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At least 1,315 records · Page 73

Bubble Transport through a Porous Lattice with an Applied Inlet Flow

Within gas-evolving electrochemical systems, bubbles negatively impact performance by covering electrode active sites for reactions, blocking electric field lines, and obstructing liquid electrolyte flow causing pressure buildup. Recent additive manufacturing advances have enabled tuned porous electrode microstructures to be created, but producing systems that maximize electrochemical throughput and minimize bubble impact remains challenging. Thus, improved physical understanding of and modeling capabilities for bubble behavior are critical to improve electrolyzer design. To address this need, this study examines rising stage bubbles within a lattice with an applied liquid flow—an underexplored regime that strongly influences an electrochemical bubble’s fate. Notably, theoretical predictions and resolved bubble simulations are complemented by experiments from a 3D-printed visualization cell that matches the simulation geometry. The minimum threshold flow rate to achieve bubble breakthrough is found to be larger for higher porosities and for smaller bubbles. Different-sized bubbles decrease expected electrochemical performance in different ways; smaller bubbles tend to stay stuck but cover less solid surface, while larger bubbles more readily break through but cover more surface while in the lattice. The bubble trajectory, deformation, and contact area provide insight into these different behaviors. These findings provide design guidelines toward creating more effective electrolyzers.

Guo, Jack [Lawrence Livermore National Laboratory ↗

Tuning nanoparticle size for enhanced functionality in perovskite thin films deposited by metal organic deposition

Because of pressing global environmental challenges, focus has been placed on materials for efficient energy use, and this has triggered the search for nanostructural modification methods to improve performance. Achieving a high density of tunable-sized second-phase nanoparticles while ensuring the matrix remains intact is a long-sought goal. In this paper, we present an effective, scalable method to achieve this goal using metal organic deposition in a perovskite system REBa 2 Cu 3 O 7 (rare earth (RE)) that enhances the superconducting properties to surpass that of previous achievements. We present two industrially compatible routes to tune the nanoparticle size by controlling diffusion during the nanoparticle formation stage by selecting the second-phase material and modulating the precursor composition spatially. Combining these routes leads to an extremely high density (8 × 10 22 m -3 ) of small nanoparticles (7 nm) that increase critical currents and reduce detrimental effects of thermal fluctuations at all magnetic field strengths and temperatures. This method can be directly applied to other perovskite materials where nanoparticle addition is beneficial.

36 MATERIALS SCIENCE↗

Data Acquisition System Selection and Calibration of Resistive Moisture Content Measurements for Large-Scale Field Studies in Cold Climate Residential Building Envelope Performance

The residential building stock built before the energy codes were enforced has several significant inefficiency problems in terms of insulation and air leakage. To decrease these inefficiencies, building retrofits are necessary. However, if the envelope is not appropriately designed, excessive accumulation of moisture content and thus mold formation and decay inside the envelope layers can be a vital problem. This risk becomes higher, especially in extreme climate conditions such as cold winters and hot and humid summers as in some northern regions of the U.S. Field studies are essential to test the long-term hygrothermal performance of building envelopes. Although in-situ temperature, RH, and heat flux measurements are straightforward, moisture content measurements are cumbersome. Mainly, because of the heterogeneous nature of the wood materials, deviations and nonuniformities within the materials are unavoidable. Resistance measurements are one of the oldest methods used to measure the moisture content of wood and other building materials. In large-scale studies, it is commonly preferred to use multi-purpose data acquisition systems (DAQ) and custom-made or prefabricated moisture pins to measure the electrical resistance (and thus moisture content) of critical building materials. These multi-purpose DAQ systems generally provide lower costs and offer more flexibility. However, these systems require calibration and fine-tuning to achieve accurate moisture content measurements. A large-scale, two-year-long field study was conducted in northern Minnesota to monitor the hygrothermal performance of residential retrofit wall systems in cold climates. Two base case walls and sixteen different wall treatments were tested. Moisture contents were measured at various layers in each wall treatment using 85 sets of moisture pins. This paper focuses on the overall approach, fabrication, and calibration methodology for the combination of custom-made moisture pins and a multi-purpose DAQ. The aim is to directly use the low-excitation multi-purpose DAQ without any extra voltage regulator. A half-bridge circuit is used to measure wood resistance with 4V excitation voltage and 100 kΩ and 500 kΩ reference resistors. The system is calibrated for four different materials: Douglas fir, lodgepole pine, western red cedar, and oriented strand board (OSB). Calibration experiments were done under controlled conditions in 50% and 65% RH test chambers. Resistance-based moisture content calibration curves are obtained for each species. Results show that higher reference resistors provided better calibration curves for lower excitation voltages.

