SEARCH · Search NASA
Results for “crystal design”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The importance of structure property relationship for the designing of biomaterials using liquid crystal elastomers
In this perspective, we presented our group’s journey to design biomaterials using LCEs and as inks for 3D printing. We addressed properties sought in a scaffold that address cells’ specific needs, and how we used the intrinsic properties of LCEs to influence on cell behavior.
Why Seeding Works When Nucleation Barriers Vanish
This paper explains why seeds can speed up crystallization even when the formation of new crystal nuclei is not the slow step. In zeolite synthesis, local crystalline order can form relatively early, but the material may still appear poorly crystalline by X-ray diffraction because many small crystallites are misoriented and lack long-range coherence. Using coarse-grained molecular simulations, the study showed that seeds help solve this coherence problem. Rather than primarily lowering a nucleation barrier, seeds impose a common orientation on nearby growing crystallites, allowing them to merge into larger, better aligned domains. This accelerates the development of X-ray-detectable crystallinity even if the total amount of locally ordered material has not changed much. The work changes how induction times in zeolite synthesis should be interpreted: the delay before X-ray crystallinity appears can reflect the time needed to build long-range structural coherence, not simply the time needed to form crystalline material. This provides a new explanation for why seeding is effective in growth-limited crystallization and offers design principles for controlling crystallization rate and crystal quality.
Accurate computational design of three-dimensional protein crystals
Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here, in this study, we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.
Ultrasonic-Assisted Extrusion Processing for Enhancing Physical Properties of High-Density Polyethylene by Flow-Induced Crystallization
The evolution of crystallinity resulting from stress imposed on a melt, known as flow-induced crystallinity, can strongly influence the mechanical and physical properties of semicrystalline polymers. This study investigates shear-induced crystallization by applying an ultrasonic field to the melt flow as it passes through dies with various geometries. A custom-built sonication die is employed for controlling the dynamic temperature and shear environment, resulting in molecular alignment and potential for flow-induced crystallization. Application of both conventional and ultrasonic shear rates at the equilibrium melt temperature of high-density polyethylene (HDPE) was investigated to accelerate crystallinity and manipulate the crystal morphology across the film in pursuit of improved mechanical and gas barrier properties without the need for additives or other polymer layers. The relationships among ultrasonic-assisted extrusion processing, polymer structure, and performance were analyzed using wide- and small-angle X-ray scattering (WAXS and SAXS), tensile testing, and oxygen transmission rate (OTR) analysis. Multiple linear regression models were implemented to predict the correlation among HDPE structure, process, and properties. Structural analysis revealed that both conventional and ultrasonic shear rates had the most significant influence on lamellar spacing and redistribution of rigid and soft amorphous fractions within the crystalline domains, ultimately dictating the mechanical and physical properties of the films. The goal is to explore the potential of the ultrasonic-assisted high crystallinity monolayer that can replace some of the functionality of complex, heterogeneous multilayer packaging with a single-material film having enhanced oxygen barrier properties.
Emerged Metallicity in Molecular Ferromagnetic Wires
Supramolecular engineering bridges molecular assembly with macromolecular charge-transfer salts, promising the design to construct supramolecular architectures that integrate cooperative properties difficult or impossible to find in conventional lattices. Here, we report the crystal engineering design and kinetic growth of one-dimensional supramolecular wires composed of bis(ethylenedithio)tetrathiafulvalene (ET + ) cation and polymeric Cu[N(CN) 2 ] 2 – anion. A bulk ferromagnetic order is discovered for filling up the gap where strong ferromagnetism is missing in such ET molecule-based charge-transfer salts. Metallicity is induced by electric current from the semiconducting wire, which is attributed to strain effect by tuning its close molecular contact. This structural feature is evidenced through the combination of various mechanistic spectroscopic studies. Further, electric dipole is established from the close molecular contacts and is suggestive to stabilize ferromagnetic spin interaction through anions bridging spin sites. The breakthrough shown here provides a pathway to explore low-dimensional supramolecular materials exhibiting strong electron correlation, metallicity, and ferromagnetism.
