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At least 181 records · Page 10

Natural transformation as a tool in Acinetobacter baylyi : Evolution by amplification of gene copy number

For many years, the natural competency of Acinetobacter baylyi ADP1 facilitated studies of bacterial metabolism, biochemistry, and physiology. With the advent of synthetic biology, new opportunities arise to exploit the remarkable transformability and chromosomal plasticity of this model organism. In this chapter, we describe a recently developed method, “Evolution by Amplification and Synthetic Biology” (EASy). EASy allows the targeted amplification of chromosomal segments that give rise to new phenotypes. Increased gene dosage regulates protein expression in a rudimentary fashion by establishing a chromosomal array in which copy number adjusts via recombination between repeated DNA sequences. Selective conditions enrich for cells within the population that confer a growth advantage. Under continuous selective pressure, beneficial mutations may accumulate in any genomic region. Such mutations favor decreases in the average copy number of the target region. Thus, the genetic flexibility afforded by transient copy number variation helps accelerate the selection of engineered strains with desired traits during laboratory evolution. As a result, thanks to the extremely simple genetic manipulation of Acinetobacter baylyi ADP1, the EASy method can be readily implemented by researchers without the need for advanced instrumentation or complex cloning techniques.

59 BASIC BIOLOGICAL SCIENCES↗

High-Performance Semiempirical Excited-State Molecular Dynamics Powered by Graphics Processing Units

Here, this Letter introduces excited-state molecular dynamics in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born–Oppenheimer molecular dynamics (BOMD) using configuration-interaction singles and random phase approximation for excited states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended Lagrangian excited-state BOMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The excited-state BOMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per MD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient excited-state BOMD simulations. Beyond raw performance, PYSEQM’s PyTorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as a practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic excited-state dynamics modeling of ultrafast spectroscopic probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure and Synthesizability of Iron–Sulfur Metal–Organic Frameworks

Sulfur-based metal–organic frameworks (MOFs) and coordination polymers (CPs) are an emerging class of hybrid materials that have received growing attention due to their magnetic, conductive, and catalytic properties with potential applications in electrocatalysis and energy storage. In this work, we report a high-throughput virtual screening protocol to predict the synthesizability of candidate metal–sulfur MOFs/CPs by computing the thermodynamically stable structures resulting from a particular combination of metal cluster, linker, cation, and synthetic conditions. Free energies are computed by using all-atom classical mechanical thermodynamic integration. Low-free-energy structures are refined using ab initio density functional theory, and pair distribution functions and powder X-ray diffraction patterns are calculated to complement and guide experimental structure determination. We validate the computational approach by retrospective predictions of the stable structure produced by experimental syntheses, and a subsequent screen predicts Fe 4 S 4 -BDT–TPP as a new thermodynamically stable one-dimensional (1D) CP comprising a redox-active Fe 4 S 4 cluster, a 1,4-benzenedithiolate (BDT) linker, and a tetraphenylphosphonium (TPP) countercation. Furthermore, this material is experimentally synthesized, and the 1D chain structure of the crystal is confirmed using microcrystal electron diffraction. The computational screening pipeline is generically transferable to neutral and ionic MOFs/CPs comprising arbitrary metal clusters, linkers, cations, and synthetic conditions, and we make it freely available as an open source tool to guide and accelerate the discovery and engineering of novel porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional genomics of the rapidly replicating bacterium Vibrio natriegens by CRISPRi

