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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Directed Evolution of CRISPR/Cas Systems for Precise Gene Editing

CRISPR technology is a universal tool for genome engineering that has revolutionized biotechnology. Recently identified unique CRISPR/Cas systems, as well as re-engineered Cas proteins, have rapidly expanded the functions and applications of CRISPR/Cas systems. The structures of Cas proteins are complex, containing multiple functional domains. These protein domains are evolutionarily conserved polypeptide units that generally show independent structural or functional properties. Here, we propose using protein domains as a new way to classify protein engineering strategies for these proteins and discuss common ways to engineer key domains to modify the functions of CRISPR/Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Analysis of biofilm assembly by large area automated AFM

Biofilms are complex microbial communities critical in medical, industrial, and environmental contexts. Understanding their assembly, structure, genetic regulation, interspecies interactions, and environmental responses is key to developing effective control and mitigation strategies. While atomic force microscopy (AFM) offers critically important high-resolution insights on structural and functional properties at the cellular and even sub-cellular level, its limited scan range and labor-intensive nature restricts the ability to link these smaller scale features to the functional macroscale organization of the films. We begin to address this limitation by introducing an automated large area AFM approach capable of capturing high-resolution images over millimeter-scale areas, aided by machine learning for seamless image stitching, cell detection, and classification. Large area AFM is shown to provide a very detailed view of spatial heterogeneity and cellular morphology during the early stages of biofilm formation which were previously obscured. Using this approach, we examined the organization of Pantoea sp. YR343 on PFOTS-treated glass surfaces. Our findings reveal a preferred cellular orientation among surface-attached cells, forming a distinctive honeycomb pattern. Detailed mapping of flagella interactions suggests that flagellar coordination plays a role in biofilm assembly beyond initial attachment. Additionally, we use large-area AFM to characterize surface modifications on silicon substrates, observing a significant reduction in bacterial density. This highlights the potential of this method for studying surface modifications to better understand and control bacterial adhesion and biofilm formation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dynamical origins of weakly coupled relaxor behavior in Sn-doped (Ba,Ca)TiO 3 -BiScO 3

The peculiar characteristics of relaxors, viz., a frequency-dependent dielectric permittivity peak and good functional properties (dielectric, electromechanical, electrocaloric, etc.), are attributed to nanoscale regions with correlated dipoles, or polar nanoregions (PNRs). However, the exact nature of PNRs and their contribution to relaxor behavior remains debatable. In recent years, solid solutions of BaTiO3-BiMeO3 (where Me is a metal), have emerged as an interesting system with characteristics in between that of relaxors and dipole glasses. Here, we have examined the atomistic origins of weakly coupled relaxor behavior, specifically with regard to formation of PNRs, in Sn-doped (1-x)(Ba,Ca)TiO 3-x BiScO 3 using macroscopic polarization and neutron dynamic pair distribution function measurements. We show that the short-range atomic correlations observed within the PNRs dynamically fluctuate with frequencies of the order of THz. Furthermore the composition-dependent dielectric and polarization behaviors are critically influenced by the relative stability of the atomic correlations near ~1 THz, while the instantaneous atomic correlations are largely independent of x. The current results are discussed based on a model of intrinsic local modes distributed in a dielectrically soft matrix.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

In Situ Synthesized Homochiral Spiroborate Ester Metal–Organic Framework with Mono–, Di–, and Trivalent Cations

Here we report here a one–step method for synthesizing multi–component and in–situ–formed homochiral spiroborate–ester–based metal–organic framework CPM–B1. This unique material successfully integrates COF fragment spiroborate ester within the MOF and simultaneously incorporate homochirality and helicity. In addition, CPM–B1 is a rare example of framework materials that results from the cooperative assembly of three charge–complementary cations: +1 (lithium), +2 (cobalt), and +3 (boron). The sophistication of the co–assembly is further highlighted by the three structural roles of lithium ions. This unique structure contributes to its multi–functional properties such as ionic conductivity and catalytic activity for oxygen reduction reaction (by CPM–B1 carbonized material) and provides a new path to develop MOF materials with complex secondary building units and multi–functional applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The developments in modifying functionality of lignin and its application in biocomposites

