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At least 307 records · Page 17

Highly efficient and simple SSPER and rrPCR approaches for the accurate site-directed mutagenesis of large and small plasmids

Advances are needed in the site-directed mutagenesis of large plasmids for protein structure-function studies, as current methods are often inefficient, complicated and time-consuming. Here two new methods are reported that overcome these difficulties, namely the single primer extension reaction (SSPER) strategy that reaches 100% efficiency and the reduce recycle PCR (rrPCR) method that is advantageous in generating single and pairwise combinations of mutations. Both methods are distinguished from current technologies by the addition of a step that easily removes the oligonucleotide primer(s) after the first reaction, thus allowing for the addition of a second reaction in chronological sequence to generate and isolate the appropriate DNA product with the site-directed mutation(s). High efficiency of the methods is demonstrated by generating single and paired combinations of the 11 site-directed mutations targeted on 5 different plasmid DNA templates ranging from 10 to 12 kb and 57–60% GC-content at a rate of 50–100%. Overall, the methods are demonstrated to be (i) highly accurate, allowing for screening of plasmids by DNA sequencing, (ii) streamlined to generate the mutations within a single day, (iii) cost-effective in requiring only two primers and two enzymes (DpnI and a proofreading DNA polymerase), (iv) straightforward in primer design, (v) applicable for both large and small plasmids, and (vi) easily implemented by entry level researchers.

59 BASIC BIOLOGICAL SCIENCES↗

Hybrid Absorption–Crystallization Strategies for the Direct Air Capture of CO2 Using Phase-Changing Guanidium Bases: Insights from in Operando X-ray Scattering and Infrared Spectroscopy Measurements

Efforts to limit rising concentrations of CO 2 have motivated the development of negative emission technologies. Direct air capture (DAC) of CO 2 is one of the negative emissions technologies that has been proposed for the direct removal of CO 2 from the atmosphere. Phase-changing bis(iminonoguanidine) (BIG) sorbents have been developed for the direct air capture of CO 2 . These phase changing sorbents, specifically glyoxal-bis(iminoguanidine) (GBIG), involve (1) CO 2 absorption with aqueous amino acid salts, such as K- or Na-glycinate to yield bicarbonate-rich solutions, (2) crystallization of the bicarbonate anions with a BIG solid, which regenerates the amino acid, and (3) solid-state CO 2 release from the carbonate crystals and BIG regeneration. Despite the promising potential of these materials, their structural evolution during the thermal regeneration of the BIG solids, chemical regeneration of the sodium or potassium glycinate solvents, and the crystallization behavior of CO 2 -loaded BIG bicarbonate remain to be evaluated and understood in detail. The aim of this study is to probe these knowledge gaps. In situ wide-angle X-ray Scattering (WAXS) results show that CO 2 and water molecules in GBIG bicarbonate are simultaneously released in a single step during the thermal regeneration of the sorbent at 97 – 134 °C. In situ ATR-FTIR measurements showed that sodium glycinate and GBIG bicarbonate are simultaneously generated when GBIG, glycine, and sodium bicarbonate are reacted. The crystallization of GBIG bicarbonate from GBIG and CO 2 -loaded monoethanolamine (MEA) occurs rapidly in the first 10 min of the reaction, as determined using in situ GI-SAXS measurements. Overall, the insights from these studies are essential for the scalable implementation of CO 2 capture technologies using these phase-changing sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Plug & play directed evolution of proteins with gradient-based discrete MCMC

Abstract A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sampling framework for evolving proteins in silico that supports mixing and matching a variety of unsupervised models, such as protein language models, and supervised models that predict protein function from sequence. By composing these models, we aim to improve our ability to evaluate unseen mutations and constrain search to regions of sequence space likely to contain functional proteins. Our framework achieves this without any model fine-tuning or re-training by constructing a product of experts distribution directly in discrete protein space. Instead of resorting to brute force search or random sampling, which is typical of classic directed evolution, we introduce a fast Markov chain Monte Carlo sampler that uses gradients to propose promising mutations. We conduct in silico directed evolution experiments on wide fitness landscapes and across a range of different pre-trained unsupervised models, including a 650 M parameter protein language model. Our results demonstrate an ability to efficiently discover variants with high evolutionary likelihood as well as estimated activity multiple mutations away from a wild type protein, suggesting our sampler provides a practical and effective new paradigm for machine-learning-based protein engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Relaxing Direct Ptychography Sampling Requirements via Parallax Imaging Insights