We present that the fast-growing Gram-negative bacterium Vibrio natriegens is an attractive microbial system for molecular biology and biotechnology due to its remarkably short generation time and metabolic prowess. However, efforts to uncover and utilize the mechanisms underlying its rapid growth are hampered by the scarcity of functional genomic data. Here, we develop a pooled genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) interference (CRISPRi) screen to identify a minimal set of genes required for rapid wild-type growth. Targeting 4,565 (99.7%) of predicted protein-coding genes, our screen uncovered core genes comprising putative essential and growth-supporting genes that are enriched for respiratory pathways. We found that 96% of core genes were located on the larger chromosome 1, with growth-neutral duplicates of core genes located primarily on chromosome 2. Lastly, our screen also refines metabolic pathway annotations by distinguishing functional biosynthetic enzymes from those predicted on the basis of comparative genomics. Taken together, this work provides a broadly applicable platform for high-throughput functional genomics to accelerate biological studies and engineering of V. natriegens.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing Scientific Productivity through Better Scientific Software: Developer Productivity and Software Sustainability Report

The Exascale Computing Project (ECP) provides a unique opportunity to advance computational science and engineering (CSE) through an accelerated growth phase in extreme-scale computing. Central to the project is the development of next-generation applications and software technologies that can exploit emerging architectures for optimal performance and provide high-fidelity, multiphysics, multiscale capabilities. However, disruptive changes in computer architectures and the complexities of tackling new frontiers in extreme-scale modeling, simulation, and analysis present daunting challenges to the productivity of software developers and the sustainability of software artifacts. Members of the CSE community - especially at extreme scales but more broadly at all scales of computing - face an urgent need to improve developer productivity, positively impacting product quality, development time, and staffing resources, and software sustainability, reducing the cost of maintaining, sustaining, and evolving software capabilities.

97 MATHEMATICS AND COMPUTING↗

Request for the establishment of quantum information foundries

Quantum information science still requires basic science research to achieve its full potential. However, scientists require access to fabricated device samples if we are to utilize the full toolset for solving the pressing issues in the field such as materials, device layout, or optimal error correction methods.Currently, access to samples is either prohibitively expensive, or requires close collaboration with one of the few groups in the world developing these systems. A dedicated quantum foundry could,in principle,provide affordable samples designed with current best practices to a host of scientists who otherwise do not have access. We detail several different foundry models which we believe will assist the community in developing the science for both the underlying processes, as well as the more advanced chip layout and circuit design. Opening access to the broader community has the potential to significantly lower the barrier to entry and vastly improve the ability for researchers in fields ranging from condensed matter to materials characterization to systems engineering to contribute to accelerating the advance of quantum information science and technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

PSEC5 Physical Verification

Ultra-Fast timing detectors, having a time resolution of 10pSec or less, are becoming increasingly important for many scientific disciplines, including High Energy Physics, Nuclear Physics, Medical Imaging and more. When developing ultra-fast detectors such as MCPs, LAPPDs, LGADs, SNSPDs, it is necessary to have access to a readout system that is low power, can support many channels and is cost effective. The PSEC5 chip was an application specific integrated circuit (ASIC) developed by the pioneering group of Prof. Henry Frisch at University of Chicago and micro electronic engineers at Fermi National Accelerator Laboratory. Three boards were designed, two to implement the readout system for an LAPPD and one to only characterize the PSEC1 chip. The main goal of the project shifted to setting up a testing environment to focus on the characterization of the chip. My student and I tested and characterized this ASIC using the third chip-on-board printed circuit board. Results show the successful fabrication and operation of some of the key building blocks and lead to the suggestions on modification for the second iteration of the chip.

Rico Aniles, H. D. [Unlisted]↗

Temperature Profile of the Solution Vessel of an Accelerator-Driven Subcritical Fissile Solution System

Dynamic System Simulation (DSS) models of fissile solution systems have been developed and verified against a variety of historical configurations. DSS techniques have been applied specifically to subcritical accelerator-driven systems using fissile solution fuels of uranium. Initial DSS models were developed in DESIRE, a specialized simulation scripting language. In order to tailor the DSS models to specifically meet needs of system designers they were converted to a Visual Studio implementation, and one of these subsequently to National Instrument’s LabVIEW for human factors engineering and operator training. Specific operational characteristics of subcritical accelerator-driven systems have been examined using a DSS model tailored to this particular class using fissile fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Particulate Emissions Control using Advanced Filter Systems: Final Report for Argonne National Laboratory, Corning Inc. and Hyundai Motor Company CRADA Project

