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At least 307 records · Page 17

Pseudomonas sp. Strain 273 Degrades Fluorinated Alkanes

Fluorinated organic compounds have emerged as environmental constituents of concern. We demonstrate that the alkane degrader Pseudomonas sp. strain 273 utilizes terminally monofluorinated C 7 –C 10 alkanes and 1,10-difluorodecane (DFD) as the sole carbon and energy sources in the presence of oxygen. Strain 273 degraded 1-fluorodecane (FD) (5.97 ± 0.22 mM, nominal) and DFD (5.62 ± 0.13 mM, nominal) within 7 days of incubation, and 92.7 ± 3.8 and 90.1 ± 1.9% of the theoretical maximum amounts of fluorine were recovered as inorganic fluoride, respectively. With n-decane, strain 273 attained (3.24 ± 0.14) × 10 7 cells per μmol of carbon consumed, while lower biomass yields of (2.48 ± 0.15) × 10 7 and (1.62 ± 0.23) × 10 7 cells were measured with FD or DFD as electron donors, respectively. The organism coupled decanol and decanoate oxidation to denitrification, but the utilization of (fluoro)alkanes was strictly oxygen-dependent, presumably because the initial attack on the terminal carbon requires oxygen. Fluorohexanoate was detected as an intermediate in cultures grown with FD or DFD, suggesting that the initial attack on the fluoroalkanes can occur on the terminal methyl or fluoromethyl groups. Overall, the findings indicate that specialized bacteria such as Pseudomonas sp. strain 273 can break carbon–fluorine bonds most likely with oxygenolytic enzyme systems and that terminally monofluorinated alkanes are susceptible to microbial degradation. The findings have implications for the fate of components associated with aqueous film-forming foam (AFFF) mixtures.

54 ENVIRONMENTAL SCIENCES↗

Autonomous Synthesis and Inverse Design of Electrochromic Polymers with High Efficiency and Accuracy

Here, the design and synthesis of functional polymers, aimed at targeted properties through specific structures, have long been challenged by their complex and often nonlinear structure–property relationships. Key processes, including knowledge accumulation for predictive design and experimental refinement and validation, are traditionally labor-insensitive and time-consuming, making it difficult to balance accuracy and efficiency. Here, we introduce an accelerated, autonomous system for the on-demand synthesis of electronic polymers that achieves the desired electrochromic functionality with high accuracy and efficiency. Our approach leverages large language model-assisted data mining, a physics-informed copolymer machine learning model, and an AI-driven autonomous robotic workflow in the Polybot lab. Within 72 h, Polybot autonomously synthesized electrochromic polymers (ECPs) with targeted, previously-unreported color values, including green polymers with specific absorption profiles, precisely fine-tuning copolymer structures with a 5% step size in comonomer composition within a three-monomer system. A publicly accessible ECP informatics database has also been created to foster knowledge exchange.

AI-driven Robotic Lab↗

Accomplishing simple, solubility-based separations of rare earth elements with complexes bearing size-sensitive molecular apertures

Significance Rare earth metals, La–Lu, Sc, and Y, are essential components of electronic materials and permanent magnets in diverse technologies. But, their mining and separations chemistry are unsustainable and plagued with supply problems. Recycling of consumer materials containing rare earths is a promising new source of these critical materials but similarly requires efficient separations. We report the use of a tripodal hydroxylaminato ligand, TriNOx 3– , with rare earth cations that enable fast, efficient separations through a simple leaching process. This approach is expected to contribute to a new method for recycling postconsumer materials including lighting phosphors and magnets, to diversify and improve the sustainability of the rare earth metal supply chain.

36 MATERIALS SCIENCE↗

A Soft-Matter Biomolecular Memristor Synapse for Neuromorphic Systems

The goal of neuromorphic computing is to recreate the computational power and efficiency of the human brain with circuitry. The ability of the brain to solve complex real time tasks, while consuming 20 W of power on average, is made possible through its connection density, adaptability, and parallel processing. Recreating these features using traditional electronics circuit elements is incredibly difficult, and therefore, soft-matter memristors made of biomolecules similar to those found in biological synapses and capable of emulating various synaptic features can be used as neuromorphic hardware. In this work, we introduce and experimentally demonstrate an electronic neuron circuit capable of interacting with ionic, soft-matter memristors. These memristors are proven to exhibit short-term plasticity, especially paired-pulse facilitation and depression found in presynaptic terminals - features that are not found in state-of-the-art solid-state memristors. We make use of these features for applications in online learning by developing a synapse-neuron circuit which implements spike-rate-dependent plasticity (SRDP) as a learning function.

