SEARCH · Search NASA
Results for “Structure Interactions”
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.
Leveraging Triphenylphosphine-Containing Polymers to Explore Design Principles for Protein-Mimetic Catalysts
Complex interactions between noncoordinating residues are significant yet commonly overlooked components of macromolecular catalyst function. While these interactions have been demonstrated to impact binding affinities and catalytic rates in metalloenzymes, the roles of similar structural elements in synthetic polymeric catalysts remain underexplored. Using a model Suzuki–Miyuara cross-coupling reaction, we performed a series of systematic studies to probe the interconnected effects of metal–ligand cross-links, electrostatic interactions, and local rigidity in polymer catalysts. To achieve this, a novel bifunctional triphenylphosphine acrylamide (BisTPPAm) monomer was synthesized and evaluated alongside an analogous monofunctional triphenylphosphine acrylamide (TPPAm). In model copolymer catalysts, increased initial reaction rates were observed for copolymers untethered by Pd complexation (BisTPPAm-containing) compared to Pd-cross-linked catalysts (TPPAm-containing). Further, incorporating local rigidity through secondary structure-like and electrostatic interactions revealed nonmonotonic relationships between composition and the reaction rate, demonstrating the potential for tunable behavior through secondary-sphere interactions. Lastly, through rigorous cheminformatics featurization strategies and statistical modeling, we quantitated relationships between chemical descriptors of the substrate and reaction conditions on catalytic performance. Collectively, these results provide insights into relationships among the composition, structure, and function of protein-mimetic catalytic copolymers.
A multimodal large language model for materials science
Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.
Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons
Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.
Angle between DNA linker and nucleosome core particle regulates array compaction revealed by individual-particle cryo-electron tomography
Abstract The conformational dynamics of nucleosome arrays generate a diverse spectrum of microscopic states, posing challenges to their structural determination. Leveraging cryogenic electron tomography (cryo-ET), we determine the three-dimensional (3D) structures of individual mononucleosomes and arrays comprising di-, tri-, and tetranucleosomes. By slowing the rate of condensation through a reduction in ionic strength, we probe the intra-array structural transitions that precede inter-array interactions and liquid droplet formation. Under these conditions, the arrays exhibite irregular zig-zag conformations with loose packing. Increasing the ionic strength promoted intra-array compaction, yet we do not observe the previously reported regular 30-nanometer fibers. Interestingly, the presence of H1 do not induce array compaction; instead, one-third of the arrays display nucleosomes invaded by foreign DNA, suggesting an alternative role for H1 in chromatin network construction. We also find that the crucial parameter determining the structure adopted by chromatin arrays is the angle between the entry and exit of the DNA and the corresponding tangents to the nucleosomal disc. Our results provide insights into the initial stages of intra-array compaction, a critical precursor to condensation in the regulation of chromatin organization.
Recent progress in realizing novel one-dimensional polymorphs via nanotube encapsulation
Encapsulation of various materials inside nanotubes has emerged as an effective method in nanotechnology that facilitates the formation of novel one-dimensional (1D) structures and enhances their functionality. Because of the effects of geometrical confinement and electronic interactions with host nanotubes, encapsulated materials often exhibit low-dimensional polymorphic structures that differ from their bulk forms. These polymorphs exhibit unique properties, including altered electrical, optical, and magnetic behaviors, making them promising candidates for applications in electronics, energy storage, spintronics, and quantum devices. This review explores recent advancements in the encapsulation of a wide range of materials such as organic molecules, elemental substances, metal halides, metal chalcogenides, and other complex compounds. In particular, we focus on novel polymorphs formed through the geometrical confinement effect within the nanotubes. The atomic structure, other key properties, and potential applications of these encapsulated materials are discussed, highlighting the impact of nanotube encapsulation on their functionalities.
