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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Peptoid-Based Programmable 2D Nanomaterial Sensor for Selective and Sensitive Detection of H 2 S in Live Cells

During the past decades, a variety of two-dimensional (2D) nanosheets have been developed through supramolecular self-assembly. Among them, those assembled from sequence-defined molecules have received particularly attention because they enable a precise displaying of functional groups, including fluorescent dyes, within nanosheet surfaces. On the other hand, due to the fluorescence self-quenching, synthesis of organic 2D nanosheets exhibiting high fluorescence quantum yields is a significant challenge. Herein, we report the utilization of H 2 S-responsive probes as peptoid sidechains to design and synthesize crystalline 2D nanomembranes (2DNMs) as selective and sensitive H 2 S sensors. These 2DNM sensors exhibit a high quantum yield as a result of high crystallinity and tunable probe density. Compared with amorphous state of peptoid assembly and pre-assembled peptoid-probe conjugates, these crystalline 2DNM sensors exhibit a significantly strong fluorescence intensity and a high sensitivity (~ 0.36 nM). By sonication-cutting these 2DNM sensors into a colloidal form in aqueous solution, we further demonstrated the use of colloidal 2DNMs for detecting both exogenous and endogenous H 2 S inside cells or targeted cell organelles. As far as we know, this is the first example of using sequence-defined 2D nanomaterials for selective and sensitive detection of H 2 S. Because peptoids are biocompatible and peptoid-based 2DNMs are highly programmable, we expect that this new class of 2DNM sensors offer great potentials for detecting H 2 S and for biological applications.

2D nanomaterials↗
DOE OSTI2022

Programmable Photoluminescence via Intrinsic and DNA-Fluorophore Association in a Mixed Cluster Heterometallic MOF

In this report a rapid and facile design strategy to create a highly complex optical tag with programmable, multimodal photoluminescent properties is described. This was achieved via intrinsic and DNA-fluorophore hidden signatures. As a first covert feature of the tag, an intricate novel heterometallic near-infrared (NIR)-emitting mesoporous metal–organic framework (MOF) was designed and synthesized. The material is constructed from two chemically distinct, homometallic hexanuclear clusters based on Nd and Yb. Uniquely, the Nd-based cluster is observed here for the first time in a MOF and consists of two staggered Nd μ3-oxo trimers. To generate controlled, multimodal, and tailorable emission with difficult to counterfeit features, the NIR-emissive MOF was post-synthetically modified via a fluorescent DNA oligo labeling design strategy. The surface attachment of several distinct fluorophores, including the simultaneous attachment of up to three distinct fluorescently labeled oligos was achieved, with excitation and emission properties across the visible spectrum (480-800 nm). The DNA inclusion as a secondary covert element in the tag was demonstrated via the detection of SYBR Gold dye association. Importantly, the approach implemented here serves as a rapid and tailorable way to encrypt distinct information in a facile and modular fashion and provides an innovative technology in the quest toward complex optical tags.

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

Programmable Anisotropy and Percolation in Supramolecular Patchy Particle Gels

Patchy particle interactions are predicted to facilitate the controlled self-assembly and arrest of particles into phase-stable and morphologically tunable "equilibrium" gels, which avoids the arrested phase separation and subsequent aging that is typically observed in traditional particle gels with isotropic interactions. Despite these promising traits of patchy particle interactions, such tunable equilibrium gels have yet to be realized in the laboratory due to experimental limitations associated with synthesizing patchy particles in high yield. Here, we introduce a supramolecular metal-coordination platform consisting of metallic nanoparticles linked by telechelic polymer chains, which validates the predictions associated with patchy particle interactions and facilitates the design of equilibrium particle hydrogels through limited valency interactions. We demonstrate that the interaction valency and self-assembly of the particles can be effectively controlled by adjusting the relative concentration of polymeric linkers to nanoparticles, which enables the gelation of patchy particle hydrogels with programmable local anisotropy, morphology, and low mechanical percolation thresholds. Moreover, by crowding the local environment around the patchy particles with competing interactions, we introduce an independent method to control the self-assembly of the nanoparticles, thereby enabling the design of highly anisotropic particle hydrogels with substantially reduced percolation thresholds. We thus establish a canonical platform that facilitates multifaceted control of the self-assembly of the patchy nanoparticles en route to the design of patchy particle gels with tunable valencies, morphologies, and percolation thresholds. These advances lay important foundations for further fundamental studies of patchy particle systems and for designing tunable gel materials that address a wide range of engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Flexible and Extensive Platinum Ion Gel Condensers for Programmable Catalysis

