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28 records · Page 2

Self‐Standing Carbon Nanofibers@Carbon Felt Electrodes to Boost Electrolyzer Productivity: Application to the Electro‐Manufacturing of trans ‐3‐Hexenedioic Acid and Adipic Acid

The industrial implementation of electrosynthesis for chemical manufacturing remains constrained by the limited surface area of conventional electrodes. Herein, this challenge is addressed by designing a carbon nanofiber@carbon felt (CNF@CF) electrode platform that combines the high conductivity, flexibility, and ease of handling of commercial carbon felts (CF) with the large surface area and tunable surface chemistry of carbon nanofibers (CNFs). CNFs are deliberately grown onto the CF scaffold to form a sword-in-sheath structure, where entangled nanofibers wrap the felt macrofibers to provide excellent mechanical stability and electrical conductivity without binders. CNF@CF is evaluated both as an electrode and as a catalyst support for the electrochemical hydrogenation of cis,cis-muconic acid (ccMA), a biobased platform molecule key to the production of performance polyamides and renewable Nylon 6,6. As a noncatalytic electrode for the partial hydrogenation to trans-3-hexenedioic acid, CNF@CF achieves a threefold increase in both cumulative productivity and Faradaic efficiency (FE) compared to bare CF. A similar boost in catalytic activity and energy efficiency is observed using Pd/CNF@CF for the hydrogenation of ccMA to adipic acid. These results highlight the opportunities of the CNF@CF platform for electro-organic synthesis and sustainable chemical manufacturing.

electrochemical hydrogenation

Cradle-to-gate life cycle assessment of advanced composite panels incorporating CO 2 -derived multi-walled carbon nanotubes and hemp fiber for sustainable building applications

Advanced composite panels represent a promising pathway to reducing carbon emissions in the construction industry, yet comprehensive environmental impact assessments remain limited. Here, in this study, we conduct a life cycle assessment (LCA) to evaluate the environmental impacts of innovative composite panels produced from multi-walled carbon nanotubes (MWCNTs), hemp fiber (HF), recycled carbon fiber (rCF), and recycled polypropylene (PP), exploring their potential as baseline structural equivalents to conventional gypsum board. MWCNTs and HF play a critical role in sequestering carbon during raw material production, while the recycling processes for CF and PP generally require less energy compared to virgin material production. The LCA evaluates environmental performance using the TRACI 2.1 method, covering global warming potential (GWP), ozone depletion, smog formation, acidification, eutrophication, carcinogenic and non-carcinogenic effects, respiratory impacts, ecotoxicity, and fossil fuel depletion. Compositional variations—resin type (virgin vs. recycled), rCF content (9–29 wt%), and HF content (10–30 wt%)—are introduced for sensitivity and hotspot analyses. Results demonstrate that, when compared on the basis of preliminary structural equivalence, increasing recycled PP, rCF, and HF content can significantly reduce global warming potential compared to gypsum board. Beyond carbon reduction, the composite panels show trade-offs across other environmental categories. With the growing demand for composite materials in interior panels, ceiling systems, and exterior claddings, these findings highlight the environmental benefits and potential trade-offs of the proposed composites, establishing a foundational framework to support their continued development toward full building-system integration.

Advanced composite manufacturing

Flight Tests of a Supersonic Natural Laminar Flow Airfoil

IR thermography was used to characterize the transition front on a S-NLF test article at chord Reynolds numbers in excess of 30 million Changes in transition due to Mach number, Reynolds number, and surface roughness were investigated - Regions of laminar flow in excess of 80% chord at chord Reynolds numbers greater than 14 million IR thermography clearly showed the transition front and other flow features such as shock waves impinging upon the surface A series of parallel oblique shocks, of yet unknown origin, were found to cause premature transition at higher Reynolds numbers. NASA has a current goal to eliminate barriers to the development of practical supersonic transport aircraft Drag reduction through the use of supersonic natural laminar flow (S-NLF) is currently being explored as a means of increasing aerodynamic efficiency - Tradeoffs work best for business jet class at M<2 Conventional high-speed designs minimize inviscid drag at the expense of viscous drag - Existence of strong spanwise pressure gradient leads to crossflow (CF) while adverse chordwise pressure gradients amplifies and Tollmien-Schlichting (TS) instabilities Aerion Corporation has patented a S-NLF wing design (US Patent No. 5322242) - Low sweep to control CF - dp/dx < 0 on both wing surfaces to stabilize TS - Thin wing with sharp leading edge to minimize wave drag increase due to reduction in sweep NASA and Aerion have partnered to study S-NLF since 1999 Series of S-NLF experiments flown on the NASA F-15B research test bed airplane Infrared (IR) thermography used to characterize transition - Non-intrusive, global, good spatial resolution - Captures significant flow features well

