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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Polarization-Dependent Optical Response in Anisotropic Nanoparticle–DNA Superlattices

DNA-programmable assembly has been used to prepare superlattices composed of octahedral and spherical nanoparticles, respectively. These superlattices have the same body-centered cubic lattice symmetry and macroscopic rhombic dodecahedron crystal habit but tunable lattice parameters by virtue of the DNA length, allowing one to study and determine the effect of nanoscale structure and lattice parameter on the light-matter interactions in the superlattices. Backscattering measurements and finite-difference time-domain simulations have been used to characterize these two classes of superlattices. Superlattices composed of octahedral nanoparticles exhibit polarization-dependent backscattering but via a trend that is opposite to that observed in the polarization dependence for analogous superlattices composed of spherical nanoparticles. Electrodynamics simulations show that this polarization dependence is mainly due to the anisotropy of the nanoparticles and is observed only if the octahedral nanoparticles are well-aligned within the superlattices. Both plasmonic and photonic modes are identified in such structures, both of which can be tuned by controlling the size and shape of the nanoparticle building blocks, the lattice parameters, and the overall size of the three-dimensional superlattices (without changing habit).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Tuning Anisotropic Optical Properties of Inorganic and Hybrid Organic–Inorganic MXenes via Topochemical Surface Modification

Surface groups are central to the properties of MXenes, yet their role in optical anisotropy remains largely unexplored. Here, we use a topochemical route to synthesize single crystals of stacked Ti 3 C 2 Cl 2 and hybrid organic–inorganic MXenes (h-MXenes) with lateral sizes of 38–75 μm, rotational registry, and tunable interlayer spacing. Solid-state NMR spectroscopy shows that topochemical substitution generates mixed amido, imido, and hydride surface motifs, which modify the electronic structure of the Ti 3 C 2 inorganic core. Imaging spectroscopic ellipsometry with micron-scale spatial resolution enables reconstruction of the complex dielectric tensor of individual multilayer crystals. Ti 3 C 2 Cl 2 exhibits a type-II hyperbolicity above 930 nm, whereas h-MXenes do not display hyperbolicity within the measured 300–1700 nm window, instead showing reduced in-plane conductivity, suppressed out-of-plane light absorption, and a chain-length-dependent blue shift of a near-infrared absorption feature. These results demonstrate topochemical surface modification as a direct handle for engineering MXenes as surface-programmable optical media.

Hybrid materials↗
DOE OSTI2017

Lattice Mismatch in Crystalline Nanoparticle Thin Films

For atomic thin films, lattice mismatch during heteroepitaxy leads to an accumulation of strain energy, generally causing the films to irreversibly deform and generate defects. In contrast, more elastically malleable building blocks should be better able to accommodate this mismatch and the resulting strain. In our work, that hypothesis is tested by utilizing DNA-modified nanoparticles as “soft,” programmable atom equivalents to grow a heteroepitaxial colloidal thin film. Calculations of interaction potentials, small-angle X-ray scattering data, and electron microscopy images show that the oligomer corona surrounding a particle core can deform and rearrange to store elastic strain up to ±7.7% lattice mismatch, substantially exceeding the ±1% mismatch tolerated by atomic thin films. Importantly, these DNA-coated particles dissipate strain both elastically through a gradual and coherent relaxation/ broadening of the mismatched lattice parameter and plastically (irreversibly) through the formation of dislocations or vacancies. These data also suggest that the DNA cannot be extended as readily as compressed, and thus the thin films exhibit distinctly different relaxation behavior in the positive and negative lattice mismatch regimes. These observations provide a more general understanding of how utilizing rigid building blocks coated with soft compressible polymeric materials can be used to control nano- and microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reconfigurable Liquids Stabilized by DNA Surfactants

Polyelectrolyte microcapsules can be produced either by the layer-by-layer assembly technique or the formation of polyelectrolyte complexes at the liquid-liquid interface. In this work, we describe the design and construction of DNA microcapsules using the cooperative assembly of DNA and amine-functionalized polyhedral oligomeric silsesquioxane (POSS-NH 2 ) at the oil-water interface. "Janus-like" DNA surfactants (DNASs) assemble in situ at the interface, forming an elastic film. By controlling the jamming and unjamming behavior of DNASs, the interfacial assemblies can assume three different physical states: solid-like, elastomer-like, and liquid-like, similar to that seen with thermoplastics upon heating, that change from a glassy to a rubbery state, and then to a viscous liquid. By the interfacial jamming of DNASs, the liquid structures can be locked-in and reconfigured, showing promising potentials for drug delivery, biphasic reactors, and programmable liquid constructs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