Stability, electronic quantum states, and magnetic interactions of Er 3+ ions in Ga 2 O 3
Here, we report an ab initio study of phase stability, defect formation, electronic structure, and multiple magnetic, Dzyaloshinskii-Moriya, optical, hyperfine, and crystal field interactions in erbium (Er)-doped wide band gap 𝛼- and 𝛽-gallium oxides (Ga 2 O 3 ), critically important to make a foundation for both optoelectronic and quantum information applications. The chemical, structural, mechanical, and dynamical stabilities of the pristine phases are confirmed from respective negative formation energies, negative cohesive energies, favorable elastic constants, and positive phonon frequencies. The phonon dispersions indicate that the Ga-O bonds are uniform in the 𝛼-phase, while they vary in the 𝛽-phase due to the anisotropic polyhedral movement. The defect formation energy analysis confirms that both Er-doped 𝛼- and 𝛽−Ga 2 O 3 prefer Er 3+ (neutral) state. The underestimated band gaps of the pristine phases from standard density functional theory (DFT) calculations as compared to experimental values are corrected by employing the hybrid functional calculations, resulting in the indirect band gaps of 5.21 eV in 𝛼−Ga 2 O 3 and 4.94 eV in 𝛽−Ga 2 O 3 . The site preference energy analysis indicates partial occupation of Er in the octahedral site of Ga. The anisotropic nature of hyperfine tensor coefficients of Er is similar in both phases, which may be due to the occupation of Er in the same octahedral Ga site. On the other hand, the calculated magnetic exchange interaction between two Er dopants is negative for 𝛼 and positive for 𝛽, indicating an antiferromagnetic (AFM) ground state in the former and a ferromagnetic (FM) ground state in the latter. Large values of Dzyaloshinskii-Moriya interactions (DMIs) are obtained along the 𝑥 direction in the 𝛼 and along the 𝑦 direction in the 𝛽. The large DMI may support exotic magnetic textures, a promising direction for spintronic applications. The analysis of dielectric constants and refractive indices of both pristine and Er-doped phases shows a good agreement with available experimental values. The calculated optical anisotropy is slightly higher in 𝛽 than those in 𝛼, which is due to the involvement of lower symmetry in 𝛽. The crystal field coefficients (CFCs) calculated from DFT are used to analyze 4𝑓 multiplets and 4𝑓 −4𝑓 transitions. Thus calculated lowest energy level of the first excited state to the lowest energy level of the ground state is about 1.53 µm, which is in a good agreement with available experiments, and it falls within the quantum telecommunication wavelength range.
Identification of a key water molecule involved in the macrophage migration inhibitory factor‐catalyzed tautomerization of para ‐hydroxyphenylpyruvate using neutron crystallography
Abstract Neutron crystallography was used to determine a 2.5‐Å resolution all‐atom structure of macrophage migration inhibitory factor (MIF) interacting with 3‐(4‐hydroxyphenyl)‐pyruvate (HPP). MIF is a pro‐inflammatory, pro‐tumorigenic protein that may be an attractive therapeutic target. MIF catalyzes the interconversion of the keto and enol forms of HPP by a tautomerase reaction. Although HPP is evidently not a physiological substrate of MIF, many compounds that inhibit this activity in enzymatic assays have been found also to inhibit physiological activities of MIF. Therefore, the MIF‐catalyzed HPP tautomerization reaction is used in initial screening of compounds in the search for inhibitors of MIF physiological activity. The neutron diffraction‐derived crystal structure reveals the position of a water molecule involved in the tautomerization reaction, and also confirms the charged state of lysine‐32 in the active site. The structure confirms the previously proposed catalytic mechanism of MIF, with the N‐terminal Pro‐1 abstracting a proton to generate an HPP enolate intermediate which is subsequently protonated. The structure reported herein reveals that this proton is supplied by a neighboring water molecule. Along with the neutron structure, a room‐temperature synchrotron x‐ray crystal structure reveals a covalent adduct between HPP and MIF. While this adduct is a result of radiation‐induced chemistry, its formation confirms the catalytic role of the active site residue because a covalent complex could only form if the reactive carbon of the substrate is correctly positioned by the enzyme.
Forest structural complexity and ignition pattern influence simulated prescribed fire effects
Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.
Unraveling the Heterogeneous but Ordered Microstructure of the Nonionic Deep Eutectic Solvent Formed by Lauric Acid and N -Methylacetamide
The nonionic deep eutectic solvent, formed by lauric acid (LA) and N-methylacetamide (NMA), has been shown to have a heterogeneous molecular structure in which the LA and NMA form nonpolar and polar domains, respectively. Previous vibrational spectroscopy experiments demonstrated that the ability of the LA domains to solvate compounds was limited to long carbon chains, whereas other nonpolar molecules, such as W(CO) 6 , were found to be solvated by both LA and NMA. These experiments were not fully compatible with the previously proposed micelle-like structure of the nonpolar domains of the LA-NMA DES. In this work, the modeling of the DES molecular structure is pursued using classical molecular dynamics simulations. The new classical model reproduces both the SAXS structural factors and the previously experimentally derived interaction map for these LA-NMA DESs. In addition, the simulation also shows that LA-NMA DESs form highly organized LA aggregates that are difficult to disorganize. Further evidence of the correct description provided by the newly derived model is obtained using a moderately polar probe: chloroform-d. Computations using the classical model have a good agreement with the solvation behavior of the probe derived from experiments, in which the location of the probe is found to be mostly within the polar domain of the DES. The computational model also demonstrates that the probe solvation is a consequence of the tightly packed LA structure, which causes nonpolar molecules to be located at the interphase of the DES nonpolar domains.
