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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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18 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mechanical Ventilator Milano (MVM): A Novel Mechanical Ventilator Designed for Mass Scale Production in Response to the COVID-19 Pandemics

We present here the design of the Mechanical Ventilator Milano (MVM), a novel mechanical ventilator designed for mass scale production in response to the COVID-19 pandemics, to compensate for the dramatic shortage of such ventilators in many countries. This ventilator is an electro-mechanical equivalent of the old, reliable Manley Ventilator. Our design is optimized to permit large sale production in short time and at a limited cost, relying on off-the-shelf components, readily available worldwide from hardware suppliers. Operation of the MVM requires only a source of compressed oxygen (or compressed medical air) and electrical power. The MVM control and monitoring unit can be connected and networked via WiFi so that no additional electrical connections are necessary other than the connection to the electrical power. At this stage the MVM is not a certified medical device. Construction of the first prototypes is starting with a team of engineers, scientists and computing experts. The purpose of this paper is to disseminate the conceptual design of the MVM broadly and to solicit feedback from the scientific and medical community to speed the process of review, improvement and possible implementation.

Galbiati, C.↗
DOE OSTI2021

The novel Mechanical Ventilator Milano for the COVID-19 pandemic

This paper presents the Mechanical Ventilator Milano (MVM), a novel intensive therapy mechanical ventilator designed for rapid, large-scale, low-cost production for the COVID-19 pandemic. Free of moving mechanical parts and requiring only a source of compressed oxygen and medical air to operate, the MVM is designed to support the long-term invasive ventilation often required for COVID-19 patients and operates in pressure-regulated ventilation modes, which minimize the risk of furthering lung trauma. The MVM was extensively tested against ISO standards in the laboratory using a breathing simulator, with good agreement between input and measured breathing parameters and performing correctly in response to fault conditions and stability tests. The MVM has obtained Emergency Use Authorization by U.S. Food and Drug Administration (FDA) for use in healthcare settings during the COVID-19 pandemic and Health Canada Medical Device Authorization for Importation or Sale, under Interim Order for Use in Relation to COVID-19. Furthermore, following these certifications, mass production is ongoing and distribution is under way in several countries. The MVM was designed, tested, prepared for certification, and mass produced in the space of a few months by a unique collaboration of respiratory healthcare professionals and experimental physicists, working with industrial partners, and is an excellent ventilator candidate for this pandemic anywhere in the world

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Effect of lattice orientation on compressive properties of selective laser sintered nylon lattice coupons

As AM lattices become more popular in medical devices, it is important to consider how lattice design parameters affect the mechanical integrity and performance of a device. This research investigated the effect of lattice orientation on the compressive mechanical response of five common lattice geometries: Hexagonal Honeycomb (Hex), Diamond, Voronoi Tessellation Method (VTM), sheet-based Gyroid, and Face-Centered-Cubic (FCC). Samples were tested at two relative densities and eight orientations, printed in Nylon 12 (PA2200) on an EOS P396. The mechanical response was compared to simulated finite element analysis (FEA) response for Hex and FCC lattices. Hex lattices displayed significant orientation dependance. Diamond lattices demonstrated some orientation dependance when at a lower relative density. Gyroid, FCC, and VTM all displayed minimal orientation dependance. Increasing lattice relative density appeared to reduce anisotropy among tested orientations of all lattice geometries except Hex. FEA simulations were able to produce a trend response that matched the mechanical response trends based on the investigated orientations. Furthermore, these results support the need for multi axial lattice mechanical test considerations. It also bolsters the need for lattice FEA models to have a sufficient comparator when identifying “worst-case” lattice test scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Flow Measurements in Pressurized Helium Gas Cooling Channels: Rev. 1

Compressed helium gas is used to cool the NorthStar Medical Radioisotope (NMR) target system, also called the trident, chosen due to its superior heat transfer capabilities and its inability to react with Molybdenum-100 (Mo-100) during irradiation. To test the housing and NMR target stack at Los Alamos National Laboratory (LANL), two sets of helium gas flow loop facilities have been set-up and tested. One system is used for bench-top experiments to systematically investigate individual components of the NMR target, and the other, larger system is more representative of the system at NMR and is used for testing the full NMR target stack.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Compression Response of Silicone-Based Composites with Integrated Multifunctional Fillers