Desjarlais, Andre Omer↗

Iridium Nanocrystals Enriched with Defects and Atomic Steps to Enhance Oxygen Evolution Reaction Performance

The presence of defects can significantly improve catalytic activity and stability, as they influence the binding of the reactants, intermediates, and products to the catalyst. Controlling defects in the structures of nanocrystal catalysts is synthetically challenging. In this study, we demonstrate the ability to control the growth of Ir nanocrystals, enabling the tuning of both structural and surface defects. The Ir nanocrystals have unique structures that range from single crystals of a few nanometers to twinned nanoparticles and multiply twinned crystallites with a high density of atomic steps. Further, this approach of defect engineering enables us to understand their roles in enhancing the performance of the OER and producing an Ir catalyst with both high activity and stability. Our results show the importance of the concept of using synthetic control of structural and surface defects in metal nanoparticles as a strategy to improve catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design options for a superconducting ion linac

Following a review of the design options for a superconducting ion linac, we present here an alternative design for the pre-stripper section of the superconducting driver linac for the rare isotope science project (RISP) of the Institute for Basic Science in Korea. The proposed alternative design takes advantage of the recent accelerator developments at Argonne, namely for the recent ATLAS intensity and efficiency upgrade and the Fermilab proton improvement plan project (PIP-II). In particular, the state-of-the-art performance of quarter-wave (QWRs) and half-wave resonators (HWRs), the integrated steering correctors and cold beam position monitors (BPMs) for a compact cryomodule design. In order to simplify the design and avoid frequency transitions, we used two types of QWRs at 81.25 MHz while the baseline design has QWRs at 81.25 MHz and HWRs at 162.5 MHz. The new QWR types were optimized for β ~0.05 and ~0.11, respectively, and corrected for beam steering effects. Nine cryomodules are required to reach the stripping energy of 18.5 MeV/u for uranium beam. An alternative radio-frequency quadrupole (RFQ) design was also developed. It is optimized with the multi-harmonic buncher (MHB) to produce a much smaller longitudinal emittance, offering much needed flexibility for beam tuning and more tolerance to errors. Following the lattice design optimization, end-to-end beam dynamics simulations including most important sources of machine error were performed. The results showed that the design is robust and tolerant to errors with no beam loss observed for typical machine errors.

43 PARTICLE ACCELERATORS↗

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗

Controlled synthesis of α-MnO{sub 2} nanowires and their catalytic performance for toluene combustion

Highlights: • One-dimensional α-MnO{sub 2} nanowires were prepared by a facile hydrothermal route. • Shape and crystal phase of the products were controlled by tuning reaction conditions. • A possible formation mechanism of the α-MnO{sub 2} nanowires was discussed. • The α-MnO{sub 2} nanowires showed great catalytic activity for toluene combustion. - Abstract: α-MnO{sub 2} nanowires with a length about 6–10 μm and an average diameter of 20 nm were synthesized through a facile hydrothermal process without any templates or surfactants. The products were characterized by X-ray powder diffraction, Raman spectroscopy, field emission scanning electron microscopy, transmission electron microscopy, hydrogen temperature-programmed reduction techniques, X-ray photoelectron spectroscopy and surface area analysis. The effects of the hydrothermal temperature and the concentration of CH{sub 3}COOH on the crystal phase and morphology of the final products were studied in detail. The hydrothermal temperature and the concentration of CH{sub 3}COOH play crucial roles in determining the crystal phase and morphology of the products. The possible formation mechanism of the α-MnO{sub 2} nanowires was investigated and discussed. Additionally, the as-prepared α-MnO{sub 2} nanowires showed higher catalytic activity for toluene combustion than the commercial MnO{sub 2}, suggesting their potential applications in the elimination of volatile organic compounds.