Weak-coupling theory of magic-angle twisted bilayer graphene
Strong correlations occur in magic-angle twisted bilayer graphene (MATBG) when the octet of flat moiré minibands centered on charge neutrality (CN) is partially occupied. The octet consists of a single valence band and a single conduction band for each of four degenerate spin-valley flavors. Motivated by the importance of Hartree electrostatic interactions in determining the filling-factor-dependent band structure, we use a time-dependent Hartree approximation to gain insight into electronic correlations. We find that the electronic compressibility is dominated by Hartree interactions, that paramagnetic states are stable over a range of density near CN, and that the dependence of energy on flavor polarization is strongly overestimated by mean-field theory. Published by the American Physical Society 2024
Multicationic interactions mitigating lattice strain in sodium layered cathodes
Transition-metal (TM) layered oxides have emerged as the primary cathode choice for sodium-ion batteries (SIBs) due to their high energy density and sustainable chemistry using non-critical elements. However, their anisotropic lattice strain and stress accumulation during (de)sodiation lead to severe structural degradation, yet an intrinsic strain-depressant approach remains elusive. Herein, we propose entropy regulation with zero Li/Co usage to mitigate harmful lattice displacements and enhance the electrochemical performance of sodium layered cathodes. Our findings demonstrate that high entropy design effectively inhibits TMO 6 octahedra distortions upon cycling, as evidenced by hard X-ray absorption spectroscopy, greatly reducing near-surface structural deconstruction and interface side reactions. Furthermore, multicationic interactions driven by configurational entropy thermodynamically mitigate the formation of oxygen defects and strengthen ligand-to-metal coordination. The complementarity inherent in charge compensation within complex systems is unveiled and the restrained lattice parameters deviations without interior volume residuals are successfully achieved. As a result, the multicationic cathode exhibits improved cycling stability and Na + diffusion kinetics in both half and full cells. The cathode chemistries outlined here broaden the prospects for lattice engineering to alleviate bulk fatigue and open up the possibility to develop an economically viable layered oxides with long durability.
X-ray Spectroscopy Characterization of Electronic Structure and Metal–Metal Bonding in Dicobalt Complexes
Developing multimetallic complexes with tunable metal–metal interactions has long been a target of synthetic inorganic chemistry efforts due to the unique properties that such compounds can exhibit. However, understanding relationships between metal–metal bonding and chemical properties is challenging due to system-dependent factors that influence metal–metal and metal–ligand interactions, including ligand identity, coordination geometry, and metal–metal distance. In this work, we apply X-ray absorption and emission spectroscopy and quantum chemical calculations to describe electronic structure and bonding in a series of dicobalt complexes. The compounds with silane ligands and pseudo-octahedral coordination geometry exhibit Co–Co σ and multicentered bonding character, which we characterize from both the occupied and vacant perspectives via their contributions to the Co X-ray emission and absorption spectra, respectively. In contrast, the dicobalt complexes with a pseudotetrahedral coordination environment do not exhibit Co–Co bonding due to symmetry constraints on orbital overlap. We extend these insights to the theoretical evaluation of related dicobalt complexes to explain how ligand coordination and symmetry dictate the presence or absence of a Co–Co bond. In conclusion, this work highlights how fundamental insights into electronic structure and bonding through X-ray spectroscopy uncover important factors governing metal–metal interactions and guide the rational design of multimetallic complexes with tunable metal–metal bonds.
Exploitation of Pore Structure for Increased CO 2 Selectivity in Type 3 Porous Liquids
CO 2 capture requires materials with high adsorption selectivity and an industrial ease of implementation. To address these needs, a new class of porous materials was recently developed that combines the fluidity of solvents with the porosity of solids. Type 3 porous liquids (PLs) composed of solvents and metal–organic frameworks (MOFs) offer a promising alternative to current liquid carbon capture methods due to the inherent tunability of the nanoporous MOFs. However, the effects of MOF structural features and solvent properties on CO 2 –MOF interactions within PLs are not well understood. Herein experimental and computational data of CO 2 gas adsorption isotherms were used to elucidate both solvent and pore structure influences on ZIF-based PLs. The roles of the pore structure including solvent size exclusion, structural environment, and MOF porosity on PL CO 2 uptake were examined. A comparison of the pore structure and pore aperture was performed using ZIF-8, ZIF-L, and amorphous-ZIF-8. Adsorption experiments here have verified our previously proposed solvent size design principle for ZIF-based PLs (1.8× ZIF pore aperture). Furthermore, the CO 2 adsorption isotherms of the ZIF-based PLs indicated that judicious selection of the pore environment allows for an increase in CO 2 selectivity greater than expected from the individual PL components or their combination. This nonlinear increase in the CO 2 selectivity is an emergent behavior resulting from the complex mixture of components specific to the ZIF-L + 2'-hydroxyacetophenone-based PL.
