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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nanoscale cooperative adsorption for materials control

Abstract Adsorption plays vital roles in many processes including catalysis, sensing, and nanomaterials design. However, quantifying molecular adsorption, especially at the nanoscale, is challenging, hindering the exploration of its utilization on nanomaterials that possess heterogeneity across different length scales. Here we map the adsorption of nonfluorescent small molecule/ion and polymer ligands on gold nanoparticles of various morphologies in situ under ambient solution conditions, in which these ligands are critical for the particles’ physiochemical properties. We differentiate at nanometer resolution their adsorption affinities among different sites on the same nanoparticle and uncover positive/negative adsorption cooperativity, both essential for understanding adsorbate-surface interactions. Considering the surface density of adsorbed ligands, we further discover crossover behaviors of ligand adsorption between different particle facets, leading to a strategy and its implementation in facet-controlled synthesis of colloidal metal nanoparticles by merely tuning the concentration of a single ligand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Highly stable and tunable peptoid/hemin enzymatic mimetics with natural peroxidase-like activities

Abstract Developing tunable and stable peroxidase mimetics with high catalytic efficiency provides a promising opportunity to improve and expand enzymatic catalysis in lignin depolymerization. A class of peptoid-based peroxidase mimetics with tunable catalytic activity and high stability is developed by constructing peptoids and hemins into self-assembled crystalline nanomaterials. By varying peptoid side chain chemistry to tailor the microenvironment of active sites, these self-assembled peptoid/hemin nanomaterials (Pep/hemin) exhibit highly modulable catalytic activities toward two lignin model substrates 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and 3,3’,5,5’-tetramethylbenzidine. Among them, a Pep/hemin complex containing the pyridyl side chain showed the best catalytic efficiency ( V max / K m = 5.81 × 10 −3 s −1 ). These Pep/hemin catalysts are highly stable; kinetics studies suggest that they follow a peroxidase-like mechanism. Moreover, they exhibit a high efficacy on depolymerization of a biorefinery lignin. Because Pep/hemin catalysts are highly robust and tunable, we expect that they offer tremendous opportunities for lignin valorization to high value products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Magnetic control over the fundamental structure of atomic wires

When reducing the size of materials towards the nanoscale, magnetic properties can emerge due to structural variations. Here, we show the reverse effect, where the structure of nanomaterials is controlled by magnetic manipulations. Using the break-junction technique, we find that the interatomic distance in platinum atomic wires is shorter or longer by up to ~20%, when a magnetic field is applied parallel or perpendicular to the wires during their formation, respectively. The magnetic field direction also affects the wire length, where longer (shorter) wires are formed under a parallel (perpendicular) field. Our experimental analysis, supported by calculations, indicates that the direction of the applied magnetic field promotes the formation of suspended atomic wires with a specific magnetization orientation associated with typical orbital characteristics, interatomic distance, and stability. A similar effect is found for various metal and metal-oxide atomic wires, demonstrating that magnetic fields can control the atomistic structure of different nanomaterials when applied during their formation stage.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing the atomically diffuse interfaces in Pd@Pt core-shell nanoparticles in three dimensions

Deciphering the three-dimensional atomic structure of solid-solid interfaces in core-shell nanomaterials is the key to understand their catalytical, optical and electronic properties. Here, we probe the three-dimensional atomic structures of palladium-platinum core-shell nanoparticles at the single-atom level using atomic resolution electron tomography. We quantify the rich structural variety of core-shell nanoparticles with heteroepitaxy in 3D at atomic resolution. Instead of forming an atomically-sharp boundary, the core-shell interface is found to be atomically diffuse with an average thickness of 4.2 Å, irrespective of the particle’s morphology or crystallographic texture. The high concentration of Pd in the diffusive interface is highly related to the free Pd atoms dissolved from the Pd seeds, which is confirmed by atomic images of Pd and Pt single atoms and sub-nanometer clusters using cryogenic electron microscopy. These results advance our understanding of core-shell structures at the fundamental level, providing potential strategies into precise nanomaterial manipulation and chemical property regulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Beyond nothingness in the formation and functional relevance of voids in polymer films

Abstract Voids—the nothingness—broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Imaging atomic-scale chemistry from fused multi-modal electron microscopy

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic-resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark-field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)

Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗
DOE OSTI2023

Functional composites by programming entropy-driven nanosheet growth

Here, nanomaterials must be systematically designed to be technologically viable. Driven by optimizing intermolecular interactions, current designs are too rigid to plug in new chemical functionalities and cannot mitigate condition differences during integration. Despite extensive optimization of building blocks and treatments, accessing nanostructures with the required feature sizes and chemistries is difficult. Programming their growth across the nano-to-macro hierarchy also remains challenging, if not impossible. To address these limitations, we should shift to entropy-driven assemblies to gain design flexibility, as seen in high-entropy alloys, and program nanomaterial growth to kinetically match target feature sizes to the mobility of the system during processing. In tis report, following a micro-then-nano growth sequence in ternary composite blends composed of block-copolymer-based supramolecules, small molecules and nanoparticles, we successfully fabricate high-performance barrier materials composed of more than 200 stacked nanosheets (125 nm sheet thickness) with a defect density less than 0.056 µm -2 and about 98% efficiency in controlling the defect type. Contrary to common perception, polymer-chain entanglements are advantageous to realize long-range order, accelerate the fabrication process (<30 min) and satisfy specific requirements to advance multilayered film technology. This study showcases the feasibility, necessity and unlimited opportunities to transform laboratory nanoscience into nanotechnology through systems engineering of self-assembly.

42 ENGINEERING↗
DOE OSTI2020

Nano-engineering the material structure of preferentially oriented nano-graphitic carbon for making high-performance electrochemical micro-sensors

Direct synthesis of thin-film carbon nanomaterials on oxide-coated silicon substrates provides a viable pathway for building a dense array of miniaturized (micron-scale) electrochemical sensors with high performance. However, material synthesis generally involves many parameters, making material engineering based on trial and error highly inefficient. Here, we report a two-pronged strategy for producing engineered thin-film carbon nanomaterials that have a nano-graphitic structure. First, we introduce a variant of the metal-induced graphitization technique that generates micron-scale islands of nano-graphitic carbon materials directly on oxide-coated silicon substrates. A novel feature of our material synthesis is that, through substrate engineering, the orientation of graphitic planes within the film aligns preferentially with the silicon substrate. This feature allows us to use the Raman spectroscopy for quantifying structural properties of the sensor surface, where the electrochemical processes occur. Second, we find phenomenological models for predicting the amplitudes of the redox current and the sensor capacitance from the material structure, quantified by Raman. Our results indicate that the key to achieving high-performance micro-sensors from nano-graphitic carbon is to increase both the density of point defects and the size of the graphitic crystallites. Our study offers a viable strategy for building planar electrochemical micro-sensors with high-performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Photosynthetic semiconductor biohybrids for solar-driven biocatalysis

Photosynthetic semiconductor biohybrids integrate the best attributes of biological whole-cell catalysts and semiconducting nanomaterials. Enzymatic machinery enveloped in its native cellular environment offers exquisite product selectivity and low substrate activation barriers while semiconducting nanomaterials harvest light energy stably and efficiently. Here, we illustrate the evolution and advances of photosynthetic semiconductor biohybrids focusing on the conversion of CO 2 to value-added chemicals. We begin by considering the potential of this nascent field to meet global energy challenges while comparing it to alternate approaches. This is followed by a discussion of the advantageous coupling of electrotrophic organisms with light-active electrodes for solar-to-chemical conversion. We detail the dynamic investigation of photosensitized microorganisms creating direct light harvesting within unicellular organisms while describing complementary developments in the understanding of charge transfer mechanisms and cytoprotection. Lastly, we focus on trends and improvements needed in photosynthetic semiconductor biohybrids in order to address future challenges and enhance their widespread adoption for the production of solar chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. Here, in this study, we report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core–shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in fields such as biosensing, super-resolution microscopy and three-dimensional printing, can emit visible and ultraviolet light from near-infrared excitations. We report a large-scale dataset of UCNP emission spectra based on accurate but expensive kinetic Monte Carlo simulations (N > 6,000) and use these data to train a heterogeneous graph neural network using a physically motivated representation of UCNP nanostructure. Applying gradient-based optimization on the trained graph neural network, we identify structures with 6.5× higher predicted emission under 800-nm illumination than any UCNP in our training set. Our work reveals design principles for UCNP heterostructures and presents a roadmap for DL-based inverse design of nanomaterials.