Polydimethylsiloxane (PDMS) is known for its exceptional mechanical properties, chemical stability, and flexibility. Recent advancements have focused on developing functional PDMS composites by integrating various functional fillers, including polymers, ceramics, and metals, for advanced applications such as electronics, medical devices, and aerospace. Consequently, there is a growing need to investigate PDMS composites to achieve higher filler loadings offering enhanced mechanical performance. This study addresses this need by utilizing the high molecular weight (MW) PDMS resin we have developed, offering its high elongation capacity of up to >6500%. We incorporated boron (B), hollow glass microballoons (HGMs), and tungsten-coated hollow glass microballoons (WHGMs) into the developed high MW PDMS. The resulting composites demonstrated excellent elastic properties and significant compression resilience (35–80%) and elastic modulus (1.28–10.15 MPa) at high filler loadings (~60 vol.%). Specifically, B/PDMS composites achieved up to 67.6 vol.% of B, HGM/PDMS composites held up to 68.6 vol.% of HGM, and WHGM/PDMS composites incorporated up to 54.0 vol.% of WHGM. These findings highlight the potential of high MW PDMS for developing high-performance PDMS composites suitable for advanced applications such as aerospace, automotive, and medical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Compressive properties of silicone Bouligand structures

Abstract This article presents an examination of silicone, Bouligand lattices in compression. Appearing frequently in biological organisms and manufacturing design, Bouligand structures comprise layers of parallel strands or fibers oriented in a helical fashion. They can exhibit exceptional fracture resistance when composed of rigid or composite materials. The behavior of elastomeric Bouligand structures, however, is less well understood. Additively manufactured (AM) elastomeric lattices have applications in stress mitigation, medical devices, and soft robotics. This article demonstrates that Bouligand structures are a useful addition to the design space of AM elastomers. By adjusting the layer-rotation parameters, lattice stress can increase by more than 300% without altering the porosity. Additionally, we introduce path length metrics that help explain the observed relationship between layer rotation and compression response. Impact statement Additive manufacturing (AM) continues to push the boundary of manufacturable structures and enhance the ability to robustly design for specific properties and behaviors. The more we understand the design space of a novel AM microstructure, the greater its application range. In this article, we describe the mechanical behavior of helicoidal, elastomeric lattices and introduce path length metrics to help explain their stress response. We show that these structures can exhibit a large range of mechanical behaviors in compression, making them well suited for applications such as stress mitigation and impact absorption. Additionally, the path length metrics could become useful design tools and may be applicable to a larger set of cellular structures. These findings expand our ability to rapidly design materials with highly specific and customizable properties to meet the needs of modern engineering challenges. Graphical abstract

Van Meerbeek, I. M. (ORCID:000000021258132X)↗
DOE OSTI2024

Radioisotope production using lasers: From basic science to applications

The discovery of chirped pulse amplification has led to great improvements in laser technology, enabling energetic laser beams to be compressed to pulse durations of tens of femtoseconds and focused to a few micrometers. Protons with energies of tens of MeV can be accelerated using, for instance, target normal sheath acceleration and focused on secondary targets. Under such conditions, nuclear reactions can occur, with the production of radioisotopes suitable for medical application. The use of high-repetition lasers to produce such isotopes is competitive with conventional methods mostly based on accelerators. In this paper, we study the production of 67Cu, 63Zn, 18F, and 11C, which are currently used in positron emission tomography and other applications. At the same time, we study the reactions 10B(p,α)7Be and 70Zn(p,4n)67Ga to put further constraints on the proton distributions at different angles, as well as the reaction 11B(p,α)8Be relevant for energy production. The experiment was performed at the 1 PW laser facility at Vega III in Salamanca, Spain. Angular distributions of radioisotopes in the forward (with respect to the laser direction) and backward directions were measured using a high purity germanium detector. Our results are in reasonable agreement with numerical estimates obtained following the approach of Kimura and Bonasera [Nucl. Instrum. Methods Phys. Res., Sect. A 637, 164–170 (2011)].

11C↗
DOE OSTI2020

Acute Shortage Ventilator

Abstract We have implemented an “Acute Shortage Ventilator” (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.