With the advancement of sustainable material innovations, renewable natural biopolymers are gradually replacing traditional metal and petroleum-based synthetic materials due to their environmental friendliness, biodegradability, and economic advantages. Lignin, the second most abundant natural aromatic polymer in the plant kingdom, has emerged as a key candidate raw material for the development of green polymer systems because of its unique phenylpropane unit network structure, high carbon content, and rich functional group characteristics. However, challenges such as the inherent structural complexity, chemical inertness, and uneven molecular weight distribution of lignin limit its direct application. By employing modification strategies such as chemical functionalization and physical regulation, researchers can precisely control its reactivity, thermal stability, and interfacial compatibility, enabling the preparation of high-performance lignin-based functional composites. Here, this paper systematically reviews the principles and methodological advancements in lignin's multi-dimensional modification technology. It analyzes the mechanisms by which various chemical and physical modification techniques enhance the mechanical properties, functional responsiveness, and environmental adaptability of materials, and discusses innovative applications in fields such as intelligent packaging, biomedical materials, and energy storage devices. Furthermore, this review addresses the key challenges encountered in the high-value transformation of lignin, with the aim of offering a theoretical framework and technical pathway for the transformative development of lignin from agricultural and forestry by-products to functional material platforms.

Functional composites↗
DOE OSTI2022

Atomic structure of an FeCrMoCBY metallic glass revealed by high energy x-ray diffraction

Amorphous bulk metallic glasses with the composition Fe 48 Cr 15 Mo 14 C 15 B 6 Y 2 have been of interest due to their special mechanical and electronic properties, including corrosion resistance, high yield-strength, large elasticity, catalytic performance, and soft ferromagnetism. Here, we apply a reverse Monte Carlo technique to unravel the atomic structure of these glasses. The pair-distribution functions for various atomic pairs are computed based on the high-energy x-ray diffraction data we have taken from an amorphous sample. Monte Carlo cycles are used to move the atomic positions until the model reproduces the experimental pair-distribution function. The resulting fitted model is consistent with our ab initio simulations of the metallic glass. Our study contributes to the understanding of functional properties of Fe-based bulk metallic glasses driven by disorder effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Fracture‐Resistant and Thermally Insulating Ultrahigh‐Temperature Carbide Foams

Dense ultrahigh‐temperature ceramics (UHTCs) carbides are recognized as potential materials for thermal protection systems (TPS) owing to properties beyond existing structural materials’ capabilities. Recent advances in UHTCs have enabled the development of multiscale porous microstructures. Herein, it is highlighted that the porosity in UHTCs are no longer treated as a defect but as a functional property specifically tailored for thermal insulation. It is a promising solution to design and fabricate bulk UHTC foams via a freeze‐drying (FD) approach followed by calibrated pressureless spark plasma sintering. Herein, monolithic TaC and HfC UHTC foams and their composite show the partial solid–solution formation of (Ta, Hf)C with porosity ≥50%. TaC–HfC foam (≈80–92 N) shows an intermediate load‐bearing capability compared to monolithic TaC (≈120–135 N) and HfC (≈28–35 N) foams, with no evident cracking on the sample surface. The thermal conductivity of partial solid‐solution TaC–HfC foam increases up to fivefold compared to parent UHTC foams. In the results, solid solutions’ efficacy and pores’ unidirectionality in providing thermal insulation to TaC–HfC while maintaining its high‐load bearing capability are illustrated. In conclusion, the developed technique establishes a new paradigm shift in UHTCs, expanding their potential for TPS in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals an d alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

3D printed materials, stress-strain behavior, mult↗
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals and alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Metallurgical alloy approach to two-dimensional supramolecular materials

