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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Acoustics at the nanoscale (nanoacoustics): A comprehensive literature review. Part II: Nanoacoustics for biomedical imaging and therapy

We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part II of this two-part review, this paper concentrates on nanoacoustics in biomedical imaging and therapy applications, including molecular ultrasound imaging, photoacoustic imaging, ultrasound-mediated drug delivery and therapy, and photoacoustic drug delivery and therapy. Firstly, the recent developments of nanosized ultrasound and photoacoustic contrast agents as well as their various imaging applications are examined. Secondly, different types of nanomaterials/nanostructures as nanocarriers for ultrasound and photoacoustic therapies are discussed. Finally, a discussion of challenges and future research directions are provided for nanoacoustics in medical imaging and therapy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

State-of-the-Art Organic- and Inorganic-Based Hollow Fiber Membranes in Liquid and Gas Applications: Looking Back and Beyond

The aggravation of environmental problems such as water scarcity and air pollution has called upon the need for a sustainable solution globally. Membrane technology, owing to its simplicity, sustainability, and cost-effectiveness, has emerged as one of the favorable technologies for water and air purification. Among all of the membrane configurations, hollow fiber membranes hold promise due to their outstanding packing density and ease of module assembly. Herein, this review systematically outlines the fundamentals of hollow fiber membranes, which comprise the structural analyses and phase inversion mechanism. Furthermore, illustrations of the latest advances in the fabrication of organic, inorganic, and composite hollow fiber membranes are presented. Key findings on the utilization of hollow fiber membranes in microfiltration (MF), nanofiltration (NF), reverse osmosis (RO), forward osmosis (FO), pervaporation, gas and vapor separation, membrane distillation, and membrane contactor are also reported. Moreover, the applications in nuclear waste treatment and biomedical fields such as hemodialysis and drug delivery are emphasized. Subsequently, the emerging R&D areas, precisely on green fabrication and modification techniques as well as sustainable materials for hollow fiber membranes, are highlighted. Last but not least, this review offers invigorating perspectives on the future directions for the design of next-generation hollow fiber membranes for various applications. As such, the comprehensive and critical insights gained in this review are anticipated to provide a new research doorway to stimulate the future development and optimization of hollow fiber membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Constitutive Modeling and Testing of Polymer Matrix Composites Incorporating Physical Aging at Elevated Temperatures

Advanced polymer matrix composites (PMC's) are desirable for structural materials in diverse applications such as aircraft, civil infrastructure and biomedical implants because of their improved strength-to-weight and stiffness-to-weight ratios. For example, the next generation military and commercial aircraft requires applications for high strength, low weight structural components subjected to elevated temperatures. A possible disadvantage of polymer-based composites is that the physical and mechanical properties of the matrix often change significantly over time due to the exposure of elevated temperatures and environmental factors. For design, long term exposure (i.e. aging) of PMC's must be accounted for through constitutive models in order to accurately assess the effects of aging on performance, crack initiation and remaining life. One particular aspect of this aging process, physical aging, is considered in this research.

Veazie, David R.↗
DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities. This review encompasses various techniques and strategies to evaluate and enhance mixing efficiency in these confined environments. It explores the significance of mixing in micro- and millichannels, highlighting its relevance for enhanced reaction kinetics, homogeneity in mixed fluids, and analytical accuracy. We discuss various mixing methodologies that have been employed to get a narrower residence time distribution. The role of channel geometry, flow conditions, and mixing mechanisms in influencing the mixing performance are also discussed. Various emerging technologies and advancements in microfluidic devices and tools specifically designed to enhance mixing efficiency are highlighted. We emphasize the potential applications of micro- and millichannels in fields of nanoparticle synthesis, which can be utilized for biological applications. Additionally, the prospects of machine learning and artificial intelligence are offered toward incorporating better mixing to achieve precise control over nanoparticle synthesis, ultimately enhancing the potential for applications in these miniature fluidic systems.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Composition-Dependent Microstructure-Property Relationships of Fe and Al Modified Ti-12Cr (wt.%)

b-Titanium (Ti) alloys have applications in several industries (e.g. aerospace, automotive, and biomedical) where material performance requirements vary widely. To tailor the microstructure and mechanical properties of b-Ti alloys for various applications, it is critical to understand the influence of individual alloying elements. Toward this goal, we investigated the effect of individual alloying additions on the microstructure and resultant mechanical properties of four model b-Ti alloys: Ti-12Cr, Ti-12Cr-3Al, Ti-12Cr-1Fe, and Ti-12Cr-1Fe3Al (wt.%). The microstructures of these alloys were studied using x-ray diffraction, electron microscopy, and atom probe tomography. The mechanical properties were analyzed via Vickers and Rockwell hardness measurements and tensile testing. The addition of 1 wt.% Fe resulted in an approximate 5% increase in elongation-to-failure (ef), while the addition of 3 wt.% Al did not appear to significantly affect ef. The addition of Fe and Al decreased the yield and ultimate tensile strengths.

