Resilient three-dimensional ordered architectures assembled from nanoparticles by DNA
Resilient silica-nanoparticle lattices organized by DNA withstand harsh temperature, pressure and radiation conditions.
3D mineralization↗
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Results for “Architectural nanomaterials”
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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Plasma-Enhanced Atomic Layer Deposition Synthesis of Nanolayered Molybdenum Diselenide (MoSe 2 ) Thin Films for Nanoelectronics
Nanolayered molybdenum diselenide (MoSe 2 ) thin films were synthesized by plasma-enhanced atomic layer deposition (PE-ALD) using molybdenum pentachloride (MoCl 5 ) and diethyldiselenide (C 4 H 10 Se 2 ) precursors. Scanning and transmission electron microscopy revealed horizontally stacked nanolayers near the substrate and vertically oriented nanosheets at the surface of the film. X-ray diffraction confirmed the (002), (100), and (110) reflections of crystalline MoSe 2 , while X-ray photoelectron spectroscopy showed relative atomic concentrations of 33.5% Mo and 66.5% Se, consistent with stoichiometric MoSe 2 . Raman spectra exhibited characteristic E 1g , A 1g , and E$^1_{2g}$ vibrational modes. Field-effect transistors incorporating PE-ALD-grown MoSe 2 as the channel material displayed p-type behavior, demonstrating the potential of nanolayered MoSe 2 for nanoelectronic applications. This work demonstrates the feasibility of low-temperature, stoichiometric growth of nanolayered MoSe 2 by PE-ALD and its direct integration into transistor architectures.
36 MATERIALS SCIENCE↗
VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities
Scientific user facilities, such as synchrotron beamlines, are equipped with a wide array of hardware and software tools that require a codebase for human-computer-interaction. This often necessitates developers to be involved to establish connection between users/researchers and the complex instrumentation. The advent of generative AI presents an opportunity to bridge this knowledge gap, enabling seamless communication and efficient experimental workflows. Here we present a modular architecture for the Virtual Scientific Companion by assembling multiple AI-enabled cognitive blocks that each scaffolds large language models (LLMs) for a specialized task. With VISION, we performed LLM-based operation on the beamline workstation with low latency and demonstrated the first voice-controlled experiment at an x-ray scattering beamline. The modular and scalable architecture allows for easy adaptation to new instruments and capabilities. Development on natural language-based scientific experimentation is a building block for an impending future where a science exocortex—a synthetic extension to the cognition of scientists—may radically transform scientific practice and discovery.
36 MATERIALS SCIENCE↗
Carbon nanomaterials–polymer composites for perovskite solar cells: preparation, properties and applications
Perovskite solar cells (PSCs) are a rising star in the photovoltaic industry, which achieved an enormous breakthrough in terms of efficiency from an initial 3.8% in 2009 to 25.7% in 2021. Here, the major challenge to bring perovskite solar cells commercially available is the poor long-term device stability. The defects in perovskite and energy loss originating from charge recombination limit the efficiency of perovskite solar cells. Carbon–polymer composites, which feature superb electrical conductivity, outstanding carrier mobility, remarkable flexibility and superior heat and moisture stability, have attracted considerable attention to tackle these issues. With their multifunctional properties, carbon–polymer composites can play various roles in almost every component in the perovskite solar cell architecture. In this review article, recent progress concerning the utilization of carbon–polymer composites in different components in PSCs (i.e., perovskite additives, electrodes, encapsulation layers and charge transport layers) is comprehensively overviewed. Then, future research directions and opportunities toward high-performance perovskite solar cells utilizing carbon–polymer composites are presented.
36 MATERIALS SCIENCE↗
All 2D Material Printed Diodes and Circuits on Paper for Sustainable Electronics
Sustainable electronics aim to reduce environmental impact by using ecofriendly materials, energy-efficient manufacturing, and recyclable components. However, existing approaches rely on complex, resource-intensive methods, rare metals, or nanomaterials with limited stability as well as plastic substrates, raising sustainability issues. Solution-processed two-dimensional (2D) materials offer a promising alternative: water-based and biocompatible conductive, semiconductive, and insulating 2D material inks can be produced with scalable techniques and are suitable for the fabrication of fully printed devices on low-cost and biodegradable paper substrates. However, 2D material only and fully printed diodes on paper have not yet been reported. Here, we demonstrate fully inkjet-printed 2D material-based diodes on paper using metal-insulator-semiconductor and metal-insulator-metal-semiconductor architectures. Water-based graphene and MoS2 inks, prepared by liquid-phase exfoliation, are used for the metallic and insulating films, while electrochemical exfoliation is used to produce the semiconducting MoS2 ink. The highest forward-to-reverse current ratio obtained is 330 (at ±2 V), while the forward current density is 1 mA/cm2 (at 1 V), making the diode performance comparable to the best solution-processed diodes reported so far. However, in contrast to previous works, fabrication occurs entirely at room temperature and ambient pressure, without using high-pressure sputtering, thermal evaporation, and any precious metal ink. The devices maintain stable performance under bending up to strain of 4% over 10,000 cycles. Finally, the diodes are successfully integrated with other 2D-material based electrical components to realize fully printed RC circuits, differentiators, integrators, and AC-to-DC converters onto paper, hence demonstrating the suitability of our approach for sustainable and disposable integrated circuits.
