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At least 1,009 records · Page 56

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗

Synchronization of chaotic systems

We review some of the history and early work in the area of synchronization in chaotic systems. We start with our own discovery of the phenomenon, but go on to establish the historical timeline of this topic back to the earliest known paper. The topic of synchronization of chaotic systems has always been intriguing, since chaotic systems are known to resist synchronization because of their positive Lyapunov exponents. The convergence of the two systems to identical trajectories is a surprise. We show how people originally thought about this process and how the concept of synchronization changed over the years to a more geometric view using synchronization manifolds. We also show that building synchronizing systems leads naturally to engineering more complex systems whose constituents are chaotic, but which can be tuned to output various chaotic signals. We finally end up at a topic that is still in very active exploration today and that is synchronization of dynamical systems in networks of oscillators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine

Here, we analyze a steady-state thermoelectric engine, whose working substance consists of two capacitively coupled quantum dots. One dot is tunnel-coupled to a hot reservoir serving as a heat source, the other one to two electrically biased reservoirs at a colder temperature, such that work is extracted under the form of a steady-state current against the bias. In single realizations of the dynamics of this steady-state engine autonomous, four-stroke cycles can be identified. The cycles are purely stochastic, in contrast to mechanical autonomous engines which exhibit self-oscillations. In particular, these cycles fluctuate in direction and duration and occur in competition with other spurious cycles. Using a stochastic thermodynamic approach, we quantify the cycle fluctuations and relate them to the entropy produced during individual cycles. We identify the cycle mainly responsible for the engine performance and quantify its statistics with tools from graph theory. We show that such stochastic cycles are made possible because the work extraction mechanism is itself stochastic instead of the periodic time dependence in the working-substance Hamiltonian which can be found in conventional mechanical engines. Our investigation brings new perspectives about the connection between cyclic and steady-state engines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hardware-in-the-Loop Investigation of Emissions Challenges in Hybrid Medium- and Heavy-Duty Powertrains Using a Pre-Production Diesel-Electric Parallel Hybrid System With and Without Stop-Start Operation

Hybrid electric powertrains are a growing market in medium- and heavy-duty applications. There is a lack of available information to understand the challenges in the integration of engine platforms into electrified powertrains, such as cold-start, restart, and load-reduction effects on emissions and emission control devices. Results from the Heavy Heavy-Duty Diesel Truck (HHDDT) cycle using a conventional medium-duty diesel engine were compared with those of a parallel hybrid architecture. Oak Ridge National Laboratory in collaboration with the US Department of Energy and Odyne Systems, LLC developed a powertrain in a hardware-in-the-loop environment, integrating the Odyne Systems, LLC medium-duty parallel hybrid system, which was used for the hybrid portion of this study. Experiments under the HHDDT cycle showed increasing improvements in fuel consumption and engine-out emissions with the integration of stop/start, hybrid, and hybrid with stop/start. However, the effects of load reduction and exhaust temperature on the thermal management strategy have shown an increase in fueling in the second part of the HHDDT cycle. Four configurations of medium-duty electrification were studied and contributed to building a unique data set containing combustion, emissions, and system integration data. Each electrification level was compared with the conventional baseline. The calibration of the conventional engine was not altered for this study. Opportunities to tailor the combustion process were identified with the stop/start strategy.

Lerin, Chloe↗

Extreme Miller cycle with high intake boost for improved efficiency and emissions in heavy-duty diesel engines

This study experimentally investigates the impact of extreme Miller cycle strategies paired with high intake manifold pressures on the combustion process, emissions, and thermal efficiency of heavy-duty diesel engines. Well-controlled experiments isolating the effect of Miller cycle strategies on the combustion process were conducted at constant engine speed and load (1160 rpm, 1.76 MPa net IMEP) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Late intake valve closing (LIVC) timing strategies were compared to a conventional intake valve profile under either constant cylinder composition, constant engine-out NO x emission, or constant overall turbocharger efficiency (η TC ) to investigate the operating constraints that favor Miller cycle operation over the baseline strategy. Furthermore, utilizing high boost with conventional intake valve closing timing resulted in improved fuel consumption at the expense of sharp increases in peak cylinder pressures, engine-out NO x emissions, and reduced exhaust temperatures. Miller cycle without EGR at constant λ demonstrated LIVC strategies effectively reduce engine-out NO x emissions by up to 35%. However, Miller cycle associated with very aggressive LIVC timings led to fuel consumption penalties due to increased pumping work and exhaust enthalpy. LIVC strategies allowed for increased charge dilution at the baseline NO x constraint of 3.2 g/kWh, resulting in significant fuel consumption benefits over the baseline case without compromising exhaust temperatures or peak cylinder pressures. As Miller cycle implementation was shown to affect the boundary conditions dictating η TC , the LIVC and conventional IVC cases were studied at an equivalent η TC point representative of high boost operation. With high boost, LIVC yielded reduced NO x emissions, reduced peak cylinder pressures, and elevated exhaust temperatures compared to the conventional IVC case without compromising fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Los Alamos National Security, LLC Request for Information on how industry may partner with the Laboratory on KIVA software.