Weiss, Ryan↗

Cretin Memory Flow on Sierra

The Cretin iCOE project has a goal of enabling the efficient generation of Non-LTE opacities for use in radiation-hydrodynamic simulation codes using the Nvidia boards on LLNL’s upcoming Sierra system. Achieving the desired level of accuracy for some simulations require the use of a vary large number of atomic configurations (a configuration includes the atomic level for all electrons and how they are coupled together). The NLTE rate matrix needs to be solved separately in each zone. Calculating NLTE opacities can consume more time than all other physics packages used in a simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Control, Fault Management, and Grid Support Functionality of an MV AC-DC Solid State Transformer based EV Extreme Fast Charging Station

Electric vehicles (EVs) have become increasingly popular in recent times while revolutionizing the consumer and commercial transportation market. The development of charging infrastructure has become one of the priorities for increasing the adoption of EVs. Extreme fast charging (XFC) technology can reduce the so-called ’range anxiety’ of consumers as they significantly reduce the charging time. With the advent of wide band-gap (WBG) power devices and improvement in power electronic converters, medium voltage (MV) solid state transformer (SST) based XFC system has the potential to replace the traditional XFC stations because of the lower footprint, ease of installation, enhanced control feature, and better system efficiency. The control system design is one of the critical aspects of the SST development process. Careful consideration and detailed analysis are required to find out suitable control method for the SST based on its topology among different centralized and decentralized control architectures. Also, the control parameters selection and potential improvement to the transient response of the controller ought to be investigated. Another major concern of the SST is different types of internal fault which reduces the overall reliability of the XFC system. As a result, designing a robust protection system is essential. Among different fault modes, open circuit switch faults have received significant attention as an active research area because of their likelihood and severe effects on converters. Therefore, the power stages used in the XFC system require functional and accurate open circuit switch fault management methods. An equally significant aspect of this SST based XFC is its compatibility in a microgrid where there is no synchronous generator present. When the grid is not available, the XFC SSTs can provide grid forming capability and continue supplying the critical loads in islanded mode. The transition between grid connected and islanded mode, especially the grid resynchronization process has to be carefully performed for the safety of the microgrid components. The challenges posed by the aforementioned issues have inspired the work done in this dissertation. Here, a 13.2 kV, 1 MVA, AC/DC SST for the XFC system is examined and a comparative analysis is conducted to select the control architecture based on feasibility of implementation and performance. A detailed control parameter design process is demonstrated considering the sensor dynamics and delay. The selected decentralized control method is augmented by introducing a novel sensor-less load current feedforward method to provide better voltage regulation at the DC bus during a change of load. Next, in the fault management section, a hierarchical failure mode effect analysis (FMEA) is proposed to enable a systematic design of the internal fault protection of the XFC SST as there are limited examples in the literature regarding the analysis of the safety and design of the protection of a power electronic converter system. Novel open circuit switch fault management methods for the converters in the system are presented. Finally, XFC SST based MV microgrid operations in grid connected mode and islanded mode are explored. A secondary control method for grid resynchronization is presented and a design process of control parameters is shown to ensure the stability of the secondary voltage and frequency regulation.

30 DIRECT ENERGY CONVERSION↗

Aerosol-Jet Printed Sensors for Environmental, Safety, and Health Monitoring: A Review

An emergent direct-write approach, aerosol-jet printing (AJP), is gaining attention for the deployment of rapid and affordable microadditively manufactured energy-efficient sensors and printed electronics. AJP enables a broad range of ink viscosities (0.001–1 Pa s) for printing diverse materials ranging from ceramics and metals to polymers and biological matter. Reproducible, high-spatial-resolution features (≈10 µm), and wide standoff distances (1–11 mm) between the nozzle and the substrate facilitate conformal printing of complex geometrical designs on nonplanar—e.g., stepped or curved—surfaces. Here this paper aims to provide a comprehensive overview of state-of-the-art AJP-based sensors (e.g., strain and temperature gauges, biosensors, photosensors, humidity and surface acoustic wave sensors, dielectric elastomer actuators, and motion, smoke, and hazardous gas detectors) and to discuss prospective applications. The drive toward cost-effective devices that are smaller, lighter, and better-performing remains a frontier challenge in the field of printed electronics. Consequently, as AJP becomes increasingly utilized in the high-volume manufacturing of miniaturized active and passive sensors, it opens a pathway for facile large-scale fabrication of devices for a wide range of consumer and industrial applications, including transportation, agriculture, infrastructure, aerospace, national defense, and healthcare.

