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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Bright Infrared‐to‐Ultraviolet/Visible Upconversion in Small Alkaline Earth‐Based Nanoparticles with Biocompatible CaF 2 Shells

Abstract Upconverting nanoparticles (UCNPs) are promising candidates for photon‐driven reactions, including light‐triggered drug delivery, photodynamic therapy, and photocatalysis. Herein, we investigate the NIR‐to‐UV/visible emission of sub‐15 nm alkaline‐earth rare‐earth fluoride UCNPs (M 1− x Ln x F 2+ x , MLnF) with a CaF 2 shell. We synthesize 8 alkaline‐earth host materials doped with Yb 3+ and Tm 3+ , with alkaline‐earth (M) spanning Ca, Sr, and Ba, MgSr, CaSr, CaBa, SrBa, and CaSrBa. We explore UCNP composition, size, and lanthanide doping‐dependent emission, focusing on upconversion quantum yield (UCQY) and UV emission. UCQY values of 2.46 % at 250 W cm −2 are achieved with 14.5 nm SrLuF@CaF 2 particles, with 7.3 % of total emission in the UV. In 10.9 nm SrYbF:1 %Tm 3+ @CaF 2 particles, UV emission increased to 9.9 % with UCQY at 1.14 %. We demonstrate dye degradation under NIR illumination using SrYbF:1 %Tm 3+ @CaF 2 , highlighting the efficiency of these UCNPs and their ability to trigger photoprocesses.

Fischer, Stefan↗
DOE OSTI2020

Bright Infrared‐to‐Ultraviolet/Visible Upconversion in Small Alkaline Earth‐Based Nanoparticles with Biocompatible CaF 2 Shells

Abstract Upconverting nanoparticles (UCNPs) are promising candidates for photon‐driven reactions, including light‐triggered drug delivery, photodynamic therapy, and photocatalysis. Herein, we investigate the NIR‐to‐UV/visible emission of sub‐15 nm alkaline‐earth rare‐earth fluoride UCNPs (M 1− x Ln x F 2+ x , MLnF) with a CaF 2 shell. We synthesize 8 alkaline‐earth host materials doped with Yb 3+ and Tm 3+ , with alkaline‐earth (M) spanning Ca, Sr, and Ba, MgSr, CaSr, CaBa, SrBa, and CaSrBa. We explore UCNP composition, size, and lanthanide doping‐dependent emission, focusing on upconversion quantum yield (UCQY) and UV emission. UCQY values of 2.46 % at 250 W cm −2 are achieved with 14.5 nm SrLuF@CaF 2 particles, with 7.3 % of total emission in the UV. In 10.9 nm SrYbF:1 %Tm 3+ @CaF 2 particles, UV emission increased to 9.9 % with UCQY at 1.14 %. We demonstrate dye degradation under NIR illumination using SrYbF:1 %Tm 3+ @CaF 2 , highlighting the efficiency of these UCNPs and their ability to trigger photoprocesses.

Fischer, Stefan↗
DOE OSTI2023

Correlation of Broad Absorption Band with Small Singlet‐Triplet Energy Gap in Organic Photovoltaics

Abstract Organic photovoltaics (OPV) are one of the most effective ways to harvest renewable solar energy, with the power conversion efficiency (PCE) of the devices soaring above 19 % when processed with halogenated solvents. The superior photocurrent of OPV over other emerging photovoltaics offers more opportunities to further improve the efficiency. Tailoring the absorption band of photoactive materials is an effective way to further enhance OPV photocurrent. However, the field has mostly been focusing on improving the near‐infrared region photo‐response, with the absorption shoulders in short‐wavelength region (SWR) usually being neglected. Herein, by developing a series of non‐fullerene acceptors (NFAs) with varied side‐group conjugations, we observe an enhanced SWR absorption band with increased side‐group conjugation length. The underpinning factors of how molecular structures and geometries improve SWR absorption are clearly elucidated through theoretical modelling and crystallography. Moreover, a clear relationship between the enhanced SWR absorption and reduced singlet‐triplet energy gap is established, both of which are favorable for the OPV performance and can be tailored by rational structure design of NFAs. Finally, the rationally designed NFA, BO‐TTBr, affords a decent PCE of 18.5 % when processed with a non‐halogenated green solvent.