2D materials↗
Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation
Here, extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) in its most recent shadow potential energy version has been implemented in the semiempirical PyTorch-based software PySeQM. The implementation includes finite electronic temperatures, canonical density matrix perturbation theory, and an adaptive Krylov subspace approximation for the integration of the electronic equations of motion within the XL-BOMB approach (KSA-XL-BOMD). The PyTorch implementation leverages the use of GPU and machine learning hardware accelerators for the simulations. The new XL-BOMD formulation allows studying more challenging chemical systems with charge instabilities and low electronic energy gaps. The current public release of PySeQM continues our development of modular architecture for large-scale simulations employing semi-empirical quantum-mechanical treatment. Applied to molecular dynamics, simulation of 840 carbon atoms, one integration time step executes in 4 s on a single Nvidia RTX A6000 GPU.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structural and compositional complexities of hierarchical self-assembly: A hypergraph approach
Programmable self-assembly enables the construction of complex molecular, supramolecular, and crystalline architectures from well-designed building blocks. In this work, we introduce a hypergraph-based formalism, Blocks & Bonds (B&B), which generalizes classical chemical graph theory by incorporating directed and multicolored interactions, internal symmetries, and hierarchical organization. Within this framework, we develop the Structure Code (SC), a compact and versatile language for describing self-assembled architectures. We define a Kolmogorov-style structural complexity as the total information content of SC, obtained through its tokenization and Shannon information assignment. Complementing this encoding-based measure, we introduce a much simpler quantity, the compositional complexity, which depends only on the number and cumulative usage of block and bond types in the construction set. A central result of this work is a strong empirical correlation between the token-based structural complexity and the compositional complexity across all examined systems. Owing to this agreement, the compositional complexity emerges as the most practical and broadly applicable measure: it is easy to compute, requires no explicit encoding, and yet closely tracks the actual information content of structurally diverse architectures. Applications to molecular systems (ethylene glycol and glucose), DNA-origami lattices, and crystalline assemblies show that B&B hypergraphs provide a unified, scalable, and information-efficient representation of structural organization, naturally capturing symmetry, modularity, and stereochemistry. This framework establishes a quantitative foundation for complexity-aware classification and inverse design of programmable matter.
36 MATERIALS SCIENCE↗
New Directions in Focused Ion Beam Induced Deposition for the Nanoprinting of Functional 3D Heterostructures
The focused ion beam (FIB) microscope is well established as a high-resolution machining instrument capable of site-selectively removing material down to the nanoscale. Beyond subtractive processing, however, the FIB can also add material via a technique known as focused ion beam induced deposition (FIBID). Using FIBID, the FIB can thus be employed for the direct-write of complex nanostructures. This work explores new directions in three-dimensional FIBID nanoprinting, harnessing unique features of helium and neon FIBs. In particular, the superior spatial resolution of these novel FIBs is leveraged to fabricate precise multimaterial architectures, an isotope effect is used to create satellite deposits, and dose-controlled implantation of the gaseous ions is used to engineer internal voids. In the context of voids, the fabrication of hollow nanopillars by helium-FIBID due to concurrent milling (as shown previously by others) is revisited. Insight into the chemical and structural composition of the nanostructures is obtained using advanced electron microscopy, accurately revealing buried interfaces, crystallite distributions, chemical compositions, and material transformations. Next-generation devices and technologies that could be enabled by the novel heterostructures demonstrated here are discussed, setting the stage for the potential evolution of FIBID into a versatile platform for functional nanomaterials design and fabrication.
FIBID↗
Nanomaterials for Electronics and Optoelectronics
Nanomaterials such as carbon nanotubes(CNTs), graphene, and inorganic nanowires(INWs) have shown interesting electronic, mechanical, optical, thermal, and other properties and therefore have been pursued for a variety of applications by the nanotechnology community ranging from electronics to nanocomposites. While the first two are carbon-based materials, the INWs in the literature include silicon, germanium, III-V, II-VI, a variety of oxides, nitrides, antimonides and others. In this talk, first an overview of growth of these three classes of materials by CVD and PECVD will be presented along with results from characterization. Then applications in development of chemical sensors, biosensors, energy storage devices and novel memory architectures will be discussed.