Sivonxay, Eric [Lawrence Berkeley National Laborat↗
DOE OSTI2021

Hybrid magnetic nanoparticles as efficient nanoheaters in biomedical applications

Heating at the nanoscale is the basis of several biomedical applications, including magnetic hyperthermia therapies and heat-triggered drug delivery. The combination of multiple inorganic materials in hybrid magnetic nanoparticles provides versatile platforms to achieve an efficient heat delivery upon different external stimuli or to get an optical feedback during the process. However, the successful design and application of these nanomaterials usually require intricate synthesis routes and their magnetic response is still not fully understood. In this review we give an overview of the novel systems reported in the last few years, which have been mostly obtained by organic phase-based synthesis and epitaxial growth processes. Since the heating efficiency of hybrid magnetic nanoparticles often relies on the exchange-interaction between their components, we discuss various interface-phenomena that are responsible for their magnetic properties. Finally, followed by a brief comment on future directions in the field, we outline recent advances on multifunctional nanoparticles that can boost the heating power with light and combine heating and temperature sensing in a single nanomaterial.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Shell-mediated control of surface chemistry of highly stoichiometric magnetite nanoparticles

Magnetite (Fe 3 O 4 ) nanoparticles are one of the most studied nanomaterials for different nanotechnological and biomedical applications. However, Fe 3 O 4 nanomaterials gradually oxidize to maghemite (γ-Fe 2 O 3 ) under conventional environmental conditions leading to changes in their functional properties that determine their performance in many applications. Here we propose a novel strategy to control the surface chemistry of monodisperse 12 nm magnetite nanoparticles by means of a 3 nm-thick Zn-ferrite epitaxial coating in core/shell nanostructures. We have carried out a combined Mössbauer spectroscopy, dc magnetometry, X-ray photoelectron spectroscopy and spatially resolved electron energy loss spectroscopy study on iron oxide and Fe 3 O 4 /Zn 0.6 Fe 2.4 O 4 core/shell nanoparticles aged under ambient conditions for 6 months. Our results reveal that while the aged iron oxide nanoparticles consist of a mixture of γ-Fe 2 O 3 and Fe 3 O 4 , the Zn-ferrite-coating preserves a highly stoichiometric Fe 3 O 4 core. Therefore, the aged core/shell nanoparticles present a sharp Verwey transition, an increased saturation magnetization and the possibility of tuning the effective anisotropy through exchange-coupling at the core/shell interface. The inhibition of the oxidation of the Fe 3 O 4 cores can be accounted for in terms of the chemical nature of the shell layer and an epitaxial crystal symmetry matching between the core and the shell.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Atom vacancies and electronic transmission Stark effects in boron nanoflake junctions

Finite-sized boron nanomaterials have received little attention in comparison to their graphene-like 2D boron analogues. It is with systems of precise atomic structures where the electrical conductance can be most fruitfully analyzed at the fundamental level. To understand how conductance varies with respect to the electronic structure, and particularly with vacancies, we study finite-sized boron nanoflakes (BNFs) and closely examine their remarkable changes in physical properties. Unlike carbon-based materials, we find from non-equilibrium Green's functions density functional theory (NEGF-DFT) calculations that the charge transport of BNFs with 35–37 atoms is modulated by site-specific atomic vacancies. Here, the BNF with no vacancy (B 37 ) shows significantly lower conductivity (9.23 μS), than B 36 with one vacancy (46.1 μS), and lower still than with two vacancies (B 35 , 54.2 μS). From the thermopower function, these nanomaterials change from strong hole conductors to electron and back to hole conductors with the addition of each vacancy, from a doublet (B 37 ) to singlet (B 36 ) to doublet (B 35 ) ground state, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Synthesizing and formulating metal oxide nanoparticle inks for perovskite solar cells

The perovskite solar cell has commercial potential due to the low-cost of materials and manufacturing processes with cell efficiencies on par with traditional technologies. Nanomaterials have many properties that make them attractive for the perovskite devices, including low-cost inks, low temperature processing, stable material properties and good charge transport. In this feature article, the use of nanomaterials in the hole transport and electron transport layers are reviewed. Specifically, SnO 2 and NiO x are the leading materials with the most promise for translation to large scale applications. Here, the review includes a discussion of the synthesis, formulation, and processing of these nanoparticles and provides insights for their further deployment towards commercially viable perovskite solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