Direct ptychography enables the retrieval of information encoded in the phase of an electron wave passing through a thin sample by deconvolving the interference effects of a converged probe with known aberrations. Under the weak phase object approximation, this permits the optimal transfer of information using noniterative techniques. However, the achievable resolution of the technique is traditionally limited by the probe step size—setting stringent Nyquist sampling requirements. At the same time, parallax imaging has emerged as a dose-efficient phase technique which relaxes sampling requirements and enables scan-upsampling. Here, we formulate parallax imaging as a quadratic approximation to part of the direct ptychography kernel and use this insight to enable upsampling in direct ptychography. We validate our analytical results numerically using simulated and experimental reconstructions.

direct ptychography, parallax imaging, scan Nyquis↗

Hot-electron preheat and mitigation in polar-direct-drive experiments at the National Ignition Facility

Target preheat by superthermal electrons from laser–plasma instabilities is a major obstacle to achieving thermonuclear ignition via direct-drive inertial confinement fusion at the National Ignition Facility (NIF). Polar-direct-drive surrogate plastic implosion experiments were performed on the NIF to quantify preheat levels at ignition-relevant scale and develop mitigation strategies. Here, the experiments were used to infer the hot-electron temperature, energy fraction, divergence, and to directly measure the spatial hot-electron energy deposition profile inside the imploding shell. Silicon layers buried in the ablator are shown to mitigate the growth of laser–plasma instabilities and reduce preheat, providing a promising path forward for ignition designs at an on-target intensity of about 10 15 W/cm 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bound on hot-spot mix in high-velocity, high-adiabat direct-drive cryogenic implosions based on comparison of absolute x-ray and neutron yields

In laser-driven implosions for laboratory fusion, the comparison of hot-spot x-ray yield to neutron production can serve to infer hot-spot mix. For high-performance direct-drive implosions, this ratio depends sensitively on the degree of equilibration between the ion and electron fluids. A scaling for x-ray yield as a function of neutron yield and characteristic ion and electron hot-spot temperatures is developed on the basis of simulations with varying degrees of equilibration. We apply this model to hot-spot x-ray measurements of direct-drive cryogenic implosions typical of the direct-drive designs with best ignition metrics. Furthermore, the comparison of the measured x-ray and neutron yields indicates that hot-spot mix, if present, is below a sensitivity estimated as ~ 2% by-atom mix of ablator plastic into the hot spot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficiency and Physical Limitations of Adiabatic Direct Energy Conversion in Axisymmetric Fields

We describe and analyze a new class of direct energy conversion schemes based on the adiabatic magnetic drift of charged particles in axisymmetric magnetic fields. The efficiency of conversion as well as the geometrical and dynamical limitations of the recoverable power are calculated. The geometries of these axisymmetric field configurations are suited for direct energy conversion in radiating advanced aneutronic reactors and in advanced divertors of deuterium-tritium tokamak reactors. The E × B configurations considered here do not suffer from the classical drawbacks and limitations of thermionic and magnetohydrodynamic high-temperature direct energy conversion devices.

30 DIRECT ENERGY CONVERSION↗

Analysis and Overview of Hybrid Wired and Wireless Bi-Directional EV Charger Systems

Here, this paper analyzes and overviews hybrid wired and wireless bi-directional Electric Vehicle (EV) charging systems with a primary focus on resonant compensation methods that enable a unified power conversion architecture. Four compensation configurations based on series–series and LCC–LCC resonant networks are systematically evaluated for both wired transformer-based and wireless coupler-based operation. The analysis examines how coupling conditions, resonant component selection, and auxiliary compensation tuning influence voltage gain characteristics, resonant tank current magnitude and phase, and operating frequency requirements. Normalized frequency-domain results are presented to directly compare reactive current behavior and voltage regulation capability under wired and wireless operating conditions. A 60 kW bi-directional charger case study is used to demonstrate the feasibility of retaining a common hardware platform while accommodating distinct coupling scenarios through compensation tuning rather than structural modification. The presented results provide design-oriented insights into resonant network selection and compensation strategies for scalable and flexible hybrid EV charging systems.