Catalytic condensers composed of ion gels separating a metal electrode from a platinum-on-carbon active layer were fabricated and characterized to achieve more powerful, high surface area dynamic heterogeneous catalyst surfaces. Ion gels comprised of poly(vinylidene difluoride)/1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide were spin coated as a 3.8 μm film on a Au surface, after which carbon sputtering of a 1.8 nm carbon film and electron-beam evaporation of 2 nm Pt clusters created an active surface exposed to reactant gases. Electronic characterization indicated that most charge condensed within the Pt nanoclusters upon application of a potential bias, with the condenser device achieving a capacitance of ∼20 μF/cm 2 at applied frequencies of up to 120 Hz. The maximum charge of ∼10 14 |e – | cm –2 was condensed under stable device conditions at 200 °C on catalytic films with ∼10 15 sites cm –2 . Grazing incidence infrared spectroscopy measured carbon monoxide adsorption isobars, indicating a change in the CO* binding energy of ∼19 kJ mol –1 over an applied potential bias of only 1.25 V. Condensers were also fabricated on flexible, large area Kapton substrates allowing stacked or tubular form factors that facilitate high volumetric active site densities, ultimately enabling a fast and powerful catalytic condenser that can be fabricated for programmable catalysis applications.

Catalysis↗
DOE OSTI2017

Supra-Nanoparticle Functional Assemblies through Programmable Stacking

The quest for the by-design assembly of material and devices from nanoscale inorganic components is well recognized. Conventional self-assembly is often limited in its ability to control material morphology and structure simultaneously. We report a general method of assembling nanoparticles in a linear “pillar” morphology with regulated internal configurations. Our approach is inspired by supramolecular systems, where intermolecular stacking guides the assembly process to form diverse linear morphologies. Programmable stacking interactions were realized through incorporation of DNA coded recognition between the designed planar nanoparticle clusters. This resulted in the formation of multilayered pillar architectures with a well-defined internal nanoparticle organization. Furthermore, by controlling the number, position, size, and composition of the nanoparticles in each layer, a broad range of nanoparticle pillars were assembled and characterized in detail. In addition, we demonstrated the utility of this stacking assembly strategy for investigating plasmonic and electrical transport properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Programmable Aggregation of Artificial Cells with DNA Signals

Cell aggregation is a complex behavior, which is closely related to the viability, differentiation, and migration of cells. An effort to create synthetic analogs could lead to considerable advances in cell physiology and biophysics. Rendering and modulating such a dynamic artificial cell system require mechanisms for receiving, transducing, and transmitting intercellular signals, yet effective tools are limited at present. Here we construct synthetic cells from engineered lipids and show their programmable aggregation behaviors using DNA oligonucleotides as a signaling molecule. The artificial cells have transmembrane channels made of DNA origami that are used to recognize and process intercellular signals. We demonstrate that multiple small vesicles aggregate onto a giant vesicle after a transduction of external DNA signals by an intracellular enzyme, and that the small vesicles dissociate when receiving ‘release’ signals. Furthermore, this work provides new possibilities for building synthetic protocells capable of chemical communication and coordination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Programmable Synthesis of Multimetallic Phosphide Nanorods Mediated by Core/Shell Structure Formation and Conversion