Koehne, Jessica E.↗
Two-Stage Assembly of Nanoparticle Superlattices with Multiscale Organization
Self-assembly processes, while promising for enabling the fabrication of complexly organized nanomaterials from nanoparticles, are often limited in creating structures with multiscale order. These limitations are due to difficulties in practically realizing the assembly processes required to achieve such complex organizations. For a long time, a hierarchical assembly attracted interest as a potentially powerful approach. However, due to the experimental limitations, intermediate-level structures are often heterogeneous in composition and structure, which significantly impacts the formation of large-scale organizations. Here, we introduce a two-stage assembly strategy: DNA origami frames scaffold a coordination of nanoparticles into designed 3D nanoclusters, and then these clusters are assembled into ordered lattices whose types are determined by the clusters’ valence. Through modulating the nanocluster architectures and intercluster bindings, we demonstrate the successful formation of complexly organized nanoparticle crystals. To conclude, the presented two-stage assembly method provides a powerful fabrication strategy for creating nanoparticle superlattices with prescribed unit cells.
36 MATERIALS SCIENCE↗
Nanoshell quantum dots: Quantum confinement beyond the exciton Bohr radius
Nanoshell quantum dots (QDs) represent a novel class of colloidal semiconductor nanocrystals (NCs), which supports tunable optoelectronic properties over the extended range of particle sizes. Traditionally, the ability to control the bandgap of colloidal semiconductor NCs is limited to small-size nanostructures, where photoinduced charges are confined by Coulomb interactions. A notorious drawback of such a restricted size range concerns the fact that assemblies of smaller nanoparticles tend to exhibit a greater density of interfacial and surface defects. This presents a potential problem for device applications of semiconductor NCs where the charge transport across nanoparticle films is important, as in the case of solar cells, field-effect transistors, and photoelectrochemical devices. Furthermore, the morphology of nanoshell QDs addresses this issue by enabling the quantum-confinement in the shell layer, where two-dimensional excitons can exist, regardless of the total particle size. Such a geometry exhibits one of the lowest surface-to-volume ratios among existing QD architectures and, therefore, could potentially lead to improved charge-transport and multi-exciton characteristics. The expected benefits of the nanoshell architecture were recently demonstrated by a number of reports on the CdS bulk /CdSe nanoshell model system, showing an improved photoconductivity of solids and increased lifetime of multi-exciton populations. Along these lines, this perspective will summarize the recent work on CdS bulk /CdSe nanoshell colloids and discuss the possibility of employing other nanoshell semiconductor combinations in light-harvesting and lasing applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Nanostructured C@CuS Core–Shell Framework with High Lithium-Ion Storage Performance
In this study, we have synthesized a nanostructured core–shell framework of carbon-coated copper sulfide (C@CuS) through a one-step precipitation technique. The carbon sphere template facilitated the nucleation of CuS nanostructures. The synthesized nanocomposites have demonstrated remarkable lithium-ion storage capabilities when utilized as an anode in lithium-ion batteries. Notably, they exhibit an impressive rate capability of 314 mAh g -1 at a high current density of 5000 mA g -1 , along with excellent long-term cycle stability, maintaining 463 mAh g -1 at 1000 mA g -1 after 800 cycles. This superior performance is due to the core–shell architecture of the composite, where the carbon core enhances the conductivity of CuS nanoparticles and mitigates volume expansion, thus preventing capacity loss. Our study not only elucidates the significance of carbon in the construction of nano-heterojunctions or composite electrodes but also presents a practical approach to significantly boost the electrochemical performance of CuS and other metal sulfides.
25 ENERGY STORAGE↗
Investigation on the AgPt and AgPd hybrid alloy nanoparticles (HANPs) for the hybrid MoS 2 /ZnO/HANP UV photodetector application
We report hybrid photodetectors made of two or more nanomaterial components can offer the high potential for advanced photodetection applications with enhanced light absorption, improved efficiency and structural tunability. A hybrid UV photodetector (PD) configuration incorporating the plasmonic hybrid alloy nanoparticles (HANP), ZnO quantum dots (QDs) and MoS 2 nanoflakes, namely MoS2/ZnO/HANP PD, is demonstrated. The optimized MoS 2 /ZnO/HANP PD exhibits a high photocurrent of 5.66 mA at 0.34 mW/mm 2 under 385 nm illumination with two orders of improvement from the bare ZnO, which is one of the highest photocurrents by the ZnO-based PDs. It also demonstrates high figure-of-merits with the responsivity of 14,523 mA/W, detectivity of 8.13 x 10 11 jones, and external quantum efficiency (EQE) of 4,680 %, outperforming most of the ZnO-based hybrid architectures. The enhanced photoresponse is primarily attributed to the significantly enhanced hot electron generation by the AgPd HANPs and photocarrier collection through the ZnO QD layer. MoS 2 nanoflakes also provide additional photon absorption sites and boost the photo-carrier transfer process. HANPs are grown by adapting a dual-step solid-state dewetting process (SSD) approach and the superiority of AgPd HANPs is confirmed by systematic investigation, FDTD simulation and comparison of AgPt and AgPd HANPs.