Alloys are normally mixtures of metallic elements used to search for superior functional properties compared with their individual components. Although a quintessential approach to better materials in metallurgy, the concept of alloying has been expanded to other inorganic materials and covalent polymers. In this work, we report on alloy formation of small organic molecules structured as amphiphilic chromophores in water. Using X-ray scattering, microscopy, and optical spectroscopy, we unambiguously demonstrate the formation of supramolecular alloys with changes in physical, photophysical, and mechanical properties. Additionally, we identify single-crystalline, two-dimensional supramolecular polymers containing multiple molecular species, analogous to intermetallic compounds. The mechanism of alloy formation suggests the possibility of controlled growth in these supramolecular assemblies to create emergent functional structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Small to Large Polaron Behavior Induced by Controlled Interactions in Perovskite Quantum Dot Solids

The polaron is an essential photoexcitation that governs the unique optoelectronic properties of organic–inorganic hybrid halide perovskites, and it has been subject to extensive spectroscopic and theoretical investigation over the past decade. A crucial but underexplored question is how the nature of the photogenerated polarons is impacted by the microscopic perovskite structure and what functional properties this affects. To tackle this question, we chemically tuned the interactions between perovskite quantum dots (QDs) to rationally manipulate the polaron properties. Through a suite of time-resolved spectroscopies, we find that inter-QD interactions open an excited-state channel to form large polaron species, which exhibit enhanced spatial diffusion, slower hot polaron cooling, and a longer intrinsic lifetime. At the same time, polaronic excitons are formed in competition via localized band-edge states, exhibiting strong photoluminescence but are limited by shorter intrinsic lifetimes. Furthermore, this control of polaron type and function through tunable inter-QD interactions not only provides design principles for QD-based materials but also experimentally disentangles polaronic species in hybrid perovskite materials.

14 SOLAR ENERGY↗
DOE OSTI2024

Electronic, direct optical, and phonon-assisted optical properties of 4H Si from first principles

The cubic polytype of silicon (Si) is the most commercialized semiconductor material and finds applications in numerous electronic and optoelectronic devices, such as solar cells. However, recent reports on the synthesis of the hexagonal 4H Si polytype have attracted the attention of the scientific community to understand its functional properties. Here, we report the electronic, vibrational, and optical properties of the 4H Si polytype obtained with predictive first-principles calculations, with an emphasis of phonon-assisted absorption in the indirect regime. Compared to the cubic polytype, 4H Si shows a slightly narrower indirect gap by ∼0.05 eV. The calculated phonon-assisted optical spectra show that 4H Si exhibits a stronger absorption coefficient than cubic Si across the visible and IR spectral regions. We further evaluate the short-circuit current density of textured thin-films. We demonstrate that 4H Si can achieve the same short-circuit current density for a five times thinner film compared to the cubic polytype, which mainly resulted from absorption in the indirect gap regime. Our work demonstrates the advantages of 4H Si for thin-film silicon-based solar-cell applications.

Materials Science↗
DOE OSTI2023

α-Quartz Phase Stabilization, Surface Texturing, and Tunable Optical Properties of Nanocrystalline GeO 2 Films Made by Pulsed-Laser Deposition: Implications for Optical and Optoelectronic Applications