Generalized synthetic strategies for nanostructures with well-defined physical dimensions and broad-range chemical compositions are at the frontier of advanced nanomaterials design, functionalization, and application. In this paper, we report a composition-programmable synthesis of multimetallic phosphide CoMP x nanorods (NRs) wherein M can be controlled to be Fe, Ni, Mn, Cu, and their binary combinations. Forming Co 2 P/MP x core/shell NRs and subsequently converting them into CoMP x solid-solution NRs through thermal post-treatment are essential to overcome the obstacle of morphology/structure inconsistency faced in conventional synthesis of CoMP x with the different M compositions. The resultant CoMP x with uniform one-dimensional (1-D) structure provides us a platform to unambiguously screen the M synergistic effects in improving the electrocatalytic activity, as exemplified by the oxygen evolution reaction. This new approach mediated by core/shell nanostructure formation and conversion can be extended to other multicomponent nanocrystal systems (metal alloy, mixed oxide, and chalcogenide, etc.) for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Platinum Graphene Catalytic Condenser for Millisecond Programmable Metal Surfaces

Accelerating catalytic chemistry and tuning surface reactions require precise control of the electron density of metal atoms. In this work, nanoclusters of platinum were supported on a graphene sheet within a catalytic condenser device that facilitated electron or hole accumulation in the platinum active sites with negative or positive applied potential, respectively. The catalytic condenser was fabricated by depositing on top of a p-type Si wafer an amorphous HfO 2 dielectric (70 nm), on which was placed the active layer of 2–4 nm platinum nanoclusters on graphene. A potential of ±6 V applied to the Pt/graphene layer relative to the silicon electrode moved electrons into or out of the active sites of Pt, attaining charge densities more than 1% of an electron or hole per surface Pt atom. At a level of charge condensation of ±10% of an electron per surface atom, the binding energy of carbon monoxide to a Pt(111) surface was computed via density functional theory to change 24 kJ mol –1 (0.25 eV), which was consistent with the range of carbon monoxide binding energies determined from temperature-programmed desorption (ΔBE CO of 20 ± 1 kJ mol –1 or 0.19 eV) and equilibrium surface coverage measurements (ΔBE CO of 14 ± 1 kJ mol –1 or 0.14 eV). Impedance spectroscopy indicated that Pt/graphene condensers with potentials oscillating at 3000 Hz exhibited negligible loss in capacitance and charge accumulation, enabling programmable surface conditions at amplitudes and frequencies necessary to achieve catalytic resonance.

Inorganic carbon compounds↗
DOE OSTI2018

A programmable two-qubit quantum processor in silicon

Now that it is possible to achieve measurement and control fidelities for individual quantum bits (qubits) above the threshold for fault tolerance, attention is moving towards the difficult task of scaling up the number of physical qubits to the large numbers that are needed for fault-tolerant quantum computing (1,2). In this context, quantum-dot-based spin qubits could have substantial advantages over other types of qubit owing to their potential for all-electrical operation and ability to be integrated at high density onto an industrial platform (3,4,5). Initialization, readout and single- and two-qubit gates have been demonstrated in various quantum-dot-based qubit representations (6,7,8,9). However, as seen with small-scale demonstrations of quantum computers using other types of qubit (10,11,12,13), combining these elements leads to challenges related to qubit crosstalk, state leakage, calibration and control hardware. We overcome these challenges by using carefully designed control techniques to demonstrate a programmable two-qubit quantum processor in a silicon device that can perform the Deutsch–Josza algorithm and the Grover search algorithm—canonical examples of quantum algorithms that outperform their classical analogues. We characterize the entanglement in our processor by using quantum-state tomography of Bell states, measuring state fidelities of 85–89 per cent and concurrences of 73–82 per cent. These results pave the way for larger-scale quantum computers that use spins confined to quantum dots.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

The MoSeS dynamic omnigami paradigm for smart shape and composition programmable 2D materials