MoS2↗
MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics
Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.
08 HYDROGEN↗
Discovering polyelemental nanostructures with redistributed plasmonic modes through combinatorial synthesis
Coupling plasmonic and functional materials provides a promising way to generate multifunctional structures. However, finding plasmonic nanomaterials and elucidating the roles of various geometric and dielectric configurations are tedious. This work describes a combinatorial approach to rapidly exploring and identifying plasmonic heteronanomaterials. Symmetry-broken noble/non-noble metal particle heterojunctions (~100 nanometers) were synthesized on multiwindow silicon chips with silicon nitride membranes. The metal types and the interface locations were controlled to establish a nanoparticle library, where the particle morphology and scattering color can be rapidly screened. By correlating structural data with near- and far-field single-particle spectroscopy data, we found that certain low-energy plasmonic modes could be supported across the heterointerface, while others are localized. Furthermore, we found a series of triangular heteronanoplates stabilized by epitaxial Moiré superlattices, which show strong plasmonic responses despite largely comprising a lossy metal (~70 atomic %). These architectures can become the basis for multifunctional and cost-effective plasmonic devices.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors
Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.
60 APPLIED LIFE SCIENCES↗
Molecular Design Principles for Photosystem I-Based Biohybrid Solar Fuel Catalysts
Direct solar-to-chemical conversion offers a compelling route to clean, dispatchable energy. Photosystem I (PSI), an evolutionarily optimized light-driven oxidoreductase, can be repurposed for solar-fuel production by coupling its photochemistry to catalytic interfaces. However, the molecular determinants that govern productive electron transfer to abiotic catalysts remain poorly understood. Here, we present molecular structures of active PSI-Pt nanoparticle (PtNP) biohybrids that reveal how protein architecture controls catalyst access, binding geometry, and photocatalytic efficiency. Removal of stromal subunits exposes the electron transfer chain and enables PtNP binding proximal to the F X cluster, demonstrating that steric occlusion limits access to native acceptor regions in PSI. In contrast, in trimeric PSI, PtNPs bind at multiple sites per monomer, but only a subset are positioned within electron transfer distance of terminal cofactors, resulting in a heterogeneous population of productive and nonproductive configurations. Structural analyses and molecular dynamics simulations define the interface topology, electrostatics, and cofactor-to-nanoparticle distances that govern catalyst binding and electron transfer. These results establish that catalytic inefficiency arises not only from intrinsic electron transfer constraints but also from the distribution of binding geometries imposed by the protein scaffold. Together, these findings provide a molecular framework linking protein structure to biohybrid function and define design principles for engineering PSI-based solar fuel systems and protein-nanomaterial interfaces for light-driven catalysis.
biohybrid↗
Low-Temperature Catalyst Redispersion: A Route to Enhanced Stability of Supported Metal Catalysts?
Sintering poses a significant challenge to achieving the long-term stability of supported metal catalysts under reaction conditions. Here, in this study, we report a low-temperature catalyst redispersion mechanism, in which platinum single atoms, which aggregate into nanoparticles under Reverse Water Gas Shift (RWGS) conditions at elevated temperatures, fragment into atomically dispersed species upon cooling. Using multimodal operando characterization combined with first-principles theoretical modeling, we track the structural evolution of Pt single atoms supported on ceria nanodomes, deposited either on ceria or ceria–titania mixed oxides. We find that fragmentation is more pronounced when cooling occurs under RWGS conditions compared to CO alone, owing to a synergistic interplay of the effects of H 2 , CO 2 , and CO. The support architecture has a strong influence on the extent of redispersion: while CO alone induces fragmentation on ceria, interfacial confinement and vacancy pinning at the ceria–titania interface suppress restructuring. In contrast, RWGS conditions overcome these barriers, enabling redispersion across both supports. These findings point toward a pathway for catalyst stabilization via reaction-induced redispersion under mild conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