laminar flow

Development of a deep potential model for F and CF 2 etching of Si and SiO 2

An understanding of plasma-surface interactions at increasingly smaller scales is invaluable for the development of novel technologies and processing techniques. Molecular dynamics (MD) simulations can provide insights into atomic-scale interactions, though they are restricted by the availability of interatomic potentials. Machine learning methods, such as Deep Potential Molecular Dynamics (DeepMD), provide a systematic framework for the development of accurate and flexible ab initio-based models. In this work, we develop DeepMD models for the ion-enhanced etching of Si and SiO 2 by F and CF 2 radicals. We employ an active learning process to expand the data set on which the model is trained and demonstrate its effect on the model accuracy. The DeepMD results are compared to data from classical MD simulations and experiments. Physical sputtering yields of SiO 2 by Ar + ions show good agreement with previous simulation results using conventional interatomic potentials, though the predicted depth profiles are different. Etching yields are calculated as a function of ion energy and neutral to ion flux ratio for the Ar + ion-enhanced etching of SiO 2 and Si by F atoms, as well as for etching of SiO 2 by CF 2 radicals, showing reasonable agreement with experimental data. Finally, an ion-enhanced surface kinetic model is fitted to the DeepMD etch yields, and the fitted parameters are compared to quantities computed directly from DeepMD simulations. This study illustrates how molecular dynamics simulations using machine learning potentials can provide an accurate model of etching processes relevant to device manufacturing.

Kounis-Melas, Andreas [Princeton Univ., NJ (United

Carbon Nanotube – Polysiloxane Nanocomposites for Ablative Thermal Protection Systems

Ultra-high temperature resins (UHTR) such as polysiloxane possess excellent characteristics for ablation including low thermal conductivity, lightweight composition, high thermal resistance, and the ability to form a durable char layer. To enhance its mechanical strength, the aerospace industry utilizes fiber reinforcement, such as carbon fiber reinforced polysiloxane (CF-polysiloxane), due to its high strength-to-weight ratio. Carbon nanotubes (CNTs) have advantages over microfibers including higher specific strength, lower density, and customizable thermal conductivity. Their nano-scale dimensions allow for a more homogenous material compared to traditional microfibers. Conventional methods of incorporating CNTs into resins often have structural defects such as voids, CNT agglomerations, and randomly dispersed CNTs, resulting in marginal improvements in properties. A novel approach known as bulk nanocomposite laminating (BNL) has been introduced involving CNT densification, resin polymer infiltration, and pressurized curing to achieve a high packing density exceeding 35% by volume. Characterization and testing to simulate re-entry conditions is performed with a sample of CNT-polysiloxane nanocomposite cured onto a CF-polysiloxane backing. These samples are subjected to ablation by an oxyacetylene flame while collecting temperature data to evaluate thermal protection properties.

Palak B Patel

Failure analysis of the lithium battery: A study of the header deposit on the cell top and diffusion within the electrode glass seal using nuclear microanalysis and FFTIR spectroscopy

The Solid Rocket Booster Range Safety System (SRBRSS) uses a lithium/poly-carbon monofluoride primary battery as a source of electrical power. After cell fabrication and activation, some battery cells have shown self discharge. One possible source of this cell discharge has been suggested to be the formation and growth of a conducting crystallized chemical compound across the glass bead insulator, electrically shorting the glass bead to the casing. This laboratory has begun an analysis of this compound, the glass seal holding the cathode into place, and the cell electrolyte, using Fast Fourier Transform Infrared (FFTIR) Analysis, Rutherford Backscattering Spectroscopy (RBS), and Nuclear Reaction Microanalysis. Preliminary measurements have confirmed the existence of lithium, nitrogen, fluorine, and oxygen on a reddish-brown deposit covering parts of the glass seal holding the positive electrode in place. Cells using Li metal electrodes, have many advantages over conventional primary batteries. One principal disadvantage of using Li batteries on a commercial basis would be the environmental impact of the fluorocarbon material. Another would be the relatively high expense of (CF)n.

Hassan, Razi A.

Fluorinated ionic liquids as gas chromatographic stationary phases for the separation of volatile per- and polyfluoroalkyl substances