Selective Heating Through Y-Junction Waveguide Designed by Acoustic Shape Optimization
Unlike phononic crystals or systems designed by topology optimization, waveguides designed by shape optimization do not have voids or internal defects, making the fabrication process more suitable for additive manufacturing. By designing a Y-junction waveguide through shape optimization, an ultrasonic wave can be controlled so that it propagates to a predetermined location just by adjusting its frequency. These demultiplexed ultrasonic waves can be used to transport signals or stimulate nearby materials. As an example, the ultrasonic wave is converted to heat at different locations, which can be applied to mechanisms that can take advantage of heating. First, shape optimization is performed on a cylindrical structure to selectively propagate ultrasonic waves of a particular frequency while attenuating others, which is analyzed through a finite element model. The numerical study results are compared with experimental measurements from samples fabricated through additive manufacturing methods. After verifying the concept, the Y-junction waveguide is fabricated to demultiplex the wave and selectively heat different locations. Here the results show that the method of combining shape optimization with additive manufacturing is exceptionally simple and capable of demultiplexing ultrasonic waves, which can replace complex electrical components with single-material waveguides.
Modulating Iron Crystals with Lattice Chalcophile‐Siderophile Elements for Selective Dechlorinations Over Hydrogen Evolution
Selective dechlorination of organic chlorides over hydrogen evolution reaction (HER) remains a challenge because of their coincidence. Nanoscale zerovalent iron (nFe 0 ) draws a promising picture of in situ groundwater dechlorination, but its indiscriminate reactivity limits the application. Here, nFe 0 crystals are designed with electron shuttles and improved hydrophobic nature based on elemental chalcophile-siderophile characteristics, where chalcophile-siderophile S served as a bridge to allow impregnating nFe 0 crystals with weakly siderophile and strongly chalcophile Cu. Even impregnations of lattice chalcophile-siderophile elements into the nFe 0 crystals are evidenced at both intraparticle and individual-particle levels. The modulated Fe microenvironment and physicochemical properties broke the reactivity-selectivity-longevity-stability trade-off. Compared to nFe 0 , superhydrophobic Cu─S─nFe 0 with lattice expansion promoted dechlorination by 20-fold but inhibited HER by 150-fold, utilizing ≈80–100% electrons from the Fe 0 reservoir. This work demonstrates the concept of engineering nFe 0 lattice with tunable structure-property relationships, mimicking reductive dehalogenases by selectively interacting with halocarbon functional groups for efficient dehalogenation and sustainable groundwater remediation.
Anisotropic Dynamics and Mechanics of Macromolecular Crystals Containing Lattice-Patterned Polymer Networks
The mechanical and functional properties of many crystalline materials depend on cooperative changes in lattice arrangements in response to external perturbations. However, the flexibility and adaptiveness of crystalline materials are limited. Additionally, the bottom-up, molecular-level design of crystals with desired dynamic and mechanical properties at the macroscopic level remains a considerable challenge. To address these challenges, we had previously integrated mesoporous, cubic ferritin crystals with hydrogel networks, resulting in hybrid materials (polymer integrated crystals or PIX) which could undergo dramatic structural changes while maintaining crystalline periodicity and display efficient self-healing. Here, the dynamics and mechanics of these ferritin-PIX were devoid of directionality, which is an important attribute of many molecular and macroscopic materials/devices. In this study, we report that such directionality can be achieved through the use of ferritin crystals with anisotropic symmetries (rhombohedral or trigonal), which enable the templated formation of patterned hydrogel networks in crystallo. The resulting PIX expand and contract anisotropically without losing crystallinity, undergo prompt bending motions in response to stimuli, and self-heal efficiently, capturing some of the essential features of sophisticated biological devices like skeletal muscles.
Powering ≈50 µm Motion by a Molecular Event in DNA Crystals
A major challenge in material design is to couple nanoscale molecular and supramolecular events into desired chemical, physical, and mechanical properties at the macroscopic scale. Here, a novel self-assembled DNA crystal actuator is reported, which has reversible, directional expansion and contraction for over 50 μm in response to versatile stimuli, including temperature, ionic strength, pH, and redox potential. The macroscopic actuation is powered by cooperative dissociation or cohesion of thousands of DNA sticky ends at the designed crystal contacts. The increase in crystal porosity and cavity in the expanded state dramatically enhances the crystal capability to accommodate/encapsulate nanoparticles/proteins, while the contraction enables a “sponge squeezing” motion for releasing nanoparticles. This crystal actuator is envisioned to be useful for a wide range of applications, including powering self-propelled robotics, sensing subtle environmental changes, constructing functional hybrid materials, and working in drug controlled-release systems.
Optimizing Batch Crystallization with Model-based Design of Experiments
Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.