Akerib, D. S.↗
DOE OSTI2020

Acute shortage ventilator

We have implemented an ″Acute Shortage Ventilator″ (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.

Breur, Sander↗
DOE OSTI2025

Hybrid epoxy–acrylate resins for wavelength-selective multimaterial 3D printing

Structures in nature have evolved to combine hard and soft materials in precise 3D arrangements, which imbues bulk properties and functionality that remain elusive to mimic synthetically. However, the potential for biomimetic analogs to seamlessly interface hard materials with soft surfaces for applications ranging from robotics and sealants to medical devices (e.g., prosthetics and wearable health monitors) has driven the demand for innovative chemistries and manufacturing approaches. Herein, we unveil a liquid resin for rapid, high resolution digital light processing (DLP) 3D printing of multimaterial objects with an unprecedented combination of strength, elasticity, and resistance to aging. Two enabling discoveries are the use of a covalently bound (hybrid) epoxy-acrylate monomer that precludes plasticization of soft domains and a wavelength-selective photosensitizer that accelerates cationic curing for hard domains. Using dual projection for multicolor DLP 3D printing (UV and violet light), several bioinspired metamaterial structures are fabricated, including one with hard springs embedded in a soft cylinder to adjust compressive behavior and a detailed knee joint featuring “bones” and “ligaments” for smooth motion. Lastly, the application of this system to facilitate selective stretching for electronic devices is demonstrated with a proof-of-concept device.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Range and strength of mechanical interactions of force dipoles in elastic fiber networks

Mechanical forces generated by myosin II molecular motors drive diverse cellular processes, most notably shape change, division and locomotion. These forces may be transmitted over long range through the cytoskeletal medium – a disordered, viscoelastic network of biopolymers. The resulting cell size scale force chains can in principle mediate mechanical interactions between distant actomyosin units, leading to self-organized structural order in the cell cytoskeleton. Inspired by such force transmission through elastic structures in the cytoskeleton, we consider a percolated fiber lattice network, where fibers are represented as linear elastic elements that can both bend and stretch, and the contractile activity of myosin motors is represented by force dipoles. Then, by using a variety of metrics, we show how two such contractile force dipoles interact with each other through their mutual mechanical deformations of the elastic fiber network. As a prelude to two-dipole interactions, we quantify how forces propagate through the network from a single anisotropic force dipole by analyzing clusters of nodes connected by highly strained bonds, as well as through the decay rate of strain energy with distance from a force dipole. We show that predominant fiber bending screens out force propagation, resulting in reduced and strongly network configuration-dependent dipole interactions. On the other hand, stretching-dominated networks support longer-ranged inter-dipole interactions that recapitulate the predictions of linear elasticity theory. By characterizing the differences between tensile and compressive force propagation in the fiber network, we show how inter-dipole interaction depends on the dipoles’ mutual separation and orientation. The resulting elastic interaction energy may mediate a force between multiple distant dipoles, leading to their self-organization into ordered configurations. In conclusion, this provides a potential pathway for active mechanical force-driven structural order in elastic biopolymer networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach

Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. Here, this paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni 50 Ti 50 \Ni 50 Ti 50 \Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni 50 Ti 50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 °C, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni 50 Ti 50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Porous Polymer Structures with Tunable Mechanical Properties Using a Water Emulsion Ink

Recently, the manufacturing of porous polydimethylsiloxane (PDMS) with engineered porosity has gained considerable interest due to its tunable material properties and diverse applications. An innovative approach to control the porosity of PDMS is to use transient liquid phase water to improve its mechanical properties, which has been explored in this work. Adjusting the ratios of deionized water to the PDMS precursor during blending and subsequent curing processes allows for controlled porosity, yielding water emulsion foam with tailored properties. The PDMS-to-water weight ratios were engineered ranging from 100:0 to 10:90, with the 65:35 specimen exhibiting the best mechanical properties with a Young’s Modulus of 1.17 MPa, energy absorption of 0.33 MPa, and compressive strength of 3.50 MPa. This led to a porous sample exhibiting a 31.46% increase in the modulus of elasticity over a bulk PDMS sample. Dowsil SE 1700 was then added, improving the storage capabilities of the precursor. The optimal storage temperature was probed, with -60 °C resulting in great pore stability throughout a three-week duration. The possibility of using these water emulsion foams for paste extrusion additive manufacturing (AM) was also analyzed by implementing a rheological modifier, fumed silica. Fumed silica’s impact on viscosity was examined, revealing that 9 wt% of silica demonstrates optimal rheological behaviors for AM, bearing a viscosity of 10,290 Pa·s while demonstrating shear-thinning and thixotropic behavior. This study suggests that water can be used as pore-formers for PDMS in conjunction with AM to produce engineered materials and structures for aerospace, medical, and defense industries as sensors, microfluidic devices, and lightweight structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Novel Concepts for High Gradient Acceleration (Final Technical Report)

