “formation energy of a material given its structure and composition”. On an experimental hold-out test set containing 137 entries, AI can predict formation energy from materials structure and composition with a mean absolute error (MAE) of 0.064 eV/atom; comparing this against DFT-computations, we find that AI can significantly outperform DFT computations for the same task (discrepancies of $$>0.076$$ > 0.076 eV/atom) for the first time.

36 MATERIALS SCIENCE↗

A charge-density-based general cation insertion algorithm for generating new Li-ion cathode materials

Future lithium (Li) energy storage technologies, in particular solid-state configurations with a Li metal anode, opens up the possibility of using cathode materials that do not necessarily contain Li in its as-made state. To accelerate the discovery and design of such materials, we develop a general, chemically, and structurally agnostic methodology for identifying the optimal Li sites in any crystalline material. For a given crystal structure, we attempt multiple Li insertions at symmetrically in-equivalent positions by analyzing the electronic charge density obtained from first-principles density functional theory. In this report, we demonstrate the effectiveness of this procedure in successfully identifying the positions of the Li ion in well-known cathode materials using only the empty host (charged) material as guidance. Furthermore, applying the algorithm to over 2000 candidate cathode empty host materials we obtain statistics of Li site preferences to guide future developments of novel Li-ion cathode materials, particularly for solid-state applications.

25 ENERGY STORAGE↗

Comprehensive new insights on the potential use of SiC as plasma-facing materials in future fusion reactors

Abstract The performance of silicon carbide as an alternative plasma facing material (PFM) was studied at various irradiation conditions relevant to ion energies and fluxes of a fusion reactor. This analysis involves detailed modeling of subsurface plasma/material interactions, sputtered particle transport above the surface and redeposition, and related changes in material composition and microstructure induced by steady-state and Edge Localized Mode ion fluxes. Transition of a crystalline SiC surface to semi-crystalline and amorphous phases was analyzed based on advanced modeling of DIII-D tokamak experiments where SiC was irradiated in single- and multiple- L-mode and H-mode discharges. This analysis shows that displacement damage, particle deposition/redeposition, and D accumulation on the SiC divertor surface can lead to significant microstructural changes that result in enhanced sputtering erosion in comparison with the original crystalline material. However, the resulting total net erosion rate for a full-coverage, advanced tokamak, SiC coated divertor may well be acceptably low. Moreover, the C sputtering yield from the evolved SiC surface can be seven times lower than from a pure graphite surface; this would imply significantly reduced tritium co-deposition rates in a D-T tokamak reactor, compared with a pure carbon surface. It was also determined that chemical sputtering of both C and Si should not result in any noticeable effect on the net erosion, for attached plasma regimes. Our results thus show encouraging results overall for use of SiC as a PFM in tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Facile, One-Step Synthesis for Core–Shell Perovskite Materials via Molten Salt

Core–shell La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 (LSCF)–La 0.8 Sr 0.2 MnO 3 (LSM) heterostructure crystalline materials have been synthesized in a simple, one-step feeding method via a KNO 3 molten salt solvent. Two-phase perovskite composites can be synthesized in times as short as 10 minutes and is demonstrated for the first time in a molten salt. Further, a combination of X-ray diffraction and S/TEM energy dispersive X-ray spectroscopy has been utilized to confirm the formation of an LSM shell on LSCF cores in all samples when adjusting dwell time, core size, weight ratio between core and shell precursors, and weight ratio of powder to salt. Specifically, decreasing the LSCF core size increases core–shell yield. Smaller cores introduce a greater density of facets on the crystal surface and provide more favorable sites for LSM heterogeneous nucleation.

36 MATERIALS SCIENCE↗

Catalog of topological phonon materials

Phonons play a crucial role in many properties of solid-state systems, and it is expected that topological phonons may lead to rich and unconventional physics. On the basis of the existing phonon materials databases, we have compiled a catalog of topological phonon bands for more than 10,000 three-dimensional crystalline materials. Using topological quantum chemistry, we calculated the band representations, compatibility relations, and band topologies of each isolated set of phonon bands for the materials in the phonon databases. Additionally, we calculated the real-space invariants for all the topologically trivial bands and classified them as atomic or obstructed atomic bands. We have selected more than 1000 “ideal” nontrivial phonon materials to motivate future experiments. The datasets were used to build the Topological Phonon Database.