Germanium oxide (GeO 2 ) has great potential in multifunctional devices and next-generation power electronics due to its high thermal conductivity and ambipolar doping capability. However, the complexity of synthesizing the desirable polymorph with a controlled phase, surface/interface quality, microstructure, and functional properties is the main barrier to GeO 2 utilization in advanced applications. Here, in this regard, we present a method to realize the hexagonal (h) or a-quartz type GeO 2 with nano-textured surface morphology on sapphire substrates using a hybrid synthesis strategy that comprises pulsed laser deposition (PLD) and post-deposition thermal annealing. We performed a comprehensive study to investigate the effect of annealing temperature, which was varied in a wide range (600-1100 °C), on the crystal structure, phase, surface morphology, chemical stoichiometry, defect states, and optical properties of PLD-grown GeO 2 films. As-deposited GeO 2 films at 500 °C were amorphous. Upon annealing, the GeO 2 films induced an amorphous-to-crystalline phase transformation; GeO 2 films annealed at higher annealing temperatures (≥900 °C) stabilized in the hexagonal phase and demonstrated excellent crystal quality and chemical stability. Thermally activated growth process showed increased average crystallite size, which was varied in the range of 20-130 (±2) nm, while the surface roughness followed a similar trend. The spectral transmittance and band gap also increased with increasing annealing temperature. The resulting h-GeO 2 films, particularly those obtained at annealing temperatures in the 900-1100 °C range, had a higher band gap of 6.2-6.3 eV and displayed excellent optical transmittance in the visible region. Moreover, the absence of extended valence band maxima and reduced optical defect density support the quality improvement upon annealing. When considering phase-pure bulk and nanostructured GeO 2 as a possible candidate for ultra wide band gap semiconductors in cutting-edge technological applications, the results of the current work can be beneficial to realize high structural and optical quality a-quartz structured GeO 2 films.

GeO2↗
DOE OSTI2020

Structural and photoelectrochemical properties in the thin film system Cu–Fe–V–O and its ternary subsystems Fe–V–O and Cu–V–O

Thin-film material libraries in the ternary and quaternary metal oxide systems Fe–V–O, Cu–V–O, and Cu–Fe–V–O were synthesized using combinatorial reactive co-sputtering with subsequent annealing in air. Their compositional, structural, and functional properties were assessed using high-throughput characterization methods. Prior to the investigation of the quaternary system Cu–Fe–V–O, the compositions (Fe 61 V 39 )O x and (Cu 52 V 48 )O x with promising photoactivity were identified from their ternary subsystems Fe–V–O and Cu–V–O, respectively. Two Cu–Fe–V–O material libraries with (Cu 29-72 Fe 4-27 V 22-57 )O x and (Cu 11-55 Fe 27-73 V 12-34 )O x composition spread were investigated. Seven mixed ternary and quaternary phase regions were identified: I (α-Cu 3 FeV 6 O 26 /FeVO 4 ), II (Cu 5 V 2 O 10 /FeVO 4 /α-Cu 3 Fe 4 V 6 O 26 ), III (Cu 5 V 2 O 10 ), IV (Cu 5 V 2 O 10 /FeVO 4 , V (FeVO 4 /γ-Cu 2 V 2 O 7 /α-Cu 3 Fe 4 V 6 O 26 ), VI (β-Cu 2 V 2 O 7 /α-Cu 3 Fe 4 V 6 O 26 /FeVO 4 ), and VII (β-Cu 3 Fe 4 V 6 O 26 /FeVO 4 ). Furthermore, in the investigated composition range, two photoactive regions, (Cu 53 Fe 7 V 40 )O x and (Cu 45 Fe 21 V 34 )O x , were identified, exhibiting 103 μ A/cm 2 and 108 μ A/cm 2 photocurrent density for the oxygen evolution reaction at 1.63 V vs reversible hydrogen electrode, respectively. The highest photoactive region (Cu 45 Fe 21 V 34 )O x comprises the dominant α-Cu 3 Fe 4 V 6 O 24 phase and minor FeVO 4 phase. This photoactive region corresponds to having an indirect bandgap of 1.87 eV and a direct bandgap of 2.58 eV with an incident photon-to-current efficiency of 30% at a wavelength of 310 nm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Garcinoic Acid Is a Natural and Selective Agonist of Pregnane X Receptor