Ballor, Joann P.↗
DOE OSTI2020

DEEP CELLULAR RECURRENT NEURAL ARCHITECTURE FOR EFFICIENT MULTIDIMENSIONAL TIME-SERIES DATA PROCESSING

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in complexity and size to accommodate the additional dimensionality of time. Specifically, the biologically inspired learning based models known as artificial neural networks that have shown extraordinary success in pattern recognition, tend to grow prohibitively large and cumbersome in the presence of large scale multi-dimensional time series biomedical data such as EEG. Consequently, this work aims to develop representative ML and DL models for robust and efficient large scale time series processing. First, we design a novel ML pipeline with efficient feature engineering to process a large scale multi-channel scalp EEG dataset for automated detection of epileptic seizures. With the use of a sophisticated yet computationally efficient time-frequency analysis technique known as harmonic wavelet packet transform and an efficient self-similarity computation based on fractal dimension, we achieve state-of-the-art performance for automated seizure detection in EEG data. Subsequently, we investigate the development of a novel efficient deep recurrent learning model for large scale time series processing. For this, we first study the functionality and training of a biologically inspired neural network architecture known as cellular simultaneous recurrent neural network (CSRN). We obtain a generalization of this network for multiple topological image processing tasks and investigate the learning efficacy of the complex cellular architecture using several state-of-the?art training methods. Finally, we develop a novel deep cellular recurrent neural network (CDRNN) architecture based on the biologically inspired distributed processing used in CSRN for processing time series data. The proposed DCRNN leverages the cellular recurrent architecture to promote extensive weight sharing and efficient, individualized, synchronous processing of multi-source time series data. Experiments on a large scale multi-channel scalp EEG, and a machine fault detection dataset show that the proposed DCRNN offers state-of-the-art recognition performance while using substantially fewer trainable recurrent units.

Vidyaratne, Lasitha S.↗
DOE OSTI2025

Room‐Temperature Mid‐Infrared Detection Using Metasurface‐Absorber‐Integrated Phononic Crystal Oscillator

Mid-infrared (MIR) detectors find extensive applications in chemical sensing, spectroscopy, communications, biomedical diagnosis, and space exploration. Alternative to semiconductor MIR photodiodes and bolometers, mechanical-resonator-based MIR detectors show advantages in higher sensitivity and lower noise at room temperature, especially toward longer wavelength infrared. Here, uncooled room-temperature MIR detectors based on lithium niobate surface acoustic wave phononic crystal (PnC) resonators integrated with wavelength-and-polarization-selective metasurface absorber arrays are demonstrated. The detection is based on the resonant frequency shift induced by the local temperature change due to MIR absorptions. The PnC resonator is configured in an oscillating mode, enabling active readout and low-frequency noise. The 1-GHz oscillator-based MIR detector shows a relative frequency deviation of 5.24 × 10 −10 Hz −1/2 at an integration time of 50 µs, leading to an incident noise equivalent power of 197 pW Hz −1/2 when input 6-µm MIR light is modulated at 1.8 kHz, and a large dynamic range of 10 7 in incident MIR power. The device architecture is compatible with the scalable manufacturing process and can be readily extended to a broader spectral range by tailoring the absorbing wavelengths of metasurface absorbers.