Science & Technology - Other Topics↗

Quest for Multifunctionality: Current Progress in the Characterization of Heterometallic Metal–Organic Frameworks

Metal–organic frameworks (MOFs) are a class of porous, crystalline materials that have been systematically developed for a broad range of applications. Incorporation of two or more metals into a single crystalline phase to generate heterometallic MOFs has been shown to lead to synergistic effects, in which the whole is oftentimes greater than the sum of its parts. Because geometric proximity is typically required for metals to function cooperatively, deciphering and controlling metal distributions in heterometallic MOFs is crucial to establish structure–function relationships. However, determination of short- and long-range metal distributions is nontrivial and requires the use of specialized characterization techniques. Advancements in the characterization of metal distributions and interactions at these length scales is key to rapid advancement and rational design of functional heterometallic MOFs. Further, this perspective summarizes the state-of-the-art in the characterization of heterometallic MOFs, with a focus on techniques that allow metal distributions to be better understood. Using complementary analyses, in conjunction with computational methods, is critical as this field moves toward increasingly complex, multifunctional systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-Driving Microscopy for AI/ML-Enabled Physics Discovery and Materials Optimization

Materials are the bedrock of economy and foundation for all real-world technologies. The viability of space travel, grid energy storage, solar to fuels conversion, methane removal, and photovoltaic energy solutions hinge on the discovery and optimization of novel materials and rapid scaling toward manufacturing. The last 20 years have seen an exponential growth in the theoretical predictive capability for crystalline materials and small molecules. However, it is only in the last five years that we have seen the rapid expansion of high-throughput synthesis enabled by laboratory robotics and microfluidics, as well as a resurgence of combinatorial synthesis (Abolhasani and Kumacheva 2023; Epps and Abolhasani 2021; Jiang et al. 2022; Rajan 2008; Soldatov et al. 2021; Szymanski et al. 2023). Combinatorial synthesis, microfluidics, and ultimately dip-pen megalibraries have demonstrated the ability to “write” multicomponent nanomaterials at high throughput scale, generating millions of material examples in the 3D, 4D, and 5D composition spaces (Chen et al. 2016, 2019; Jibril et al. 2022).

36 MATERIALS SCIENCE↗

Simulation-based methodology to assess the lattice defects creation as energy storing process

In nuclear industry, damages caused to in-core structural materials by high-energy neutrons have been studied for years. Recently, the possibility of storing energy through the creation of defects in crystalline materials via heavy particle bombardment was investigated. To evaluate the potential of the Wigner effect as energy-storing process, a graphite-moderated Molten Salt Reactor was adopted as a test case. Neutronics simulations performed with OpenMC Monte Carlo code allowed estimating the amount of energy released during fission events, the fraction that is deposited in graphite, and the fraction that has the potential to cause radiation damages. Additionally, molecular dynamics simulations were then performed to study the evolution of cascades triggered by high-energy neutrons. As a major outcome, a more accurate estimate of the radiation damage with respect to the traditional approaches was obtained, and the fraction of the deposited neutron energy that can be stored through long-lived defects was quantified.

25 ENERGY STORAGE↗

Two-photon excited deep-red and near-infrared emissive organic co-crystals

Abstract Two-photon excited near-infrared fluorescence materials have garnered considerable attention because of their superior optical penetration, higher spatial resolution, and lower optical scattering compared with other optical materials. Herein, a convenient and efficient supramolecular approach is used to synthesize a two-photon excited near-infrared emissive co-crystalline material. A naphthalenediimide-based triangular macrocycle and coronene form selectively two co-crystals. The triangle-shaped co-crystal emits deep-red fluorescence, while the quadrangle-shaped co-crystal displays deep-red and near-infrared emission centered on 668 nm, which represents a 162 nm red-shift compared with its precursors. Benefiting from intermolecular charge transfer interactions, the two co-crystals possess higher calculated two-photon absorption cross-sections than those of their individual constituents. Their two-photon absorption bands reach into the NIR-II region of the electromagnetic spectrum. The quadrangle-shaped co-crystal constitutes a unique material that exhibits two-photon absorption and near-infrared emission simultaneously. This co-crystallization strategy holds considerable promise for the future design and synthesis of more advanced optical materials.

36 MATERIALS SCIENCE↗

Simulating charged defects at database scale

Point defects have a strong influence on the physical properties of materials, often dominating the electronic and optical behavior in semiconductors and insulators. The simulation and analysis of point defects is, therefore, crucial for understanding the growth and operation of materials, especially for optoelectronics applications. In this work, we present a general-purpose Python framework for the analysis of point defects in crystalline materials as well as a generalized workflow for their treatment with high-throughput simulations. The distinguishing feature of our approach is an emphasis on a unique, unit cell, structure-only, definition of point defects which decouples the defect definition, and the specific supercell representation used to simulate the defect. This allows the results of first-principles calculations to be aggregated into a database without extensive provenance information and is a crucial step in building a persistent database of point defects that can grow over time, a key component toward realizing the idea of a “defect genome” that can yield more complex relationships governing the behavior of defects in materials. We demonstrate several examples of the approach for three technologically relevant materials and highlight current pitfalls that must be considered when employing these methodologies as well as their potential solutions.