This is a 3-way CRADA project working together with Corning, Inc. and Hyundai Motor Co. (HMC). The project is to understand particulate emissions from gasoline direct-injection engines (GDI) and their physico-chemical properties. In addition, this project focuses on providing fundamental information about filtration and regeneration mechanisms occurring in gasoline particulate filter (GPF) systems. For the work, Corning provides most advanced filter substrates for GPF applications and HMC provides three-way catalyst (TWC) coating services of these filter by way of a catalyst coating company. Then, Argonne National Laboratory characterizes fundamental behaviors of filtration and regeneration processes as well as evaluated TWC functionality for the coated filters. To examine aging impacts on TWC and GPF performance, the research team evaluates gaseous and particulate emissions as well as back-pressure increase with ash loading by using an engine-oil injection system to accelerate ash loading in TWC-coated GPFs.

42 ENGINEERING↗

Synthetic Biology: Engineering, Evolution and Design (SEED) Conference 2014

SEED2014 focused on advances in the science and technology emerging from the field of synthetic biology. We broadly define this as technologies that accelerate the process of genetic engineering. It highlighted new tool development, as well as the application of these tools to diverse problems in biotechnology, including therapeutics, industrial chemicals and fuels, natural products, and agriculture. Systems spanned from in vitro experiments and viruses, through diverse bacteria, to eukaryotes (yeast, mammalian cells, plants).

Voigt, Christopher↗

Multimodal Approaches for Leveraging Domain Knowledge with State-of-the-Art Machine Learning to Engineer Biocatalysts

This grant aimed to accelerate the development of specialized enzymes—biological catalysts essential for sustainable manufacturing and medicine—by integrating traditional laboratory evolution with cutting-edge artificial intelligence. To achieve this, we developed a suite of high-throughput sequencing tools and a centralized database to bridge the gap between a protein’s genetic "code" and its physical function. By training machine learning models on large datasets, we also demonstrated the ability to move beyond slow, trial-and-error testing to a "generative" approach, where AI can independently design new, versatile enzymes like tryptophan synthases. Ultimately, these findings demonstrate that combining laboratory data with computer-guided design enables the engineering of highly efficient biological tools with unprecedented speed and precision.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Fuel Properties on Gasoline Direct Injection Particulate Matter Emissions Over First 200 s of World-Harmonized Light-Duty Test Procedure Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software

Abstract The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine was investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in labview to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 s of the World-harmonized Light-duty Test Procedure (WLTP) driving cycle was tested using six different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 s of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.

Energy & Fuels↗

Characterization of Biomass-Based Fuels and Fuel Blends for Low-Emissions, Advanced Compression Ignition Engines (Final Report)

The goal of the Co-Optima program was to accelerate deployment of co-optimized fuels and engines that will reduce fuel consumption, and criterion pollutants and greenhouse gas (GHG) emissions for both spark and compression-ignited engines. In this project, combustion measurements from a constant pressure flow rig (CPFR) with optical access were used to assess fundamental combustion behavior of number of different candidate fuels and fuel blends. This chamber and its peripheral systems allowed stable control of ambient air pressure and temperature and fuel injection pressure and timing for hundreds of repeat injections allowing statistical interpretation of the results. The optical diagnostics enabled capturing of liquid length, vapor length, ignition timing, lift-off length as well as localized (temporal and spatially resolved) mixture refractive index, flame structure, and soot mass. The operating conditions allowed the study of combustion conditions promoting lean lifted flame combustion (LLFC), a mixing-controlled low-temperature combustion (LTC) strategy to reduce soot production in Advanced Compression Ignition (ACI) engines.