3-dimensional↗

Exposure to hazardous substances in Cathode Ray Tube (CRT) recycling sites in France

Highlights: • Chemical risks were assessed in the nine cathode ray tube screens recycling facilities. • The main hazardous agents are dust containing lead, cadmium, barium and yttrium. • Exposure and pollutant levels are described for different operations and processes. • All the operations and processes are concerned by significant levels of pollutants. • We suggest recommendations to reduce chemical risk. - Abstract: The Waste Electrical and Electronic Equipment (WEEE) or e-waste recycling sector has grown considerably in the last fifteen years due to the ever shorter life cycles of consumables and an increasingly restrictive policy context. Cathode Ray Tubes (CRTs) from used television and computer screens represent one of the main sources of e-waste. CRTs contain toxic materials such as lead, cadmium, barium, and fluorescent powders which can be released if recycling of CRTs is not appropriate. Exposure to these harmful substances was assessed in nine workshops where CRT screens are treated. Particulate exposure levels were measured using a gravimetric method and metals were analysed by plasma emission spectrometry. The maximum levels of worker exposure were 8.8 mg/m{sup 3}, 1504.3 μg/m{sup 3}, 434.9 μg/m{sup 3}, 576.3 μg/m{sup 3} and 2894.3 μg/m{sup 3} respectively for inhalable dust, barium, cadmium, lead and yttrium. The maximum levels of airborne pollutants in static samples were 39.0 mg/m{sup 3}, 848.2 μg/m{sup 3}, 698.4 μg/m{sup 3}, 549.3 μg/m{sup 3} and 3437.9 μg/m{sup 3} for inhalable dust, barium, cadmium, lead and yttrium. The most harmful operations were identified, and preventive measures for reducing the chemical risk associated with screen recycling were proposed. Workplace measurements were used to define recommendations for reducing the chemical risks in CRT screens recycling facilities and for promoting the design and development of “clean and safe” processes in emerging recycling channels.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A search model for topological insulators with high-throughput robustness descriptors

Topological insulators (TI) are becoming one of the most studied classes of novel materials because of their great potential for applications ranging from spintronics to quantum computers. To fully integrate TI materials in electronic devices, high-quality epitaxial single-crystalline phases with sufficiently large bulk bandgaps are necessary. Current efforts have relied mostly on costly and time-consuming trial-and-error procedures. Here we show that by defining a reliable and accessible descriptor {cflx X}TI, which represents the topological robustness or feasibility of the candidate, and by searching the quantum materials repository aflowlib.org, we have automatically discovered 28 TIs (some of them already known) in five different symmetry families. These include peculiar ternary halides, Cs{l_brace}Sn,Pb,Ge{r_brace}{l_brace}Cl,Br,I{r_brace}{sub 3}, which could have been hardly anticipated without high-throughput means. Our search model, by relying on the significance of repositories in materials development, opens new avenues for the discovery of more TIs in different and unexplored classes of systems.

36 MATERIALS SCIENCE↗

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗

A Dynamic Amplitude-Correcting Gradient Estimation Technique to Align X-ray Focusing Optics

High-brightness X-rays, as produced at synchrotrons and X-ray free electron laser (XFEL) facilities, are used to characterize materials in a variety of scientific experiments. In most cases, effective use of the high-energy light requires precisely-aligned focusing optics; one example being a compound refractive lens (CRL). To align a CRL, the position and rotation must be optimized along four axes. In practice, this is a labor-intensive, time-consuming manual process that can monopolize scarce experimental time at the necessary X-ray facilities. Models of the expected Xray transmission function suggest that this task can be automated; however, the temporally-varying intensity at X-ray free electron laser facilities preclude the direct use of standard implementations of optimization solvers such as steepest descent algorithms. In this paper, we propose a novel technique to estimate the gradient of noisy functions with temporally-varying amplitudes. We construct this dynamicamplitude correction by systematically sampling a fixed central location within the standard finite difference stencil, accounting for the observed changes in time, and normalizing the difference quotients against those fluctuations. In addition to a rigorous error analysis of the sampling technique, we demonstrate its efficacy in stochastic descent optimization methods. Further, we demonstrate how this approach may be implemented to optimize X-ray focusing optics at synchrotrons or XFEL facilities