The properties of 2D materials can be broadly tuned through alloying and phase and strain engineering. Shape programmable materials offer tremendous functionality, but sub-micron objects are typically unachievable with conventional thin films. Here we propose a new approach, combining phase/strain engineering with shape programming, to form 3D objects by patterned alloying of 2D transition metal dichalcogenide (TMD) monolayers. Conjugately, monolayers can be compositionally patterned using non-flat substrates. For concreteness, we focus on the TMD alloy MoSe 2c S 2 (1–c) ; i.e., MoSeS. These 2D materials down-scale shape/composition programming to nanoscale objects/patterns, provide control of both bending and stretching deformations, are reversibly actuatable with electric fields, and possess the extraordinary and diverse properties of TMDs. Utilizing a first principles-informed continuum model, we demonstrate how a variety of shapes/composition patterns can be programmed and reversibly modulated across length scales. Furthermore, the vast space of possible designs and scales enables novel material properties and thus new applications spanning flexible electronics/optics, catalysis, responsive coatings, and soft robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R 2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R 2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Programmable quantum emitter formation in silicon

Abstract Silicon-based quantum emitters are candidates for large-scale qubit integration due to their single-photon emission properties and potential for spin-photon interfaces with long spin coherence times. Here, we demonstrate local writing and erasing of selected light-emitting defects using femtosecond laser pulses in combination with hydrogen-based defect activation and passivation at a single center level. By choosing forming gas (N 2 /H 2 ) during thermal annealing of carbon-implanted silicon, we can select the formation of a series of hydrogen and carbon-related quantum emitters, including T and C i centers while passivating the more common G-centers. The C i center is a telecom S-band emitter with promising optical and spin properties that consists of a single interstitial carbon atom in the silicon lattice. Density functional theory calculations show that the C i center brightness is enhanced by several orders of magnitude in the presence of hydrogen. Fs-laser pulses locally affect the passivation or activation of quantum emitters with hydrogen for programmable formation of selected quantum emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Autonomous stabilization with programmable stabilized state

Reservoir engineering is a powerful technique to autonomously stabilize a quantum state. Traditional schemes involving multi-body states typically function for discrete entangled states. In this work, we enhance the stabilization capability to a continuous manifold of states with programmable stabilized state selection using multiple continuous tuning parameters. We experimentally achieve 84.6% and 82.5% stabilization fidelity for the odd and even-parity Bell states as two special points in the manifold. We also perform fast dissipative switching between these opposite parity states within 1.8 μs and 0.9 μs by sequentially applying different stabilization drives. Our result is a precursor for new reservoir engineering-based error correction schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Regioselective surface encoding of nanoparticles for programmable self-assembly

Surface encoding of colloidal nanoparticles with DNA is fundamental for fields where recognition interaction is required, particularly controllable material self-assembly. However, regioselective surface encoding of nanoparticles is still challenging because of the difficulty associated with breaking the identical chemical environment on nanoparticle surfaces. Here we demonstrate the selective blocking of nanoparticle surfaces with a diblock copolymer (polystyrene-b-polyacrylic acid). By tuning the interfacial free energies of a ternary system involving the nanoparticles, solvent and copolymer, controllable accessibilities to the nanoparticles’ surfaces are obtained. Through the modification of the polymer-free surface region with single-stranded DNA, regioselective and programmable surface encoding is realized. The resultant interparticle binding potential is selective and directional, allowing for an increased degree of complexity of potential self-assemblies. As a result, the versatility of this regioselective surface encoding strategy is demonstrated on various nanoparticles of isotropic or anisotropic shape and a total of 24 distinct complex nanoassemblies are fabricated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

High-speed programmable photonic circuits in a cryogenically compatible, visible–near-infrared 200 mm CMOS architecture