09 BIOMASS FUELS↗

Convergence QL: NSF/DOE Quantum Science Summer School: QS3 Final Report

Convergence QL: NSF/DOE Quantum Science Summer School (QS3) was a 2-week summer program held in 2017, 2018, 2019, and 2022. The program was aimed at graduate students and postdoctoral researchers working on a wide range of topics related to quantum science and quantum engineering. Expert leaders in this field served as lectures for the school. The school program included lectures, active learning, project activities, poster presentations, and industry panel discussions. The school covered four topics: Fundamentals and Applications of Quantum Computing (2017), Fundamentals and Applications of Quantum Materials (2018), Fundamentals and Applications of Quantum Devices (2019), and Modern Synthesis of Quantum Materials (2022). In terms of intellectual merit, the school brought together students from different areas of research related to quantum science to educate them on a broad range of related topics, providing a unique crucible for the development of educational content and learning opportunities in a cross-disciplinary fashion in the context of quantum science and quantum engineering. In terms of broader impacts, this may serve to create a workforce which would accelerate research in quantum science, quantum engineering, and the development of new quantum technologies beneficial to society. Additionally, this may add to the training of a cadre of scientists and engineers to serve as future leaders in this research field.

42 ENGINEERING↗

High-Throughput Functional Genomics for Energy Production

Functional genomics remains a foundational field for establishing genotype-phenotype relationships that enable strain engineering. High-throughput (HTP) methods accelerate the Design-Build-Test-Learn cycle that currently drives synthetic biology towards a forward engineering future. Trackable mutagenesis techniques including transposon insertion sequencing and CRISPR-Cas-mediated genome editing allow for rapid fitness profiling of a collection, or library, of mutants to discover beneficial mutations. Due to the relative speed of these experiments compared to adaptive evolution experiments, iterative rounds of mutagenesis can be implemented for next-generation metabolic engineering efforts to design complex production and tolerance phenotypes. Further, the expansion of these mutagenesis techniques to novel bacteria are opening up industrial microbes that show promise for establishing a bio-based economy.

59 BASIC BIOLOGICAL SCIENCES↗

Co-Optimization of Fuels & Engines: FY16 Year in Review

The U.S. Department of Energy's (DOE) Co-Optimization of Fuels & Engines (Co-Optima) initiative is accelerating the introduction of affordable, scalable, and sustainable fuels and high-efficiency, low-emission engines with a first-of-its-kind effort to simultaneously tackle fuel and engine research and development (R&D). This report summarizes accomplishments in the first year of the project. Co-Optima is conducting concurrent research to identify the fuel properties and engine design characteristics needed to maximize vehicle performance and affordability, while deeply cutting emissions. Nine national laboratories - the National Renewable Energy Laboratory and Argonne, Idaho, Lawrence Berkeley, Lawrence Livermore, Los Alamos, Oak Ridge, Pacific Northwest, and Sandia National Laboratories - are collaborating with industry and academia on this groundbreaking research.

09 BIOMASS FUELS↗

Considering Strain Variation and Non-Type Strains for Yeast Metabolic Engineering Applications

A variety of yeast species have been considered ideal hosts for metabolic engineering to produce value-added chemicals, including the model organism Saccharomyces cerevisiae, as well as non-conventional yeasts including Yarrowia lipolytica, Kluyveromyces marxianus, and Pichia pastoris. However, the metabolic capacity of these microbes is not simply dictated or implied by genus or species alone. Within the same species, yeast strains can display distinct variations in their phenotypes and metabolism, which affect the performance of introduced pathways and the production of interesting compounds. Moreover, it is unclear how this metabolic potential corresponds to function upon rewiring these organisms. These reports thus point out a new consideration for successful metabolic engineering, specifically: what are the best strains to utilize and how does one achieve effective metabolic engineering? Understanding such questions will accelerate the host selection and optimization process for generating yeast cell factories. In this review, we survey recent advances in studying yeast strain variations and utilizing non-type strains in pathway production and metabolic engineering applications. Additionally, we highlight the importance of employing portable methods for metabolic rewiring to best access this metabolic diversity. Finally, we conclude by highlighting the importance of considering strain diversity in metabolic engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