Xi, Zichen [Virginia Polytechnic Inst. and State U↗
DOE OSTI2017

Laser Nitriding of the Newly Developed Ti-20Nb-13Zr at.% Biomaterial Alloy to Enhance Its Mechanical and Corrosion Properties in Simulated Body Fluid

Despite the widespread application of Ti alloy in the biomedical field, surface treatments are typically applied to improve its resistance to corrosion and wear. A newly developed biomedical Ti-20Nb-13Zr at.% alloy (TNZ) was laser-treated in nitrogen environment to improve its surface characteristics with corrosion protection performance. Surface modification of the alloy by laser was performed through a Nd:YAG laser. The structural and surface morphological alterations in the laser nitrided layer were investigated by XRD and a FE-SEM. The mechanical properties have been evaluated using nanoindentation for laser nitride and as-received samples. The corrosion protection behavior was estimated using electrochemical corrosion analysis in a physiological medium (SBF). The obtained results revealed the production of a dense and compact film of TiN fine grains (micro-/nanosize) with 9.1 µm below the surface. The mechanical assessment results indicated an improvement in the modulus of elasticity, hardness, and resistance of the formed TiN layer to plastic deformation. The electrochemical analysis exhibited that the surface protection performance of the laser nitrided TNZ substrates in the SBF could be considerably enhanced compared to that of the as-received alloy due to the presence of fine grains in the TiN layer resulting from laser nitriding. Furthermore, the untreated and treated Ti-20Nb-13Zr alloy exhibited higher corrosion resistance than the CpTi and Ti6Al4V commercial alloys. The improvements in the surface hardness and corrosion properties of Ti alloy in a simulated body obtained using laser nitriding make this approach a suitable candidate for enhancing the properties of biomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Enhancement of red upconversion emission of cubic phase NaLuF{sub 4}: Yb{sup 3+}/Ho{sup 3+}/Ce{sup 3+} nanocrystals

Highlights: • The upconversion emission of Ho{sup 3+} ions was tuned from green to red. • The upconversion mechanism of Ho{sup 3+} ions was discussed based on emission spectrum. • The conversion efficiency between Ho{sup 3+} and Ce{sup 3+} were studied and calculated. - Abstract: The red upconversion emission of lanthanide-doped fluoride nanocrystals have great potential applications in color display and anticounterfeiting applications, especially for biological imaging and biomedical. In this work, a significant enhancement of red upconversion emission of Ho{sup 3+} ions was successfully obtained in the cubic phase NaLuF{sub 4} nanocrystals through codoping Ce{sup 3+} ions under NIR 980 nm excitation. The ratio of red-to-green emission of Ho{sup 3+} ions was enhanced about 10-fold, which is due to two efficient cross relaxation processes derived from Ho{sup 3+} and Ce{sup 3+} ions promoted the red emission and quenched the green emission. The upconversion emission and luminescent colors of NaLuF{sub 4}: Yb{sup 3+}/Ho{sup 3+} nanocrystals were carefully investigated by a confocal microscopy setup. The possible upconversion emission mechanism and conversion efficiency of cross relaxation between Ho{sup 3+} and Ce{sup 3+} ions were discussed in detail. The current study suggests that strong red emission of NaLuF{sub 4}: Yb{sup 3+}/Ho{sup 3+}/Ce{sup 3+} nanomaterials can be used for color display and anticounterfeiting techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structure and Stability of Pristine and Carboxylate-Covered Anatase TiO 2 (001) in Aqueous Environment

The interactions of carboxylic acids and water with TiO 2 surfaces are important in applications ranging from solar cells to biomedical devices. Here we focus on the aqueous interface with the minority (001) surface of anatase TiO 2 (A-001) and the behavior of adsorbed formic and acetic acid monolayers at this interface. We investigated the structure and stability of the pristine reconstructed and formic/acetic acid covered A-001 surfaces in contact with water using density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations. The (1 × 4) reconstruction of the pristine surface is found to be stable in aqueous environment, within the time scale of our simulation. Here, carboxylic acids adsorb in deprotonated bidentate (BD) form on A-001, with the dissociated proton transferred to a surface oxygen to form a bridging hydroxyl. Of the two possible configurations, BD bridging and BD straddling, of the adsorbed species, the latter is found to rapidly transform to a monodentate structure during our simulations. Further investigation of mixed acetate–formate monolayers on A-001 in water indicates that also BD bridging species can become unstable at the boundaries between formate and acetate-covered regions, transforming to a monodentate form that does not prevent water adsorption on the TiO 2 surface.