Chemistry↗
DOE OSTI2025

Millisecond Phase Transition Kinetics of Lyotropic Liquid Crystalline Nanoparticles Observed by Time‐Resolved Small Angle X‐ray Solution Scattering

This study investigates the dynamic behavior of lyotropic liquid crystal nanoparticles (LCNPs), which are widely recognized for their applications in drug delivery. By employing nanosecond near‐infrared laser pulse‐induced temperature jump (T‐jump) and time‐resolved X‐ray solution scattering, the structural dynamics of phase transitions in phytantriol‐based cubosomes and hexosomes are revealed. Both cubosome and hexosome LCNPs undergo phase transitions into noncrystalline phases at high temperatures. Their phase transition kinetics, occurring within milliseconds (ms) and involving one intermediate structure, are captured. Additionally, the reverse self‐assembly processes of LCNPs were observed, occurring on the timescale of a few hundred ms. To our knowledge, this is the first observation of LCNP T‐jump induced phase transitions on the ms timescale and their reverse self‐assembly. These findings provide valuable insights into the LCNP phase transition processes, with potential implications for drug delivery applications.

Chemistry↗
DOE OSTI2019

Automatic detection of small bowel tumors in wireless capsule endoscopy images using ensemble learning

Purpose Wireless Capsule Endoscopy (WCE) is a minimally invasive diagnosis tool for lesion detection in the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the significant amount of acquired data leads to difficulties in the diagnosis by the physicians; which can be eased with computer assistance. This paper addresses a method for the automatic detection of tumors in WCE by using a two‐step based procedure: region of interest selection and classification. Methods The first step aims to separate abnormal from normal tissue by using automatic segmentation based on a Gaussian Mixture Model (GMM). A modified version of the Anderson method for convergence acceleration of the expectation–maximization (EM) algorithm is proposed. The proposed features for both segmentation and classification are based on the CIELab color space, as a way of bypassing lightness variations, where the L component is discarded. Tissue variability among subjects, light inhomogeneities and even intensity differences among different devices can be overcome by using simultaneously features from both regions. In the second step, an ensemble system with partition of the training data with a new training scheme is proposed. At this stage, the gating network is trained after the experts have been trained decoupling the joint maximization of both modules. The partition module is also used at the test step, leading the incoming data to the most likely expert allowing incremental adaptation by preserving data diversity. Results This algorithm outperforms others based on texture features selected from Wavelets and Curvelets transforms, classified by a regular support vector machine (SVM) in more than 5%. Conclusions This work shows that simpler features can outperform more elaborate ones if appropriately designed. In the current case, luminance was discarded to cope with saturated tissue, facilitating the color perception. Ensemble systems remain an open research field. In the current case, changes in both topology and training strategy have led to significant performance improvements. A system with this level of performance can be used in current clinical practice.

Vieira, Pedro M.↗
DOE OSTI2024

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗
DOE OSTI2021

Development of an optimized and scalable method for isolation of umbilical cord blood-derived small extracellular vesicles for future clinical use

Abstract Extracellular vesicles (EV) are a promising therapeutic tool in regenerative medicine. These particles were shown to accelerate wound healing, through delivery of regenerative mediators, such as microRNAs. Herein we describe an optimized and upscalable process for the isolation of EV smaller than 200 nm (sEV), secreted by umbilical cord blood mononuclear cells (UCB-MNC) under ischemic conditions and propose quality control thresholds for the isolated vesicles, based on the thorough characterization of their protein, lipid and RNA content. Ultrafiltration and size exclusion chromatography (UF/SEC) optimized methodology proved superior to traditional ultracentrifugation (UC), regarding production time, standardization, scalability, and vesicle yield. Using UF/SEC, we were able to recover approximately 400 times more sEV per mL of media than with UC, and upscaling this process further increases EV yield by about 3-fold. UF/SEC-isolated sEV display many of the sEV/exosomes classical markers and are enriched in molecules with anti-inflammatory and regenerative capacity, such as hemopexin and miR-150. Accordingly, treatment with sEV promotes angiogenesis and extracellular matrix remodeling, in vitro. In vivo, UCB-MNC-sEV significantly accelerate skin regeneration in a mouse model of delayed wound healing. The proposed isolation protocol constitutes a significant improvement compared to UC, the gold-standard in the field. Isolated sEV maintain their regenerative properties, whereas downstream contaminants are minimized. The use of UF/SEC allows for the standardization and upscalability required for mass production of sEV to be used in a clinical setting.