36 MATERIALS SCIENCE↗

Tuning the Quantum Dot (QD)/Mediator Interface for Optimal Efficiency of QD-Sensitized Near-Infrared-to-Visible Photon Upconversion Systems

Lead sulfide (PbS) quantum dots (QDs) have shown promising performance as a sensitizer in infrared-to-visible photon upconversion systems. To investigate the key design rules, we compare three PbS-sensitized upconversion systems using three mediator molecules with the same tetracene triplet acceptor at different distances from the QD. Using transient absorption spectroscopy, we directly measure the triplet energy-transfer rates and efficiencies from the QD to the mediator and from the mediator to the emitter. With increasing distance between the mediator and PbS QD, the efficiency of the first triplet energy transfer from the QD to the mediator decreases because of a decrease in the rate of this triplet energy-transfer step, while the efficiency of the second triplet energy transfer from the mediator to the emitter increases because of a reduction in the QD-induced mediator triplet state decay. The latter effect is a result of the slow rate constant of the second triplet energy-transfer process, which is 3 orders of magnitude slower than the diffusion-limited value. The combined results lead to a net decrease of the steady-state upconversion quantum yield with distance, which could be predicted by our kinetic model. Our result shows that the QD/mediator interface affects both the first and second triplet energy transfer processes in the photon upconversion system, and the QD/mediator distance has an opposite effect on the efficiencies of the first and second triplet energy transfer. Lastly, these findings provide important insight for the further rational improvement of the overall efficiency of QD-based upconversion systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning the Perfluorosulfonic Acid Membrane Morphology for Vanadium Redox-Flow Batteries

The microstructure of the perfluorinated sulfonic acid proton exchange membranes such as Nafion significantly affects their transport properties and performance in a vanadium redox flow battery (VRB). In this work, Nafion membranes with various equivalent weights (EW) ranging from 1000 to 1500 are prepared and the structure-property-performance relationship is investigated. Nuclear magnetic resonance (NMR) and small-angle X-ray scattering (SAXS) studies revealed their composition and morphology variances, which lead to major differences in key transport properties related to proton conduction and vanadium ion permeation. Their performances are further characterized as VRB membranes. Based on those understanding, a new perfluorosulfonic acid membrane is designed with optimal pore geometry and thickness, leading to higher ion selectivity and lower cost compared with the widely used Nafion® 115. Excellent VRB single-cell performance (89.3% energy efficiency at 50mA∙cm-2) was achieved along with a stable cyclical capacity over prolonged cycling.

25 ENERGY STORAGE↗

Over 15% Efficiency Polymer Solar Cells Enabled by Conformation Tuning of Newly Designed Asymmetric Small‐Molecule Acceptors

Abstract The prosperous period of polymer solar cells (PSCs) has witnessed great progress in molecule design methods to promote power conversion efficiency (PCE). Designing asymmetric structures has been proved effective in tuning energy level and morphology, which has drawn strong attention from the PSC community. Two hepta‐ring and octa‐ring asymmetric small molecular acceptors (SMAs) (IDTP‐4F and IDTTP‐4F) with S‐shape and C‐shape confirmations are developed to study the relationship between conformation shapes and PSC efficiencies. The similarity of absorption and energy levels between two SMAs makes the conformation a single variable. Additionally, three wide‐bandgap polymer donors (PM6, S1, and PM7) are chosen to prove the universality of the relationship between conformation and photovoltaic performance. Consequently, the champion PCE afforded by PM7: IDTP‐4F is as high as 15.2% while that of PM7: IDTTP‐4F is 13.8%. Moreover, the S‐shape IDTP‐4F performs obviously better than their IDTTP‐4F counterparts in PSCs regardless of the polymer donors, which confirms that S‐shape conformation performs better than the C‐shape one. This work provides an insight into how conformations of asymmetric SMAs affect PCEs, specific functions of utilizing different polymer donors to finely tune the active‐layer morphology and another possibility to reach an excellent PCE over 15%.

Guo, Qing↗

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series: Preprint

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗

Tuning the Lifetimes of Photoinduced Deligation in a Metal–Organic Framework via Linker Functionalization

Recently photoinduced dynamic ligation in a metal–organic frameworks (MOFs) was reported, where a long-lived charge-transfer excited state (ca. 30 μs) featuring partial dissociation between the carboxylate linker and metal-based node was probed by time-resolved infrared (TRIR) spectroscopy. The study offers a new mechanistic perspective to evaluate the potential contribution from the excited state molecular configuration to the performance of MOF photocatalysts. In this work, by employing MIL-101(Fe) as the study platform, we have further explored the influence of intramolecular interactions on the stability of relevant excited states and demonstrated the effective tuning of their lifetimes through the incorporation of different functional groups into the system. The correlations between the varied excited state lifetimes and coordination configurations with specific functional groups (−NH 2 or −NO 2 ) was inferred from the analyses of infrared spectroscopic data and theoretical calculations, revealing the essential role of the intramolecular interactions (i.e., between the added functional groups and the carboxylate group) in the modulation of system energetics. Overall, the work presents a pathway to tune the excited state dynamics and expands the knowledge regarding the photoinduced dynamic ligation in carboxylate-based MOFs.