Hybrid↗

Comparing Regional Energy Consumption for Direct Drone and Truck Deliveries

Drone delivery, once thought of as fictitious, is becoming a reality with the efforts of both forward-looking enterprises and supportive government policies. This emerging mode of e-commerce delivery raises many concerns. One important concern is the energy efficiency of direct delivery drones compared with conventional delivery trucks at a regional systems level. Here, in this study, we develop and apply methods to quantify the regional energy impacts of drone delivery, then we assess these impacts and compare them with the impacts of truck delivery. To study this problem, we develop an optimization model that determines an optimal set of fulfillment centers (FCs) with variable service capacities that allow drones to make direct e-commerce deliveries. We adopt two drone delivery energy estimation models from the literature and use them as inputs to demonstrate the potential range of energy needs. We also develop another optimization model to account for the energy consumption of diesel trucks (DTs) and battery electric vehicles (BEVs). We test the models using validated simulation data for the Chicago metropolitan area in the U.S. to quantify the energy implications of these three delivery modes. For drone delivery, we further extend our analyses by considering the impact of wind speed and flight patterns. Our results show that direct delivery drones require 15.8% more energy than BEVs on an average windy day, and they need 15% more energy than DTs on a very windy day. We provide essential parameter values for reproducibility and list relevant open problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimization of spray breakup model parameters for predicting fuel spray and film characteristics in gasoline direct injection engines

This study investigated the behavior of gasoline direct injection (GDI) sprays using computational fluid dynamics (CFD). The authors developed an approach to identify optimal spray breakup model parameters by evaluating an error function across numerous simulations, with the goal of minimizing discrepancies from experimental data. Using the optimal setup, the simulated spray matched well with projected liquid volume distributions, liquid penetration, and spray width measured in a constant-pressure continuous-flow chamber. To further validate the approach, the same setup was tested across various fuels, injectors, and operating conditions. Subsequently, the optimal setup, along with a recently developed spray-wall interaction model, were applied to a direct-injection spark-ignited engine under late-injection conditions to predict and evaluate fuel film formation and evolution at varying engine coolant temperatures. Here, with the centrally mounted injector directing the spray toward the piston, simulations indicated that the spray tends to impinge on the piston surface. The proposed simulation framework also accurately captured the aggregate film area on the piston surface, aligning with previously published experimental results. Moreover, simulations showed that increasing the coolant temperature from cold start conditions (333 K) to warm conditions (363 K) reduced the fuel mass deposited on the piston by roughly 50%. Furthermore, for the spray-guided engine configuration studied in this work, the CFD model predicted minimal film deposition on the spark plug electrodes regardless of the coolant temperatures due to a relatively weak in-cylinder flow during the compression phase.

Computational fluid dynamics (CFD)↗

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug–drug interactions

Background. During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels. Methods. We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC. Results. This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences. Discussion and conclusion. Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more “fit for purpose” NLP methods could be developed and used to facilitate the drug development process.

59 BASIC BIOLOGICAL SCIENCES↗

Multicriteria screening evaluation of geothermal resources on mine lands for direct use heating

Abstract Direct use of geothermal energy is the oldest and most versatile form of utilizing geothermal energy. In the last decade, this utilization has significantly increased, especially with the installation of geothermal (ground-source) heat pumps. Many current and inactive mine land sites across the U.S. could be redeveloped with clean energy technologies such as direct use geothermal, which would revitalize former mining communities, help with reducing greenhouse gas emissions, and accelerate the transition to a clean energy economy. We present a multicriteria screening framework to evaluate various aspects of direct-use geothermal projects on mine lands. The criteria are divided into three categories: (1) technical potential, (2) demand and benefits, and (3) regulatory and permitting. We demonstrate the framework using publicly available data on a national scale (continental U.S.). Then, using an example of abandoned coal mines in Illinois and focusing on resource potential, we illustrate how this evaluation can be applied at the state or more local scales when a region’s characteristics drive spatial variability estimates. The strength of this approach is the ability to combine seemingly disparate parameters and inputs from numerous sources. The framework is very flexible—additional criteria can be easily incorporated and weights modified if input data support them. Vice versa, the framework can also help identify additional data needed for evaluating those criteria. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

15 GEOTHERMAL ENERGY↗

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

15 GEOTHERMAL ENERGY↗

Membrane Adsorbents Comprising Self-Assembled Inorganic Nanocages (SINCs) for Super-fast Direct Air Capture Enabled by Passive Cooling