97 MATHEMATICS AND COMPUTING↗

Design of an Open Smart Energy Gateway for Smart Meter Data Management

With the widespread deployment of electronic interval meters, commonly known as smart meters, came the promise of real-time data on electric energy consumption. Recognizing an opportunity to provide consumers access to their near real-time energy consumption data directly from their installed smart meter, we designed a mechanism for capturing those data for consumer use via an open smart energy gateway (OpenSEG). By design, OpenSEG provides a clearly defined boundary for equipment and data ownership. OpenSEG is an open-source data management platform to enable better data management of smart meter data. Effectively, it is an information architecture designed to work with the ZigBee Smart Energy Profile 1.x (SEP 1.x). It was specifically designed to reduce cyber-security risks and provide secure information directly from smart meters to consumers in near real time, using display devices already owned by the consumers. OpenSEG stores 48 hours of recent consumption data in a circular cache using a format consistent with commonly available archived (not real-time) consumption data such as Green Button, which is based on the Energy Services Provider Interface (ESPI) data standard. It consists of a common XML format for energy usage information and a data exchange protocol to facilitate automated data transfer upon utility customer authorization. Included in the design is an application program interface by which users can acquire data from OpenSEG for further post processing. A sample data display application is included in the initial software product. The data display application demonstrates that OpenSEG can help electricity use data to be retrieved from a smart meter and ported to a wide variety of user-owned devices such as cell phones or a user-selected database. This system can be used for homes, multi-family buildings, or small commercial buildings in California.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Introduction to Special Section: Machine Learning for Image-based Geologic Interpretation

Image-based geological interpretation has been a labor-intensive and time-consuming process because it requires well-trained geoscientists to identify geological structures, features, and textures from various types of images. These images include scanning electron microscopic images, optical microscopic images, optical photos, resistivity images, seismic volumes, remote-sensing images, etc. With fast-evolving machine learning (ML) technology and computing power in recent decades, computers can achieve nearhuman-level to super-human-level performance with scalable high efficiency in the computer vision field. These technological revolutions facilitated image-based geological interpretation in petroleum exploration and production. For example, a fault picking method applied to 3-D seismic volume data using deep learning can achieve superior performance in comparison to conventional auto-picking methods. In addition, under the new normal of low oil prices, the petroleum industry seeks cost-effective strategies such as automating traditionally labor-intensive processes. Nevertheless, the potential of applying ML to geological image interpretation is still facing a few key challenges including data scarcity, data distribution, poor data and/or label quality, data leakage, learning algorithms, model architecture, training methodologies, testing and evaluation metrics, hyper-parameters optimization, model drift, production deployment, and the like.

58 GEOSCIENCES↗

Stress dependent oxidation of sputtered niobium and effects on superconductivity

We report on the suppression of room temperature oxidation of DC sputtered niobium films and the effects upon the superconductive transition temperature, T{sub c}. Niobium was sputter-deposited on silicon dioxide coated 150 mm wafers and permitted to oxidize at room temperature and pressure for up to two years. Resistivity and stress measurements indicate that tensile films greater than 400 MPa resist bulk oxidation with measurements using transmission electron microscope, electron dispersive X-ray spectroscopy, x-ray photoelectric spectroscopy, and secondary ion mass spectrometry confirming this result. Although a surface oxide, Nb{sub 2}O{sub 5}, consumed the top 6–10 nm, we measure less than 1 at. % oxygen and nitrogen in the bulk of the films after the oxidation period. T{sub c} measurements using a SQUID magnetometer indicate that the tensile films maintained a T{sub c} approaching the dirty superconductive limit of 8.4 K after two years of oxidation while maintaining room temperature sheet resistance. This work demonstrates that control over niobium film stress during deposition can prevent bulk oxidation by limiting the vertical grain boundaries ability to oxidize, prolonging the superconductive properties of sputtered niobium when exposed to atmosphere.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Isothermal solidification for high-entropy alloy synthesis