excited states↗

Multimaterial 3D Printing in Activating Bath Enables In Situ Polymerization of Thermosets with Intricate Geometries and Diverse Elastic Behaviors

Polydicyclopentadiene, p(DCPD), is a high‐performance thermoset valued for its exceptional toughness, strength, and stiffness. When copolymerized with 1,5‐cyclooctadiene (COD), its mechanical properties can be tuned from glassy to rubbery at room temperature. While frontal polymerization enables a rapid and energy‐efficient route to 3D print DCPD‐based materials, challenges such as ink shelf life and gravitational distortion, especially in direct ink writing of soft COD‐rich formulations, must be considered. Here, a complementary chemical strategy is presented, embedded 3D printing, that enables localized in situ polymerization of printed DCPD/COD inks within a reactive support matrix. The matrix provides both physical support and a reservoir of chemical activator, which diffuses into the ink, activates a latent bis(N‐heterocyclic carbene) Ru precatalyst, and initiates ring‐opening metathesis polymerization. Curing begins at the ink–matrix interface and propagates inward via diffusion, stabilizing the interface and preventing capillary‐driven deformation regardless of the matrix yield stress. This approach eliminates the need for cold storage, external curing, or photoinitiation, significantly expanding the processing window. Using this method, diverse thermosetting and elastomeric architectures are fabricated with features as small as 5 µm and aspect ratios of 100, including interlinked chains, shallow spherical shells exhibiting snap‐through buckling, and hair‐like fin arrays inaccessible through traditional techniques.

chemical activation↗

Assessment of DFT methods for the prediction of detachment energies and electronic structures of complex and multiply charged anions

Here, in this work, we assess the ability of different density functional theory methods to reproduce the vertical/adiabatic detachment energies (VDEs/ADEs) of a series of 40 anions, including monoanion versus multiply charged anions (MCAs) and covalent versus noncovalent interaction. The statistical analysis of errors is firstly performed by comparing the theoretical values with the experimental benchmark data obtained from the negative ion photoelectron spectroscopy (NIPES). The proposed optimally tuned range-separated (OTRS) functionals are proved to not only well reproduce the experimental VDEs/ADEs, but also simulate experimental NIPES. The result implies a more serious issue of delocalization error for MCAs and a balanced description of electron-rich/- deficient region of anions is necessary. The radius of the spherically symmetric average electron localization function (ELF) region is demonstrated as a useful descriptor for the characterization of electronic structure of anionic systems and a quasilinear fitting model is proposed to efficiently obtain their OTRS parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Co-design of a wave energy converter for autonomous power

A "bolt-on" wave energy converter is designed to provide power for sensors on an existing oceanographic buoy. The narrow-banded pitch/roll response of the target oceanographic buoy lends itself to a tuned-resonator design, for which we suggest a novel "pitch resonator" wave energy converter concept. Using a pseudo-spectral method, the performance of the proposed wave energy converter is modeled in the range of sea states expected to be present at the target deployment location to study the e

Coe, Ryan Geoffrey↗

New Concepts in Electrolytes

Over the past decades, Li-ion battery (LIB) has turned into one of the most important advances in the history of technology due to its extensive and in-depth impact on our life. Its omnipresence in all electric vehicles, consumer electronics and electric grids relies on the precisely tuned electrochemical dynamics and interactions among the electrolytes and the diversified anode and cathode chemistries therein. Furthermore, with consumers' demand for battery performance ever increasing, more and more stringent requirements are being imposed upon the established equilibria among these LIB components, and it became clear that the state-of-the-art electrolyte systems could no longer sustain the desired technological trajectory. Driven by such gap, researchers started to explore more unconventional electrolyte systems. From superconcentrated solvent-in-salt electrolytes to solid-state electrolytes, the current research realm of novel electrolyte systems has grown to unprecedented levels. In this review, we will avoid discussions on current state-of-the-art electrolytes but instead focus exclusively on unconventional electrolyte systems that represent new concepts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