Background Here, the production of fluorinated organic compounds in the manufacturing, semiconductor, and pharmaceutical industries has increased exponentially over the past decade. This rapid growth has created an urgent need for efficient chromatographic platforms capable of selectively separating these compounds from complex mixtures, not only to support industrial quality control and waste management practices, but also to enable reliable environmental monitoring of volatile fluorinated contaminants. Conventional GC stationary phases lack the fluorophilic interactions needed for highly fluorinated analytes. Consequently, there is a clear demand for specialized stationary phases designed to improve chromatographic retention and selectivity for these compounds. Results Three stationary phases composed of fluorinated ionic liquids (ILs) with varied extent of fluorination were prepared to study fluorophilic interactions with fluorinated/non-fluorinated probe molecules by gas chromatography (GC). IL stationary phases featuring linear and branched perfluoroalkyl moieties, as well as a branched alkyl moiety, were systematically investigated. Chromatographic performance was examined using fluorinated compounds and their hydrocarbon analogs, including CF 3 -substituted aromatics, aliphatic alcohols, fluorotelomer alcohols (FTOHs), and perfluoroalkenes. Measurements on 5 m and 20 m columns revealed that the IL possessing branched alkyl provided stronger dispersive and hydrogen bonding interactions toward non-fluorinated aromatic and long-chain alcohols, whereas the fluorinated ILs enhanced retention of highly fluorinated FTOHs and perfluorodecene. Comprehensive two-dimensional GC (GC × GC), using a nonpolar primary column coupled with secondary columns featuring cross-bonded poly(trifluoropropylmethyl siloxane) (Rtx-200 ms), the branched fluorinated IL, or the branched non-fluorinated IL, highlighted complementary selectivity with the branched fluorinated IL providing the strongest interactions with fluorinated analytes. Significance These results demonstrate that fluorinated IL stationary phases are promising alternatives to conventional polysiloxane stationary phases for improving the separation of per- and polyfluoroalkyl substances and related fluorinated compounds. By correlating IL structure with fluorophilic interactions, this work establishes design principles for GC stationary phases that enable enhanced selectivity for highly fluorinated analytes while maintaining complementary interactions with non-fluorinated compounds.

Comprehensive two-dimensional GC

Properties of Multifunctional Hybrid Carbon Nanotube/Carbon Fiber Polymer Matrix Composites

For aircraft primary structures, carbon fiber reinforced polymer (CFRP) composites possess many advantages over conventional aluminum alloys due to their light weight, higher strength- and stiffness-to-weight ratios, and low life-cycle maintenance costs. However, the relatively low electrical and thermal conductivities of CFRP composites fail to provide structural safety in certain operational conditions such as lightning strikes. Carbon nanotubes (CNT) offer the potential to enhance the multi-functionality of composites with improved thermal and electrical conductivity. In this study, hybrid CNT/carbon fiber (CF) polymer composites were fabricated by interleaving layers of CNT sheets with Hexcel® IM7/8852 prepreg. Resin concentrations from 1 wt% to 50 wt% were used to infuse the CNT sheets prior to composite fabrication. The interlaminar properties of the resulting hybrid composites were characterized by mode I and II fracture toughness testing. Fractographical analysis was performed to study the effect of resin concentration. In addition, multi-directional physical properties like thermal conductivity of the orthotropic hybrid polymer composite were evaluated.

Cano, Roberto J.

Rapid neutron and gamma-ray source localization using machine learning

Rapid localization of radiation sources is critical for applications including nuclear emergency response, safeguards, and security. However, conventional imaging systems such as neutron scatter cameras and Compton cameras depend on rare coincidence events, which often result in long acquisition times. In this work, we address the challenge of rapid source localization by developing a machine learning approach to predict the direction of a single radiation source using only count rates from an array of neutron and gamma-ray detectors. The proposed model is a fully connected neural network (FCNN) trained using Monte Carlo simulation data from a 252 Cf source. The model hyperparameters are optimized with a small set of routine 252 Cf measurements. We benchmarked the performance of the trained and optimized machine learning model using additional 252 Cf , 137 Cs , and PuBe measurements under laboratory conditions with varying source-detector configurations. For these measurements, the machine learning model achieved a mean localization error smaller than 30° with 3 x 10 3 system counts, corresponding to 8 s measurement time for the imaging system used in this work. In this low-statistics regime, the method outperformed traditional scatter-based imaging by more than 75% in localization accuracy for the evaluated measurement configurations. These results demonstrate that a machine learning-based approach can significantly reduce the time required for accurate single-source localization, providing a robust and computationally efficient alternative to traditional imaging systems in time-critical nuclear security and emergency response scenarios.

Gamma-ray imaging

Long carbon fibers boost performance of dry processed Li-ion battery electrodes

Dry processing (DP) is an advanced manufacturing technique for lithium-ion battery (LIB) electrodes. Unlike conventional wet-process-based manufacturing that involves dissolving polyvinylidene fluoride (PVDF) binder in n-methyl-2-pyrrolidone (NMP) solvent for slurry-casting, DP involves fibrillation of polymer binders. This method offers environmental and cost benefits by eliminating the need for expensive and environmentally hazardous organic solvents. However, DP-produced electrode films often lack mechanical stability due to the absence of a current collector substrate during electrode material layer fabrication. This reduced mechanical instability results in difficulty during fabricating of thin electrodes (≈5 mAh/cm 2 ). To address this issue, long (>8 mm) carbon fiber (CF) has been incorporated to reinforce the mechanical strength of the electrode films. In conclusion, the study demonstrates that the inclusion of long carbon fiber boosts the mechanical, electrical, thermal, and electrochemical performance of DP electrodes.

25 ENERGY STORAGE