KIVA is a family of Fortran-based computational fluid dynamics software developed by LANL. The software predicts complex fuel and air flows as well as ignition, combustion, and pollutant-formation processes in engines. The KIVA models have been used to understand combustion chemistry processes, such as auto-ignition of fuels, and to optimize diesel engines for high efficiency and low emissions. Fuel economy is heavily dependent upon engine efficiency, which in turn depends to a large degree on how fuel is burned within the cylinders of the engine. Higher in-cylinder pressures and temperatures lead to increased fuel economy, but they also create more difficulty in controlling the combustion process. Poorly controlled and incomplete combustion can cause higher levels of emissions and lower engine efficiencies.

33 ADVANCED PROPULSION SYSTEMS↗

Green Power Initiative

National energy policy supports the gathering of more detailed and authoritative data on the introduction of renewable bio-based fuels into new and existing district energy systems via the application of biomass gasification. The University of Iowa developed a biomass-fueled, university-scale steam generation system based on biomass gasification technologies. The system serves as a state-of-the-art research and educational facility in the emerging application of gasification in steam generation. The facility, which includes a smaller down-draft gasifier and a larger multi-stage biomass boiler, was designed to operate primarily on wood-based fuels, but has provisions for testing other biomass fuel sources produced within a 100-mile radius, providing enough flexibility to meet the fluctuating local supply of biomass from industry and Midwest agriculture. The equipment was installed in an existing, staffed facility. The down-draft gasifier unit is operated by College of Engineering staff and students, under the direct technical supervision of qualified Utilities plant staff. The Green Power Initiative also includes a substantial, innovative educational component. In addition to an onsite, graduate-level research program in biomass fuels, the investigators have integrated undergraduate and graduate level teaching – through classroom studies and experiential learning – and applied research into a biomass-based, university-scale, functioning power plant. University of Iowa is unique in that it currently has multiple renewable energy technologies deployed, including significant biomass combustion (oat hulls) at its Main Power Plant and a new reciprocating engine based renewable district energy system. This project complements and supports the national energy policy and State of Iowa initiatives in ethanol and biodiesel. Byproducts of ethanol and biodiesel processes (distiller grains) as well as industry residues (oat hulls, wood chips, construction and demolition waste), farm related material (seed corn and soybean seed), and poplar trees for cleaning up ground water are logical feed stocks for gasification.

09 BIOMASS FUELS↗

Red Storm Case Study

Sandia and Cray Inc. co-developed Red Storm, a distributed memory, massively paralleled highperformance supercomputer modeled on ASCI Redl, to run computer codes used for conducting materials science simulations for national security. Supercomputers have some of the fastest highperformance systems available and are used primarily for scientific and engineering work requiring exceedingly high-speed computations. Unlike conventional computers, supercomputers have large storage capacity; more than one central processing unit to rapidly retrieve stored data and program instructions; and input/output capability.

97 MATHEMATICS AND COMPUTING↗

Investigation of Cutter–Woodchip Contact Pressure in a New Biomass Comminution System

A Crumbler ® rotary shear system was recently developed to process fuel-grade woodchips into feedstocks having more uniform particle sizes for improved flowability and higher thermochemical output yield than a traditional hammer mill. It represents a significant innovation in the state of the art of biomass comminution equipment. However, the milling unit has experienced significant abrasive wear of the feeding teeth and cutters when processing hard and dusty feedstocks, such as logging residue and corn stover. Here, we present initial simulation results from a finite-element stress analysis of the rotary shear, which is used to investigate the dynamics of interaction between the cutters and woodchips. This is the first step for optimizing the cutter design to improve the system lifetime and processing efficiency, thus reducing downtime and improving overall productivity.

42 ENGINEERING↗

LanzaTech- Capturing Carbon. Fueling Growth.

LanzaTech will design a gas fermentation system that will significantly improve the rate at which methane gas is delivered to a biocatalyst. Current gas fermentation processes are not cost effective compared to other gas-to-liquid technologies because they are too slow for large-scale production. If successful, LanzaTech's system will process large amounts of methane at a high rate, reducing the energy inputs and costs associated with methane conversion.

42 ENGINEERING↗

Support system, excavation arrangement, and process of supporting an object

A support system, an excavation arrangement, and a process of supporting an object are disclosed. The support system includes a weight-bearing device and a camming mechanism positioned below the weight-bearing device. A downward force on the weight-bearing device at least partially secures the camming mechanism to opposing surfaces. The excavation arrangement includes a borehole, a support system positioned within and secured to the borehole, and an object positioned on and supported by the support system. The process includes positioning and securing the support system and positioning the object on the weight-bearing device.

42 ENGINEERING↗

My vehicle is a data mine

In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.