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

Assembly of Metalloporphyrin Peptoids into Crystalline Nanomaterials as a Multifunctional System for Biomimetic Catalysis and Sensing

While natural enzymes excel at catalysis and sensing, they often suffer from high cost and low stability in applications outside living systems. Among tremendous efforts made toward the design and synthesis of catalytic biomimetic materials, the approach of using crystalline nanomaterials assembled from sequence-defined polymers has emerged as a promising strategy. Herein, we report the assembly of metalloporphyrin peptoids into crystalline nanomaterials as a multifunctional system for biomimetic catalysis and sensing. The precise spatial positioning of covalently attached porphyrins within crystalline peptoid nanomaterials enables the mimicry of several enzyme active sites, including phosphotriesterase and horseradish peroxidase, for efficient catalytic hydrolysis and oxidation reactions. Additionally, the high programmability of these peptoid crystalline materials enables the creation and tuning of the active site microenvironment for enhanced catalytic activity. We further demonstrate the integration of responsive organic dyes into catalytic peptoid assemblies to achieve both detection and degradation of chemical warfare agent (CWA) mimics, even in the vapor phase. In conclusion, we expect this multifunctional system to provide tremendous opportunities in biomimetic catalysis and sensing, including the detoxification and detection of CWAs.

Catalysts↗
DOE OSTI2019

Oxygen-Induced In Situ Manipulation of the Interlayer Coupling and Exciton Recombination in Bi 2 Se 3 /MoS 2 2D Heterostructures

Two-dimensional (2D) heterostructures are more than a sum of the parent 2D materials, but are also a product of the interlayer coupling, which can induce new properties. In this paper, we present a method to tune the interlayer coupling in Bi 2 Se 3 /MoS 2 2D heterostructures by regulating the oxygen presence in the atmosphere, while applying laser or thermal energy. Our data suggest that the interlayer coupling is tuned through the diffusive intercalation and deintercalation of oxygen molecules. When one layer of Bi 2 Se 3 is grown on monolayer MoS 2 , an influential interlayer coupling is formed, which quenches the signature photoluminescence (PL) peaks. However, thermally treating in the presence of oxygen disrupts the interlayer coupling, facilitating the emergence of the MoS 2 PL peak. Our density functional theory calculations predict that intercalated oxygen increases the interlayer separation ∼17%, disrupting the interlayer coupling and inducing the layers to behave more electronically independent. The interlayer coupling can then be restored by thermally treating in N 2 or Ar, where the peaks will requench. Hence, this is an interesting oxygen-induced switching between “non-radiative” and “radiative” exciton recombination. This switching can also be accomplished locally, controllably, and reversibly using a low-power focused laser, while changing the environment from pure N 2 to air. This allows for the interlayer coupling to be precisely manipulated with submicron spatial resolution, facilitating site-programmable 2D light-emitting pixels whose emission intensity could be precisely varied by a factor exceeding 200×. Our results show that these atomically thin 2D heterostructures may be excellent candidates for oxygen sensing.

2D materials↗
DOE OSTI2026

Grand Challenges and Opportunities in Stimulated Dynamic and Resonant Catalysis

Traditional heterogeneous catalysis is constrained by kinetic and thermodynamic limits, such as the Sabatier principle and reaction equilibrium. Dynamic and resonant catalysts hold promise to overcome these limitations by actively oscillating a catalyst’s physical or electronic structure at the time scale of the catalytic cycle, allowing programmable control over reaction pathways, and leading to improved rate and selectivity. External stimuli such as temperature swing, mechanical strain, electric charge, and light can perturb catalyst surfaces in different ways, altering adsorbate coverage, binding energies, and transition states beyond what steady-state catalysis allows. This work surveys the current state of dynamic catalysis, introduces the concept of “ stimulando ” characterization for observing transient dynamics, and outlines key modeling, mechanistic, and benchmarking strategies to advance the field toward improved chemical transformation.