We have conducted an intensive, pioneering program to demonstrate novel concepts for achieving high gradient acceleration at frequencies from the conventional microwave bands up to the millimeter wave /THz bands. High gradient accelerators hold the promise of smaller and less costly accelerators for applications ranging from the largest scale accelerators used for discovery science down to the smallest accelerators used for industrial, homeland security and medical applications. The research consisted of two major research thrusts: 1.) Structure-based wakefield accelerator (SWFA) research in collaboration with the Argonne Wakefield Accelerator research group and 2.) Millimeter Wave / THz high gradient acceleration in collaboration with SLAC. The specific goals of the research program were: Design novel metallic metamaterial structures that increase the beam-wave coupling for the accelerator mode and reduce the effect of high order modes; test novel metamaterial structures to achieve higher output power, > 1 GW at X-Band (11.7 GHz), in test at the Argonne Wakefield Accelerator (AWA); determine the experimental breakdown threshold for nanosecond-scale pulses at X-Band in testing at the AWA; test a 110 GHz accelerator structure with a field emission electron gun, built at SLAC, using pulses from a 1 MW, 110 GHz gyrotron; design, build and test a 110 GHz quasi-optical, resonant-ring pulse compressor to compress microsecond pulses from the 1 MW gyrotron into > 20 MW, 5 ns output pulses for accelerator structure testing. The proposed research program built on our successes in our research program including: Generation of 510 MW, 2.1 ns (FWHM) pulses at 11.7 GHz from a metallic metamaterial structure in test at the Argonne Wakefield Accelerator using a train of eight 65 MeV electron bunches spaced at 1.3 GHz with a total charge of 280 nC. The metamaterial structure consisted of 100 copper unit cells each consisting of a “wagon-wheel” plate and a spacer plate with a total structure length of 0.2 m. The 510 MW pulse generated an on-axis wakefield of 130 MV/m that could be used to accelerate a trailing witness bunch. Demonstration of coupling of an unprecedented rf power level of 575kW into a 110 GHz accelerator structure using a quasi-optical setup. The standing structure consisted of a central copper cavity located between two matching cavities fed by a TM01 mode. The 6 ns input pulses were sliced from 3 microsecond pulses from the gyrotron using a laser-driven silicon switch. We obtained an unprecedented high gradient up to 230MV/m corresponding to a peak surface electric field of more than 520 MV/m.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Advected carbon younger than the sediment fuels microbial metabolism in a pumped deep aquifer

Ever deeper wells are drilled worldwide to pump potable groundwater. Recent studies argue that overpumping compresses clays and releases reactive dissolved organic carbon (DOC), which in turn drives a series of microbial reactions that affect groundwater potability including arsenic concentrations. Here, we use a novel method to measure the radiocarbon ages of microbial RNA to determine the source of reactive or metabolizable DOC and argue against the compression of clays as the sole source of carbon. We show that microbial RNA (5,230; 5,550; 6,250 yr; n = 3 wells), DOC (280-10,800 yr; n = 13), and methane (modern to 6,240 yr; n = 3), from an overpumped deep aquifer in Bangladesh are much younger than the overlying clay layers deposited during the Pleistocene over 12,000 years ago. Mass-balance indicates that at least half of the carbon incorporated into RNA has to come from reactive DOC or methane that is advected downward via vertical recharge. This metabolism of advected organic carbon could have implications for the quality of water pumped from deep aquifers.

Biological and medical sciences↗
DOE OSTI2022

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