Abstract Recent advances in photonic integrated circuits have enabled a new generation of programmable Mach–Zehnder meshes (MZMs) realized by using cascaded Mach–Zehnder interferometers capable of universal linear-optical transformations on N input/output optical modes. MZMs serve critical functions in photonic quantum information processing, quantum-enhanced sensor networks, machine learning and other applications. However, MZM implementations reported to date rely on thermo-optic phase shifters, which limit applications due to slow response times and high power consumption. Here we introduce a large-scale MZM platform made in a 200 mm complementary metal–oxide–semiconductor foundry, which uses aluminium nitride piezo-optomechanical actuators coupled to silicon nitride waveguides, enabling low-loss propagation with phase modulation at greater than 100 MHz in the visible–near-infrared wavelengths. Moreover, the vanishingly low hold-power consumption of the piezo-actuators enables these photonic integrated circuits to operate at cryogenic temperatures, paving the way for a fully integrated device architecture for a range of quantum applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Programmable simulations of molecules and materials with reconfigurable quantum processors

Simulations of quantum chemistry and quantum materials are believed to be among the most important applications of quantum information processors. However, realizing practical quantum advantage for such problems is challenging because of the prohibitive computational cost of programming typical problems into quantum hardware. Here we introduce a simulation framework for strongly correlated quantum systems represented by model spin Hamiltonians that uses reconfigurable qubit architectures to simulate real-time dynamics in a programmable way. Our approach also introduces an algorithm for extracting chemically relevant spectral properties via classical co-processing of quantum measurement results. We develop a digital–analogue simulation toolbox for efficient Hamiltonian time evolution using digital Floquet engineering and hardware-optimized multi-qubit operations to accurately realize complex spin–spin interactions. As an example, we propose an implementation based on Rydberg atom arrays. In addition, we show how detailed spectral information can be extracted from the dynamics through snapshot measurements and single-ancilla control, enabling the evaluation of excitation energies and finite-temperature susceptibilities from a single dataset. To illustrate the approach, we show how to use the method to compute key properties of a polynuclear transition-metal catalyst and two-dimensional magnetic materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Programmable design of orthogonal protein heterodimers

Specificity of interactions between two DNA strands, or between protein and DNA, is often achieved by varying bases or side chains coming off the DNA or protein backbone—for example, the bases participating in Watson–Crick pairing in the double helix, or the side chains contacting DNA in TALEN–DNA complexes. By contrast, specificity of protein–protein interactions usually involves backbone shape complementarity1, which is less modular and hence harder to generalize. Coiled-coil heterodimers are an exception, but the restricted geometry of interactions across the heterodimer interface (primarily at the heptad a and d positions2) limits the number of orthogonal pairs that can be created simply by varying side-chain interactions3,4. Here we show that protein–protein interaction specificity can be achieved using extensive and modular side-chain hydrogen-bond networks. We used the Crick generating equations5 to produce millions of four-helix backbones with varying degrees of supercoiling around a central axis, identified those accommodating extensive hydrogen-bond networks, and used Rosetta to connect pairs of helices with short loops and to optimize the remainder of the sequence. Of 97 such designs expressed in Escherichia coli, 65 formed constitutive heterodimers, and the crystal structures of four designs were in close agreement with the computational models and confirmed the designed hydrogen-bond networks. In cells, six heterodimers were fully orthogonal, and in vitro—following mixing of 32 chains from 16 heterodimer designs, denaturation in 5 M guanidine hydrochloride and reannealing—almost all of the interactions observed by native mass spectrometry were between the designed cognate pairs. The ability to design orthogonal protein heterodimers should enable sophisticated protein-based control logic for synthetic biology, and illustrates that nature has not fully explored the possibilities for programmable biomolecular interaction modalities.

Chen, Zibo↗
DOE OSTI2019

Quantum supremacy using a programmable superconducting processor

The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor with programmable superconducting qubits to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 2 53 (about 10 16 ). Measurements from repeated experiments sample the resulting probability distribution, which we verify using classical simulations. Our Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. Finally, this dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy for this specific computational task, heralding a much-anticipated computing paradigm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