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

First-Principles Insights into the Thermodynamics of Variable-Temperature Ammonia Synthesis on Transition-Metal-Doped Cu (100) and (111)

Ammonia (NH 3 ) is one of the most produced chemicals worldwide. NH 3 synthesis predominantly utilizes the Haber–Bosch (HB) process, requiring high temperatures and pressures. Despite significant process advances, ample opportunity remains for improving the rate, selectivity, catalyst stability, and energy efficiency. Inspired by a recently developed programmable heating and quenching (PHQ) technique, we present in this paper a first-principles screening of candidate single-atom alloy catalysts generated from doping (111) and (100) surfaces of copper (Cu), an ineffective HB catalyst in its pure form. We predict the thermodynamics of two rate-limiting reactions, N 2 dissociative adsorption and the final hydrogenation step leading up to NH 3 release, at 400 and 900 K. Thermodynamically, the former reaction is favored at low temperatures, while the latter is favored at high temperatures. Vanadium-, chromium-, and molybdenum-doped Cu surfaces, due to intermediate M–N covalent bonding character, emerge as appealing candidate catalysts for PHQ NH 3 synthesis, as they balance the thermodynamics of the above-mentioned reaction steps at their respective optimal temperatures.

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

NMR Studies of Block Copolymer-Based Supramolecules in Solution

Hierarchical assemblies from block copolymer (BCP)-based supramolecules have shown immense potential as programmable materials owing to their versatility for incorporating functional molecules and provide access to arrays of hierarchical structures. However, there remains a knowledge gap on the formation of the supramolecule in solution. Here, we applied NMR techniques to investigate the solution-phase behavior of the most studied supramolecular systems, polystyrene-block-poly(4-vinylpyridine)(3-pentadecylphenol) (PS-b-P4VP(PDP) r ). The results show that the supramolecule likely adopts a coil-comb conformation, despite the small molecule's (PDP) rapid exchange between the bonded and free states. The exchange rate (>10 4 s -1 ) exceeds the NMR time scale at the frequency of interest. The supramolecules form under dilute conditions (~2 vol %) and are attributed to the enthalpic gain of the hydrogen bonding between the PDP and 4VP. As the solute concentration increases (>10 vol %), the supramolecule forms micelle-like aggregates with PDP accumulated within the comb-block's pervaded volume based on analysis of the apparent molecular weight, viscosity, and chain dynamics. Overall, this work sheds light on the long-standing question regarding the evolution of the constituents in the BCP-based supramolecule in solution and provides valuable guidance toward their solution-based processing and morphological control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Highly Bright and Photostable Two-Dimensional Nanomaterials Assembled from Sequence-Defined Peptoids

Free-standing two-dimensional (2D) organic nanomaterials are highly attractive for biological applications because of their unique structural properties and high biocompatibility. Herein, we designed and synthesized a new class of highly bright and photostable membrane-mimetic 2D nanosheets from sequence-defined peptoids. These nanosheets exhibited the high quantum yield and photostability as a result of the precise placement and ordering of dansyl dye molecules within crystalline nanosheets. We further showed the use of these nanosheets as biocompatible and programmable probes for live cell imaging and cell labeling. Furthermore, by programing these nanosheets with different surface charges, we achieved the enhanced lysosome escape of these nanosheets, showing their great potential as nanocarriers for the efficient intracellular delivery of macromolecular drugs.

2D nanomaterials↗
DOE OSTI2025

Supramolecular Control of Ionic Retention in Electrolyte-Gated Synaptic Transistors

Electrolyte-gated transistors with ion-trapping layers offer a promising platform for artificial synapses in neuromorphic computing, yet molecular mechanisms governing ionic retention remain poorly understood. Here, in this study, we present a supramolecular approach to modulate ion retention by incorporating a crown ether derivative-based polymer network as an ion-trapping layer on top of a semiconducting monolayer. We show that the balance between ion–host binding and ion–solvent interactions dictates the kinetics of ion capture and release, which in turn controls the memory characteristics of the device. By varying the solvent dielectric constant, we tune the ionic retention time from nearly permanent trapping to rapid relaxation. Intermediate solvent polarity enables programmable short- and long-term synaptic behaviors, including excitatory postsynaptic current, paired-pulse facilitation, and long-term potentiation and depression. These findings establish a direct link between supramolecular ion recognition and synaptic plasticity and provide a generalizable design strategy for ionic–electronic neuromorphic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Engineering Edge States of Graphene Nanoribbons for Narrow-Band Photoluminescence