Design of a multichannel photonic crystal dielectric laser accelerator
To be useful for most scientific and medical applications, compact particle accelerators will require much higher average current than enabled by current architectures. For this purpose, we propose a photonic crystal architecture for a dielectric laser accelerator, referred to as a multi-input multi-output silicon accelerator (MIMOSA), that enables simultaneous acceleration of multiple electron beams, increasing the total electron throughput by at least 1 order of magnitude. To achieve this, we show that the photonic crystal must support a mode at the Γ point in reciprocal space, with a normalized frequency equal to the normalized speed of the phase-matched electron. We show that the figure of merit of the MIMOSA can be inferred from the eigenmodes of the corresponding infinitely periodic structure, which provides a powerful approach to design such devices. Additionally, we extend the MIMOSA architecture to electron deflectors and other electron manipulation functionalities. These additional functionalities, combined with the increased electron throughput of these devices, permit all-optical on-chip manipulation of electron beams in a fully integrated architecture compatible with current fabrication technologies, which opens the way to unconventional electron beam shaping, imaging, and radiation generation.
Statistical Multiobjective Optimization of Thiospinel CoNi 2 S 4 Nanocrystal Synthesis via Design of Experiments
Thiospinels, such as CoNi 2 S 4 , are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi 2 S 4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi 2 S 4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 2 5–2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/$\bar{d}$) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Furthermore, our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.
Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste
Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.
DXRD : a user-friendly suite of two- and multiple-beam dynamical X-ray diffraction programs
The DXRD program suite consisting of a series of dynamical theory programs is introduced for computing dynamical X-ray diffraction from single crystals. Its interactive graphical user interfaces (GUIs) allow general users to make complicated calculations with minimal effort. It can calculate plane-wave Darwin curves of single crystals (or multiple crystals) for both the Bragg and Laue cases, including grazing-incidence diffraction and backward diffraction (with Bragg angles approaching 90°). It is also capable of simulating rocking curves for divergent incident X-ray beams with finite bandwidths. A unique feature of DXRD is that it provides a convenient GUI-based multiple-beam diffraction program that can accurately compute arbitrary N-beam diffraction of any geometry using a universal 4N × 4N matrix method. DXRD also provides a mapping program for plotting all the multiple-beam diffraction lines (monochromator glitches) in the azimuth–energy coordinate system. All these functions make DXRD a convenient and powerful software tool for designing crystal-based synchrotron/X-ray optics (monochromators, analyzers, polarizers, phase plates etc.) and for crystal characterization, X-ray spectroscopy and X-ray diffraction teaching.
CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening
Here, we present an updated version of the Computation-Ready, Experimental (CoRE) Metal-Organic Framework (MOF) database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were improved from the previous version to enable more frequent updates in the future. Machine-learning-predicted properties, such as stability metrics and heat capacities, are included in the dataset to streamline screening activities. An updated version of MOFid was developed to provide detailed information on metal nodes, organic linkers, and topologies of an MOF structure. DDEC6 partial atomic charges of MOFs were assigned based on a machine-learning model. Gibbs ensemble Monte Carlo simulations were used to classify the hydrophobicity of MOFs. The finalized dataset was subsequently used to perform integrated material-process screening for various carbon-capture conditions using high-fidelity temperature-swing adsorption (TSA) simulations. Our workflow identified multiple MOF candidates that are predicted to outperform CALF-20 for these applications.
Charge Disproportionation at Twisted SrTiO 3 Bilayer Interface Driven by Local Atomic Registry
The interplay of lattice, orbital, and charge degrees of freedom in complex oxide materials has hosted a plethora of exotic quantum phases and physical properties. Recent advances in the synthesis of freestanding complex oxide membranes and twisted heterostructures assembled from membranes provide diverse opportunities for discovery using moiré design with local lattice control. To this end, we designed moiré crystals at the coincidence site lattice condition, providing commensurate structure within the moiré supercell arising from the multiatom complex oxide unit cell. We fabricated such twisted bilayers from freestanding SrTiO 3 membranes and used depth-sectioning-based electron microscopic methods to investigate ordered charge states at the moiré interface. By selectively imaging SrTiO 3 atomic planes at different depths through the bilayer, we clearly resolved the moiré periodic structure at the twisted interface and found that it exhibits lattice-dependent charge disproportionation in the local atomic registry within the moiré supercell. Density functional modeling of the twisted oxide interface predicts that these moiré phenomena are accompanied by a two-dimensional flat band that can drive exceptional electronic phases. Our work provides a robust strategy for controlling moiré periodicity in twisted oxides and paves pathways to exploit the extraordinary functionalities via moiré lattice-driven charge-orbital correlation.
Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks
We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydrox-amate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivi-ty, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our stud-ies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corre-sponding to a 4% volumetric change within ≤1 deg C and a hysteresis window of ~10 deg C. Here, this highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular con-struction strategies in discovering tunable–and unpredictable–material properties.