Kinetically trapping the high-temperature states through rapid cooling solidification is widely used for the synthesis of high-entropy alloys (HEAs), especially those with intrinsically immiscible elemental combinations. However, strategies need to be developed to overcome the fundamental limitations of rapid cooling solidification in controlling the crystallinity, structure and morphology of HEAs. Here, in this study, we introduce an isothermal solidification strategy for the synthesis of HEAs by rapidly altering the metal alloy composition through liquid–liquid interface reactions at low temperatures, for example, from 25 °C to 80 °C. We use gallium (Ga)-based metal as the sacrificial reagent and mixing medium. By directing the reactions to the interfaces between the Ga-based liquid metal and an aqueous metal ion solution, the foreign metal ions can be reduced at the interfaces and incorporated into the liquid metal quickly. HEAs with various crystallinity (single crystal, mesocrystal, polycrystal and amorphous), morphology (zero, two and three dimensions) and compositions can be achieved through the isothermal solidification. Ga can be completely consumed, resulting in Ga-free HEAs. If desired, Ga can be one of the metal elements in the final products. In situ liquid phase transmission electron microscopy (TEM) studies and theoretical analysis show the isothermal solidification mechanisms. Our direct observations show the enhanced mixing of liquid metal elements and the solidification process with fluctuating nucleation dynamics. The isothermal solidification marks a powerful strategy for HEA synthesis through an unexplored pathway of kinetically trapping the high-entropy states.

Zhang, Qiubo [Lawrence Berkeley National Laborator↗

Computationally Accelerated Discovery and Experimental Demonstration of Gd0.5La0.5Co0.5Fe0.5O3 for Solar Thermochemical Hydrogen Production

Solar thermochemical hydrogen (STCH) production is a promising method to generate carbon neutral fuels by splitting water utilizing metal oxide materials and concentrated solar energy. The discovery of materials with enhanced water-splitting performance is critical for STCH to play a major role in the emerging renewable energy portfolio. While perovskite materials have been the focus of many recent efforts, materials screening can be time consuming due to the myriad chemical compositions possible. This can be greatly accelerated through computationally screening materials parameters including oxygen vacancy formation energy, phase stability, and electron effective mass. In this work, the perovskite Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF), was computationally determined to be a potential water splitter, and its activity was experimentally demonstrated. During water splitting tests with a thermal reduction temperature of 1,350°C, hydrogen yields of 101 μmol/g and 141 μmol/g were obtained at re-oxidation temperatures of 850 and 1,000°C, respectively, with increasing production observed during subsequent cycles. This is a significant improvement from similar compounds studied before (La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 and LaFe 0.75 Co 0.25 O 3 ) that suffer from performance degradation with subsequent cycles. Confirmed with high temperature x-ray diffraction (HT-XRD) patterns under inert and oxidizing atmosphere, the GLCF mainly maintained its phase while some decomposition to Gd 2-x La x O 3 was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Classifying handedness in chiral nanomaterials using label error robust deep learning

Abstract High-throughput scanning electron microscopy (SEM) coupled with classification using neural networks is an ideal method to determine the morphological handedness of large populations of chiral nanoparticles. Automated labeling removes the time-consuming manual labeling of training data, but introduces label error, and subsequently classification error in the trained neural network. Here, we evaluate methods to minimize classification error when training from automated labels of SEM datasets of chiral Tellurium nanoparticles. Using the mirror relationship between images of opposite handed particles, we artificially create populations of varying label error. We analyze the impact of label error rate and training method on the classification error of neural networks on an ideal dataset and on a practical dataset. Of the three training methods considered, we find that a pretraining approach yields the most accurate results across label error rates on ideal datasets, where size and other morphological variables are held constant, but that a co-teaching approach performs the best in practical application.

36 MATERIALS SCIENCE↗

Solid breeder material crystal structure evolution due to Li burn up–Loss of crystal stability

Solid breeder materials for fusion power plants are subjected to extreme conditions of radiation damage, high temperature and designed component burn-up. Here, the loss of lattice stability of Li 2 TiO 3 due to Li burn-up was investigated using first principles-based approaches to aid evaluation of upper limit of component lifetime. The lattice stability is analyzed using calculated phonon dispersion in the Li 2 TiO 3 supercell, while Li burn-up is modeled by the introduction of Li-vacancies. It has been determined that the studied ceramic can be structurally stable up to ~40% of Li atoms burn-up. At 50% burn-up, the negative frequency branch in the phonon dispersion spectrum appears indicating the loss of lattice dynamical stability. Moreover, the structure obtained by introduction of unstable frozen phonons with minima energy amplitude also results in a phonon dispersion with negative branches in the structure obtained. Therefore, the system completely loses stability when approximately half of Li atoms are consumed.

36 MATERIALS SCIENCE↗