Structure of a biohybrid photosystem I-platinum nanoparticle solar fuel catalyst
Biohybrid solar fuel catalysts leverage natural light-driven enzymes to produce valuable fuel products. One useful biological platform for such a system is photosystem I, a pigment-protein complex that captures sunlight and converts it into chemical energy with near unity quantum efficiency, which generates low potential reducing equivalents for metabolism. Realizing and understanding the molecular basis for an approach that utilizes those electrons and stores solar energy as a fuel is therefore appealing. Here, we report the 2.27-Å global resolution cryo-EM structure of a photosystem I complex with bound platinum nanoparticles that catalyzes light-driven H 2 production. The platinum nanoparticle binding sites and possible stabilizing interactions are described. Overall, the investigation reveals a direct structural look at a photon-to-fuels photosynthetic biohybrid system.
Data-Driven Modeling and Control of Systems with Plasma-Surface Interactions (Final Technical Report)
This final technical report summarizes the activities and accomplishments in the period from February 2023 thru January 2026. The objective of the proposed research is to investigate the physical mechanisms and processes underlying the formation of structures and patterns in systems with plasma-surface interactions. In the past decades, there have been extensive studies on the interaction of glow discharges, dielectric barrier discharges, and arc discharges with confining or intervening surfaces. The advancement of the understanding of these phenomena is not only of fundamental scientific interest and relevance to the knowledge of the plasma state, but also with profound implications in various technological applications. The research will integrate theoretical, computational, and experimental work within an innovative framework of data assimilation, i.e., optimally combining model predictions with measurements. The scientific merit of this research has three aspects. Firstly, it extends the studies of plasma-surface interactions to systems with insulator surfaces and multi-layer systems, while existing studies are predominantly on electrode surfaces. Secondly, it expects to develop a novel data-driven modeling approach based on data assimilation to enhance the predictive and control capabilities, which could make transformative contributions to basic plasma research. Thirdly, it will shed new light on outstanding problems related to formation of patterns interfacing plasmas. This project also aims to launch an education and outreach initiative at Texas A&M University-Kingsville, a non-R1, minority-serving institution in South Texas. The initiative is structured as a four-tier pyramid. Tier one will be a webinar series for culture and capacity building to inform broader audience in the region about the research fields of plasma science and engineering. Tier two will be the creation and offering of an upper-level undergraduate course on introductory plasma physics, which will help with the recruitment for the upper tiers. On tier three, we will engage and mentor senior design students to conduct work toward the research goal of this project. There will also be a certificate program on general plasma science for undergrad and graduate students, part of which will be lab training at Princeton University. Tier four will be the supervision and mentoring of Ph.D. students. Therefore, this project will systematically expand the talent pipeline, broaden participation from communities historically and geographically underrepresented in DOE SC research portfolio, significantly improve the research and education capacity at the PI’s institution, and contribute to developing a diverse workforce in plasma science and engineering.
Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems
We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.
Dynamic entity formed by protein and its hydration water
The interaction between protein and water plays a pivotal role in shaping the structure, dynamics, and function of biomacromolecules. A comprehensive understanding of this intricate interplay necessitates a systematic evaluation of interaction strength and its consequential impact on the dynamics of proteins and water across diverse protein systems. Despite numerous works on understanding the dynamics of water and proteins and the coupling between them, there are still unanswered questions. Here, we combine neutron scattering and isotope labeling to probe the dynamics of proteins and their hydration water in a variety of protein systems. We consider proteins of different structures and varying thermostability as well as proteins within living cells with distinct growth temperatures. Simultaneous characterization of protein and hydration water dynamics across diverse systems was achieved. Moreover, we performed water sorption isothermal measurements on three representative proteins to correlate the observed dynamics with the strength of the interaction energies governing each system. The experimental results underscore that proteins manifesting stronger attractive interactions with water display diffusionlike dynamics with higher flexibility upon hydration, concomitant with a reduced mobility in hydration water. Significantly, our findings suggest that, in fact, it is the interaction between protein and its hydration water that facilitates the transfer of mobility from water to protein, with stronger interactions correlating to greater protein flexibility and slower hydration water diffusion. Published by the American Physical Society 2024