42 ENGINEERING↗

WBS 2.2.1.402 - Wave-SPARC: Systematic Process & Analysis for Reaching Commercialization

Wave-SPARC is empowering the marine energy community with the tools necessary to achieve a significant improvement in techno-economic performance of wave generated grid power. A detailed systems engineering approach simultaneously balances around 100 cost and performance drivers (functional requirements and capabilities) of wave energy converters (WECs). Publicly accessible technology innovation and assessment methods and tools (new to the wave energy sector) have been delivered. They guide technology development trajectories to successful outcomes in less time, at less overall cost, and with less encountered risk. Through the use of these methods and tools along with proven structured inventive techniques the project continues to deliver high potential novel wave energy technology concepts for validation and subsequent development by industry. The intended outcomes are: (1) Invention, assessment, identification, verification and validation of novel and high techno-economic-potential WEC technology concepts to deliver high-confidence "seeds" for subsequent industrial development to full commercial application and economic viability (2) Development and delivery of WEC technology innovation and assessment methodologies and tools and provision of these as services and for free use by industry and the entire sector (3) International collaboration for global best practice alignment of assessment and innovation methods.

innovation↗

Advanced, Energy-Efficient Hybrid Membrane System for Industrial Water Reuse

In the U.S. manufacturing sector, current industrial water use practices are energy-intensive and utilize and discharge high volumes of waters, rendering them not sustainable especially in light of the growing scarcity of suitable water supplies. To help address this problem, the goal of this project was to develop an advanced, cost-effective, hybrid membrane-based water treatment system that can improve the energy efficiency of industrial wastewater treatment while allowing at least 50% water reuse efficiency. This hybrid process would combine emerging Forward Osmosis (FO) and Membrane Distillation (MD) technology components into an integrated FO-MD system that can beneficially utilize low-grade waste heat (i.e., T < 450 °F) in industrial facilities to produce distilled-quality product water for reuse. In this project, laboratory-, bench-, and pilot-scale experiments on the hybrid FO-MD system were conducted for industrial wastewater treatment. It was demonstrated at laboratory, bench, and pilot scales that FO-MD membrane technology can concentrate brine to very high total dissolved solids (TDS) levels (>200,000 ppm) that are at least 2.5 times higher than the TDS level to which RO can achieve. In laboratory testing, currently available FO and MD membranes were tested to select for high-performing membranes with high salt rejection and high water flux. Multiple FO membrane/draw-salt solution combinations that gave high water flux with higher than 98% salt rejection were also identified. Reverse draw-salt fluxes were observed to be much lower for divalent salts than for monovalent salts. MD membranes were identified that had 99.9+% salt rejection and water flux as high as 50-90 L/(m 2 ·h) for flat-sheet membranes and >20 L/(m 2 ·h) for hollow fibers. In bench-scale testing, a single unit of commercially available FO and MD membrane modules were evaluated for continuous, integrated operation. Using the laboratory- and bench-scale test data, numerical modeling was performed on the FO and MD processes to estimate engineering parameters for a larger-scale pilot unit. Based on the experimental studies and modeling results, a pilot-scale, integrated FO-MD prototype unit was designed and built for trailer-mounted operation. This prototype system was fed real industrial wastewater, which could not be further treated by conventional technologies, from an oil production facility and was successfully operated for over 15 weeks without major stoppage. About 90% water recovery was possible, while concentrating the TDS from 12,000 ppm up to 190,500 ppm. The FO-MD prototype rejected most wastewater contaminants while producing water with <300 ppm TDS, even when the feed TDS was higher than 150,000 ppm. No chemical cleaning was necessary during the pilot testing period. Flushing the system with dechlorinated tap water was sufficient to reset the membranes for the next set of test conditions. Pilot performance and membrane autopsy showed that, even though the feed was concentrated more than 10 times, membrane fouling was unnoticeable and no defects were detected on the FO and MD membrane surfaces. This project demonstrated the technical feasibility of the hybrid FO-MD process by taking water already treated to the limit with the highest level of current technologies and further concentrating it 10-fold by using mostly low-cost materials. Because no membranes suitable for full-scale plant applications are available at present, economical feasibility of the hybrid technology is still uncertain, but it is expected that broader industry participation can further reduce FO-MD process costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. In this work, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13 C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

59 BASIC BIOLOGICAL SCIENCES↗

EXPLORING THE USE OF COGNITIVE MODELS FOR NUCLEAR POWER PLANT HUMAN-SYSTEM INTERFACE EVALUATION

Much of the United States commercial nuclear power plant fleet is approaching the end of their operating licenses. To extend the life of these plants, advanced human-system interface (HSI) technologies are being researched to address aging and reliability concerns with the existing legacy instrumentation and controls. Human factors engineering (HFE) has a crucial role in ensuring these technologies are designed in a way that does not introduce new failure modes and promote optimal human-system performance. An important focus of HFE in NPP modernization is the early involvement to inform the design of the HSI. Here, traditional formative evaluations are done to collect design feedback. While these evaluations are absolutely useful, they are limited in providing convincing quantitative data for efficiency of use. This paper discusses the use of cognitive models to provide such quantitative data early in the HSI design process. A comparison of three open-source and readily accessible cognitive modeling tools are discussed.

99 GENERAL AND MISCELLANEOUS↗

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