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

Effect of the Lignin Structure on the Physicochemical Properties of Lignin-Grafted-Poly(ε-caprolactone) and Its Application for Water/Oil Separation

Lignin-grafted poly(ε-caprolactone) copolymers (lignin-g-PCLs) have shown wide application potentials in coatings, biocomposites, and biomedical fields. However, the structural heterogeneity of lignin affecting the structures and properties of lignin-g-PCL has been scarcely investigated. In this study, kraft lignin is fractionated into four precursors, namely, F ins , F1, F2, and F3, with declining molecular weights and increased hydroxyl contents. Lignin-g-PCLs are synthesized via ring-opening polymerization of ε-caprolactone with lignin and characterized by GPC, FTIR, 1 H and 31 P NMR, DSC, TGA, and iGC. The mechanical properties, UV barrier, and enzymatic biodegradability of the lignin-g-PCLs are evaluated. Results show that lignin with a higher molecular weight and aliphatic OH favors the copolymerization, leading to lignin-g-PCLs with longer PCL arms. Moreover, lignin incorporation improves the thermal stability, hydrophobicity, and UV-blocking ability but reduces the lipase hydrolyzability of the copolymers. We also demonstrated that the lignin-g-PCL-coated filter paper could successfully separate chloroform–, petroleum ether–, and hexane–water mixtures with an efficiency up to 99.2%. The separation efficiency remains above 90% even after 15 cycles. The structural differences of copolymers derived from the fractionation showed minimal influence on the separation efficiency. This work provides new insights into lignin-based copolymerization and the versatility of lignin valorization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Influence of driving frequency on discharge modes in a dielectric-barrier discharge with multiple current pulses

A one-dimensional self-consistent fluid model was employed to investigate the effect of the driving frequency on the discharge modes in atmospheric-pressure argon discharge with multiple current pulses. The discharge mode was discussed in detail not only at current peaks but also between two adjacent peaks. The simulation results show that different transitions between the Townsend and glow modes during the discharge take place with the driving frequency increased. A complicated transition from the Townsend mode, through glow, Townsend, and glow, and finally back to the Townsend one is found in the discharge with the driving frequency of 8 kHz. There is a tendency of transition from the Townsend to glow mode for the discharge both at the current peaks and troughs with the increasing frequency. The discharge in the half period can all along operate in the glow mode with the driving frequency high enough. This is resulted from the preservation of more electrons in the gas gap and acquisition of more electron energy from the swiftly varying electric field with the increase in driving frequency. Comparison of the spatial and temporal evolutions of the electron density at different driving frequencies indicates that the increment of the driving frequency allows the plasma chemistry to be enhanced. This electrical characteristic is important for the applications, such as surface treatment and biomedical sterilization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Active mixing of complex fluids at the microscale

Mixing of complex fluids at low Reynolds number is fundamental for a broad range of applications, including materials assembly, microfluidics, and biomedical devices. Of these materials, yield stress fluids (and gels) pose the most significant challenges, especially when they must be mixed in low volumes over short timescales. New scaling relationships between mixer dimensions and operating conditions are derived and experimentally verified to create a framework for designing active microfluidic mixers that can efficiently homogenize a wide range of complex fluids. As a result, active mixing printheads are then designed and implemented for multimaterial 3D printing of viscoelastic inks with programmable control of local composition.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Iterative optimization yields Mcl-1–targeting stapled peptides with selective cytotoxicity to Mcl-1–dependent cancer cells

Bcl-2 family proteins regulate apoptosis, and aberrant interactions of overexpressed antiapoptotic family members such as Mcl-1 promote cell transformation, cancer survival, and resistance to chemotherapy. Discovering potent and selective Mcl-1 inhibitors that can relieve apoptotic blockades is thus a high priority for cancer research. An attractive strategy for disabling Mcl-1 involves using designer peptides to competitively engage its binding groove, mimicking the structural mechanism of action of native sensitizer BH3-only proteins. We transformed Mcl-1–binding peptides into α-helical, cell-penetrating constructs that are selectively cytotoxic to Mcl-1–dependent cancer cells. Critical to the design of effective inhibitors was our introduction of an all-hydrocarbon cross-link or “staple” that stabilizes α-helical structure, increases target binding affinity, and independently confers binding specificity for Mcl-1 over related Bcl-2 family paralogs. Two crystal structures of complexes at 1.4 Å and 1.9 Å resolution demonstrate how the hydrophobic staple induces an unanticipated structural rearrangement in Mcl-1 upon binding. Systematic sampling of staple location and iterative optimization of peptide sequence in accordance with established design principles provided peptides that target intracellular Mcl-1. Here, this work provides proof of concept for the development of potent, selective, and cell-permeable stapled peptides for therapeutic targeting of Mcl-1 in cancer, applying a design and validation workflow applicable to a host of challenging biomedical targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