Solid-state narrow-band light emitters are on-demand for quantum optoelectronics. Current approaches based on defect engineering in low-dimensional materials usually introduce a broad range of emission centers. Here, we report narrow-band light emission from covalent heterostructures fused to the edges of graphene nanoribbons (GNRs) by controllable on-surface reactions from molecular precursors. Two types of heterojunction (HJ) states are realized by sequentially synthesizing GNRs and graphene nanodots (GNDs) and then coupling them together. HJs between armchair GNDs and armchair edges of the GNR are coherent and give rise to narrow-band photoluminescence. In contrast, HJs between the armchair GNDs and the zigzag ends of GNRs are defective and give rise to nonradiative states near the Fermi level. At low temperatures, sharp photoluminescence emissions with peak energy range from 2.03 to 2.08 eV and line widths of 2–5 meV are observed. Furthermore, the radiative HJ states are uniform, and the optical transition energy is controlled by the band gaps of GNRs and GNDs. As these HJs can be synthesized in a large quantity with atomic precision, this finding highlights a route to programmable and deterministic creation of quantum light emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reconfiguring DNA Nanotube Architectures via Selective Regulation of Terminating Structures

Molecular assemblies inside cells often undergo structural reconfiguration in response to stimuli to alter their function. Adaptive reconfiguration of cytoskeletal networks, for example, enables cellular shape change, movement, and cargo transport and plays a key role in driving complex processes such as division and differentiation. The cellular cytoskeleton is a self-assembling polymer network composed of simple filaments, so reconfiguration often occurs through the rearrangement of its component filaments’ connectivities. DNA nanotubes have emerged as promising building blocks for constructing programmable synthetic analogs of cytoskeletal networks. Nucleating seeds can control when and where nanotubes grow and capping structures can bind nanotube ends to stop growth. Such seeding and capping structure, collectively called termini, can organize nanotubes into larger architectures. However, these structures cannot be selectively activated or inactivated in response to specific stimuli to rearrange nanotube architectures, a key property of cytoskeletal networks. Here we demonstrate how selective regulation of the binding affinity of DNA nanotube termini for DNA nanotube monomers or nanotube ends can direct the reconfiguration of nanotube architectures. Using DNA hybridization and strand displacement reactions that specifically activate or inactivate four orthogonal nanotube termini, we demonstrate that nanotube architectures can be reconfigured by selective addition or removal of unique termini. Lastly, we show how terminus activation could be a sensitive detector and amplifier of a DNA sequence signal. These results could enable the development of adaptive and multifunctional materials or diagnostic tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Elucidation of Peptide-Directed Palladium Surface Structure for Biologically Tunable Nanocatalysts

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, which was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then eluddated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences

atomic pair distribution function↗
DOE OSTI2015

Modulating the Bond Strength of DNA–Nanoparticle Superlattices

In this work, a method is introduced for modulating the bond strength in DNA–programmable nanoparticle (NP) superlattice crystals. This method utilizes noncovalent interactions between a family of [Ru(dipyrido[2,3-a:3',2'-c]phenazine)(N–N) 2 ] 2+ -based small molecule intercalators and DNA duplexes to postsynthetically modify DNA–NP superlattices. This dramatically increases the strength of the DNA bonds that hold the nanoparticles together, thereby making the superlattices more resistant to thermal degradation. In this work, we systematically investigate the relationship between the structure of the intercalator and its binding affinity for DNA duplexes and determine how this translates to the increased thermal stability of the intercalated superlattices. We find that intercalator charge and steric profile serve as handles that give us a wide range of tunability and control over DNA–NP bond strength, with the resulting crystal lattices retaining their structure at temperatures more than 50 °C above what nonintercalated structures can withstand. This allows us to subject DNA–NP superlattice crystals to conditions under which they would normally melt, enabling the construction of a core–shell (gold NP-quantum dot NP) superlattice crystal.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