36 MATERIALS SCIENCE↗

Atomistic‐Level Effects of Noncovalent Interactions and Crystalline Packing for Organic Material Structural Integrity upon Exposure to Gamma Radiation

Developing an atomistic understanding of ionizing radiation induced changes to organic materials is necessary for intentional design of greener and more sustainable materials for radiation shielding and detection. Cocrystals are promising for these purposes, but a detailed understanding of how the specific intermolecular interactions within the lattice upon exposure to radiation affect the structural stability of the organic crystalline material is unknown. This study evaluates atomistic-level effects of γ radiation on both single- and multicomponent organic crystalline materials and how specific noncovalent interactions and packing within the crystalline lattice enhance structural stability. Dose studies were performed on all crystalline systems and evaluated via experimental and computational methods. Changes in crystallinity were evaluated by p-XRD and free radical formation was analyzed via EPR spectroscopy. Type of intermolecular interactions and packing within the crystal lattice was delineated and related to the specific free radical species formed and the structural integrity of each material. Periodic DFT and HOMO-LUMO surface mapping calculations provided atomistic-level identifications of the most probable sites for the radicals formed upon exposure to γ radiation and relate intermolecular interactions and molecular packing within the crystalline lattice to experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping of inhomogeneous quasi-3D electrostatic field in electro-optic materials

Abstract This paper describes a new method for direct measurement and evaluation of the inhomogeneous electrostatic vector field with translational symmetry in electro-optic materials exhibiting the Pockels effect. It is based on the evaluation of maximum transmittance of low intensity light passing through a sample under a voltage bias. Here, the sample is located between rotating crossed polarizers, and camera images are obtained at each point to determine the electric field. The evaluation procedure is demonstrated using data acquired on a CdZnTeSe quasi-hemispheric semiconductor gamma-ray detector. In addition to CdTe-related compounds, the method can be used for various other materials showing $$\overline{4}3m$$ 4 ¯ 3 m symmetry such as GaAs, CdTe, GaP, 3C-SiC, and ZnS. Furthermore, it can be generalized to other crystalline materials showing the Pockels effect. The method can be used to probe the space charge and the electric field in several kinds of electronic components and devices, as well as provide useful data on the role of defects, contact configurations and other surface and bulk inhomogeneities in the material that can affect the distribution of the internal electric field.

36 MATERIALS SCIENCE↗

Depth-dependent recovery of thermal conductivity after recrystallization of amorphous silicon

The depth-dependent recovery of silicon thermal conductivity was achieved after the recrystallization of silicon that had been partially amorphized due to ion implantation. Transmission electron microscopy revealed nanoscale amorphous pockets throughout a structurally distorted band of crystalline material. The minimum thermal conductivity of as-implanted composite material was 2.46 W m −1 K −1 and was found to be uniform through the partially amorphized region. X-ray diffraction measurements reveal 60% strain recovery of the crystalline regions after annealing at 450 °C for 30 min and almost full strain recovery and complete recrystallization after annealing at 700 °C for 30 min. In addition to strain recovery, the amorphous band thickness reduced from 240 to 180 nm after the 450 °C step with nanoscale recrystallization within the amorphous band. A novel depth-dependent thermal conductivity measurement technique correlated thermal conductivity with the structural changes, where, upon annealing, the low thermal conductivity region decreases with the distorted layer thickness reduction and the transformed material shows bulk-like thermal conductivity. Full recovery of bulk-like thermal conductivity in silicon was achieved after annealing at 700 °C for 30 min. After the 700 °C anneal, extended defects remain at the implant projected range, but not elsewhere in the layer. Previous results showed that high point-defect density led to reduced thermal conductivity, but here, we show that point defects can either reform into the lattice or evolve into extended defects, such as dislocation loops, and these very localized, low-density defects do not have a significant deleterious impact on thermal conductivity in silicon.

Huynh, Kenny↗

High Throughput Discovery of Thermoelectric Materials (Final Report)

New materials form the heart of advances in energy technologies; however, the actual synthesis and characterization of new materials remains an enormous bottleneck. In this award, the research team focused on developing new approaches overcome this bottleneck. The approach involved depositing at high (supersonic) velocity multiple crystalline materials at a substrate while controlling the resulting film composition. The film could then be annealed to create a homogeneous alloy that was suitable for characterization. High throughput characterization tools were developed in parallel. The research focused on thermoelectric materials, which convert the flow of heat into electrical power. The development of new thermoelectric materials with high power conversion efficiency could displace traditional mechanical heat engines (e.g. turbines).

30 DIRECT ENERGY CONVERSION↗