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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

All-Polymer Solar Cells: Recent Progress, Challenges, and Prospects

For over two decades bulk-heterojunction polymer solar cell (BHJ-PSC) research was dominated by donor:acceptor BHJ blends based on polymer donors and fullerene molecular acceptors. This situation has changed recently, with non-fullerene PSCs developing very rapidly. The power conversion efficiencies of non-fullerene PSCs have now reached over 15 %, which is far above the most efficient fullerene-based PSCs. Among the various non-fullerene PSCs, all-polymer solar cells (APSCs) based on polymer donor-polymer acceptor BHJs have attracted growing attention, due to the following attractions: 1) large and tunable light absorption of the polymer donor/polymer acceptor pair; 2) robustness of the BHJ film morphology; 3) compatibility with large scale/large area manufacturing; 4) long-term stability of the cell to external environmental and mechanical stresses. This Minireview highlights the opportunities offered by APSCs, selected polymer families suitable for these devices with optimization to enhance the performance further, and discusses the challenges facing APSC development for commercial applications.

bio-inspired↗
DOE OSTI2016

Progressive Loss of Function in a Limb Enhancer during Snake Evolution

The evolution of body shape is thought to be tightly coupled to changes in regulatory sequences, but specific molecular events associated with major morphological transitions in vertebrates have remained elusive. In this paper, we identified snake-specific sequence changes within an otherwise highly conserved long-range limb enhancer of Sonic hedgehog (Shh). Transgenic mouse reporter assays revealed that the in vivo activity pattern of the enhancer is conserved across a wide range of vertebrates, including fish, but not in snakes. Genomic substitution of the mouse enhancer with its human or fish ortholog results in normal limb development. In contrast, replacement with snake orthologs caused severe limb reduction. Synthetic restoration of a single transcription factor binding site lost in the snake lineage reinstated full in vivo function to the snake enhancer. Our results demonstrate changes in a regulatory sequence associated with a major body plan transition and highlight the role of enhancers in morphological evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗
DOE OSTI2021

Microstructural Progression of Shear-Induced Mixing in a CuNi Alloy

Shear deformation has been highlighted in multiple research efforts for its ability to impart mechanical properties improvements and unique microstructures. When used to process and densify powdered material, these shear-based consolidation techniques are commonly referred to as friction consolidation (FC). In this paper, we have examined the microstructural evolution from compacted Cu and Ni powders to a consolidated Cu0.5Ni0.5 alloy. We have shown various stages of porosity reduction and preferential deformation being accommodated by the more ductile material early in the process, leading to formation of a tortuous microstructural zone. Porosity reduction was extensive, decreasing from ~65% in the unprocessed powder to ~1% in the fully consolidated alloy. The final consolidated alloy showed roughly a 2X hardness improvement over the unalloyed, compacted material. Unique aspects of this work include demonstration of the ability to use FC processing to produce a submicron and equiaxed grain size in samples within a 0.5 to 2 minute processing time.

Overman, Nicole R.↗
DOE OSTI2024

Progress and roadmap for electro-privileged transformations of bio-derived molecules

Biomass incorporates carbon captured from the atmosphere and can serve as a renewable feedstock for producing valuable chemicals and fuels. Here we look at how electrochemical approaches can impact biomass valorization, focusing on identifying chemical transformations that leverage renewable electricity and feedstocks to produce valorized products via electro-privileged transformations. First, we recommend that the field should explore widening the spectrum of platform chemicals derived from bio-feedstocks, thus offering pathways to molecules that have historically been derived from petroleum. Second, we identify opportunities in electrocatalytic production of energy-dense fuels from biomass that utilize water as the hydrogen source and renewable electricity as the driving force. Finally, we look at the potential in electrochemical depolymerization to preserve key functional groups in raw feedstocks that would otherwise be lost during harsh pre-treatments in traditional depolymerization routes. Finally, on the basis of these priorities, we suggest a roadmap for the integration of biomass and electrochemistry and offer milestones required to tap further into the potential of electrochemical biomass valorization.

electrocatalysis↗