Pregnane X receptor (PXR) is a master xenobiotic-sensing transcription factor and a validated target for immune and inflammatory diseases. The identification of chemical probes to investigate the therapeutic relevance of the receptor is still highly desired. In fact, currently available PXR ligands are not highly selective and can exhibit toxicity and/or potential off-target effects. In this study, we have identified garcinoic acid as a selective and efficient PXR agonist. The properties of this natural molecule as a specific PXR agonist were demonstrated by the screening on a panel of nuclear receptors, the assessment of the physical and thermodynamic binding affinity, and the determination of the PXR-garcinoic acid complex crystal structure. Cytotoxicity, transcriptional, and functional properties were investigated in human liver cells, and compound activity and target engagement were confirmed in vivo in mouse liver and gut tissue. In conclusion, garcinoic acid is a selective natural agonist of PXR and a promising lead compound toward the development of new PXR-regulating modulators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Improved Operational Stability of Blue Phosphorescent OLEDs by Functionalizing Phenyl‐Carbene Groups of Tetradentate Pt(II) Complexes

Abstract Stable and efficient deep‐blue organic light‐emitting diodes (OLEDs) are in high demand for display and lighting applications but are rarely reported due to their poor operational lifetimes. Herein, the study designs and synthesizes two novel N ‐heterocyclic carbene (NHC)‐based tetradentate Pt(II) complexes PtON5‐dtb and PtON5N‐dtb, and thoroughly investigate their electrochemical and photophysical properties. Functionalization of the NHC moieties can increase the metal‐to‐ligand charge transfer ( 1/3 MLCT) characters in their lowest triplet excited‐states, resulting in significantly shortened photoluminescent lifetimes and remarkably improved device performance. A deep blue OLED employing PtON5N‐dtb as an emitter exhibits a narrow spectral bandwidth with a full‐width at half maximum (FWHM) of 30 nm and a CIE y value of 0.17 and demonstrates a maximum external quantum efficiency (EQE) of 20.4% with a small efficiency roll‐off, which maintains a high EQE of 18.5% at 1000 cd m −2 . Moreover, the deep blue OLED also realizes a long‐measured operational lifetime LT 90 (time to 90% of the initial luminance) of 71 hours with an initial brightness of 1134 cd m −2 , corresponding to an estimated device lifetime LT 90 of 85 h at 1000 cd m −2 . This represented an eightfold lifetime improvement for PtON5N‐dtb‐based deep blue OLED compared to PtON7‐dtb in the same device setting.

Li, Guijie↗
DOE OSTI2025

Equilibrium-gated pattern formation: How molecular dissociation thermodynamics drive emergent behavior in dissipative polymeric systems

Emergent patterns in biological systems arise through dissipative processes that balance reaction and transport phenomena, producing highly functional properties from self-regulating mechanisms. Synthetic fabrication, by contrast, often relies on user-controlled, multistep methods that lack the self-organizing capabilities of natural systems. Inspired by nature, we sought chemical systems that integrate strongly coupled reaction and transport phenomena, identifying frontal ring-opening metathesis polymerization (FROMP) as a method capable of creating diverse forms and functions through reactive processing. By employing discrete molecular initiators, FROMP allows precise control of key reaction steps—inhibition, initiation, and propagation. Using an integrated computational and experimental framework, we uncover how near-equilibrium inhibition dynamics, coupled with far-from-equilibrium reaction kinetics, drive pattern formation in frontally polymerized synthetic materials. We propose the concept of equilibrium-gated pattern formation, demonstrating how initiator chemistry can be tuned to achieve programmable macroscale properties. Our study reveals a surprising insight: Emergent behavior in FROMP systems arises from the inhibition-dominated regime of resin composition, expanding prior observations that such behavior is confined to a narrow compositional space near the boundary between front quenching and uniform front propagation. We identify a broader compositional window, far from the quenching regime, where emergent behavior reliably manifests. This expanded design space significantly enhances the operational flexibility of reactive systems and their capacity for self-organization. Furthermore, these insights provide a roadmap for designing bioinspired materials with self-organizing capabilities, unlocking possibilities in synthetic manufacturing.

Architected Polymers↗