Cardoso, Renato M. S.↗
DOE OSTI2020

Zeolite Nanosheets Stabilize Catalyst Particles to Promote the Growth of Thermodynamically Unfavorable, Small–Diameter Carbon Nanotubes

A challenge in the synthesis of single–wall carbon nanotubes (SWCNTs) is the lack of control over the formation and evolution of catalyst nanoparticles and the lack of control over their size or chirality. Here, zeolite MFI nanosheets (MFI–Ns) are used to keep cobalt (Co) nanoparticles stable during prolonged annealing conditions. Environmental transmission electron microscopy (ETEM) shows that the MFI–Ns can influence the size and shape of nanoparticles via particle/support registry, which leads to the preferential docking of nanoparticles to four or fewer pores and to the regulation of the SWCNT synthesis products. The resulting SWCNT population exhibits a narrow diameter distribution and SWCNTs of nearly all chiral angles, including sub–nm zigzag (ZZ) and near–ZZ tubes. Theoretical simulations reveal that the growth of these unfavorable tubes from unsupported catalysts leads to the rapid encapsulation of catalyst nanoparticles bearing them; their presence in the growth products suggests that the MFI–Ns prevent nanoparticle encapsulation and prologue ZZ and near–ZZ SWCNT growth. Furthermore, these results thus present a path forward for controlling nanoparticle formation and evolution, for achieving size– and shape–selectivity at high temperature, and for controlling SWCNT synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-component Dark Matter and small scale structure formation

We consider the evolution of non-thermal dark matter perturbations in models which contain both Weakly Interacting Massive Particles (WIMPs) and axions. Using constraints from existing observations we examine the percentage of WIMPs and axions that may comprise the cosmological dark matter budget in models with an Early Matter Dominated Epoch (EMDE) — where entropy production is important. After carefully tracking the thermal evolution of the various species by solving the Boltzmann equations, we consider the enhancement of perturbations that may have led to early structure formation for axions and WIMPs. We investigate the impact of enhanced perturbations on the parameter space of both species, after imposing existing constraints from indirect detection experiments. Given these constraints we establish the feasibility of axions to form miniclusters in the early universe in EMDEs for a given percentage of allowed WIMPs. We find that EMDEs with low reheat temperatures near the BBN limit are preferred for axion minicluster formation. When the EMDE is caused by string moduli, the WIMP contribution to the relic density is set by the moduli branching to dark matter at the level of ≲ $\mathcal{O}$ (10 −4 ).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

On small black holes in string theory

Abstract We discuss the worldsheet sigma-model whose target space is thed+1 dimensional Euclidean Schwarzschild black hole. We argue that in the limit where the Hawking temperature of the black hole,T, approaches the Hagedorn temperature,T H , it can be described in terms of a generalized version of the Horowitz-Polchinski effective theory. Ford≥ 6, where the Horowitz-Polchinski EFT [1, 2] does not have suitable solutions, the modified effective Lagrangian allows one to study the black hole CFT in an expansion in powers ofd− 6 andT H −T. AtT=T H , the sigma model is non-trivial for alld> 6. It exhibits an enhanced SU(2) symmetry, and is described by a non-abelian Thirring model with a radially dependent coupling. The resulting picture connects naturally to the results of [3–5], that relate Schwarzschild black holes in flat spacetime at largedto the two dimensional black hole. We also discuss an analogous open string system, in which the black hole is replaced by a system of two separated D-branes connected by a throat. In this system, the asymptotic separation of the branes plays the role of the inverse temperature. At the critical separation, the system is described by a Kondo-type model, which again exhibits an enhanced SU(2) symmetry. At larged, the brane system gives rise to the hairpin brane [6].

Physics↗
DOE OSTI2020

A predictive mirror twin Higgs with small Z2 breaking

The twin Higgs mechanism is a solution to the little hierarchy problem in which the top partner is neutral under the Standard Model (SM) gauge group. The simplest mirror twin Higgs (MTH) model — where a Z 2 symmetry copies each SM particle — has too many relativistic degrees of freedom to be consistent with cosmological observations. We demonstrate that MTH models can have an observationally viable cosmology if the twin mass spectrum leads to twin neutrino decoupling before the SM and twin QCD phase transitions. Our solution requires the twin photon to have a mass of ~20 MeV and kinetically mix with the SM photon to mediate entropy transfer from the twin sector to the SM. This twin photon can be robustly discovered or excluded by future experiments. Additionally, the residual twin degrees of freedom present in the early Universe in this scenario would be detectable by future observations of the cosmic microwave background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Gauge-invariant TMD factorization for Drell-Yan hadronic tensor at small $\mathcal{x}$

The Drell-Yan hadronic tensor for electromagnetic (EM) current is calculated in the Sudakov region $s\gg Q^2 \gg q^2_⊥$ with $\frac{1}{Q^2}$ accuracy, first at the tree level and then with the double-log accuracy. It is demonstrated that in the leading order in $N_c$ the higher-twist quark-quark-gluon TMDs reduce to leading-twist TMDs due to QCD equation of motion. The resulting tensor for unpolarized hadrons is EM gauge-invariant and depends on two leading-twist TMDs: $f_1$ responsible for total DY cross section, and Boer-Mulders function $h\frac{⊥}{1}$. The order-of-magnitude estimates of angular distributions for DY process seem to agree with LHC results at corresponding kinematics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