The objectives of the proposed project were to develop highly porous membrane adsorbents comprising CO 2 -philic polymers and self-assembled inorganic nanocages (SINCs) for rapid temperature swing adsorption using electricity-free solar heating and radiative cooling, enabling an economically viable approach for direct air capture (DAC). Our core technical activities combine three key innovations. (1) Highly porous flat-sheet membrane adsorbents contain CO 2 -philic amines that can be easily produced using a phase inversion method. (2) CO 2 -philic SINCs can be easily dispersed in the polymers with great stability (compared with the metal-organic frameworks or MOFs). (3) The adsorption and desorption are integrated with solar heating and radiative cooling for rapid continuous operation, in contrast to traditional long-cycle separate operation. The membrane adsorbents containing amines, polymers, and SINCs were produced using a one-step industrial process. The porous membranes coupled with porous SINCs offer low resistance for gas flow and fast CO 2 sorption/desorption cycles, while the incorporation of the additional amine groups provides high CO 2 sorption capacity. The key achievements are summarized below. (1) Membrane adsorbents with high PEI loading (>40%), high porosity of >80%, and low gasflow resistance were prepared in one step using commercially available, low-cost materials. (2) Membrane adsorbents based on Solupor and PEI show CO 2 sorption capacity of >1.5 mmol/g using air containing 400 ppm at a relative humidity of 15%. (3) Effect of the adsorbent compositions (such as PEI type, PEI content, SINC content, porosity) on the CO 2 sorption was systematically investigated. (4) Effect of the processing conditions (such as CO 2 content, temperature, and relative humidity) on the CO 2 sorption was systematically investigated; (5) The stability of the membrane adsorption against many cycles of sorption and desorption was studied. The higher molecular weight of PEI (PEI25k) shows better stability than PEI800. (6) Advanced materials with radiative cooling were developed, which can decrease the temperature by 5-7 °C compared to the ambient temperature. (7) Preliminary techno-economic analysis shows that our process may achieve a capture cost of $1,343/tonne CO 2 with a total OPEX cost of $1,112/tonne CO 2 . The adsorbent replacement cost accounted for 52% of the total OPEX cost. Membrane adsorbents with lower costs and longer operation life can significantly decrease the cost. The proposed project directly addresses the requirement of DE-FOA-0002188, i.e., novel materials with CO 2 adsorption capacity for direct air capture with integrated solar heating and radiative cooling to reduce the cost of the DAC. Our future work will focus on the development of low-cost adsorbents that can be stable at the sorption and desorption conditions for long term.

14 SOLAR ENERGY↗

Passivated Contacts for Direct Wafer Product (Final Technical Report)

This TCF project developed a thin-oxide (SiO 2 )/polycrystalline silicon (poly-Si) passivated contact solar cell on CubicPV's (formally 1366 Technologies, Inc.) Direct Wafer® Product (DWP) kerfless wafers. The project used two NREL-developed technologies described in U.S. Patent No. 9,911,873, Hydrogenation of Passivated Contacts and U.S. Patent Application Serial No. 15/890,172, Doped Passivated Contacts . The project was motivated by a potential higher efficiency cell (compared to a PERC cell) using passivated contacts on the ultra-low cost kerfless wafers grown using the Direct Wafer process. The hope was to accelerate market adoption of the cell and wafer by delivering the lowest LCOE in the PV industry. The project tested both n-type and p-type SiO 2 /poly-Si passivated contacts grown by thermal oxidation and plasma enhanced chemical vapor deposition (PECVD) of the poly-Si layer on DWP with varying wafer resistivities. Both deposition techniques are industry standards and thus economically viable methods for commercializing the contacts. The results indicated that both n-type and p-type poly-Si passivated contacts can be formed on polycrystalline DWP wafers, but implied open-circuit voltages (i Voc ) were limited to below 0.65 mV (compared with ~ 730 mV on n-Cz wafers). Diffusion of H to the Si/SiO 2 /poly-Si interface was key to obtaining high i Voc values. In this study, H was diffused from a high-temperature SiN x layer deposited over the poly-Si layer during a high-temperature firing step, similar to one used for screen printed metals. The study concluded that poly-Si passivated contacts on DWP wafers passivated the surface of the wafers as well as PERC passivated surfaces, which use a less expensive dielectric layer stack. The project showed that Direct Wafer Product wafers grown by CubicPV could produce high i Voc values (~0.647 mV), which could produce a cell over 20% efficient with proper processing and metallization. These cells, though not economically viable in 2024 as a stand-alone cell, could be integrated with a wide-bandgap top solar cell to form a two-junction tandem cell that could be viable under certain circumstances. This is because the bottom cell of a 30%, two-terminal tandem only needs to be a 20% cell under one-sun conditions. Thus, the DWP could be an ideal low-cost wafer for tandems. The project also revealed that a TOPCon type cell could be formed on a p-type DWP wafer using a P-diffused emitter and a p-type poly-Si contact. In fact, the p-type version of the poly-Si contact out-performed the n-type version for a variety of wafer resistivities, from highly doped to lowly doped. This curiosity requires more work to understand because on Cz wafers, the n-type poly-Si contact is of much higher quality than the p-type version.

14 SOLAR ENERGY↗

Nuclear Direct Air Capture with Carbon Storage (NuDACCS) (Final Technical Report)

This final report, which is for DOE Award Number DE-FE0032160 (Direct Air Capture Combined with dedicated Long-Term Carbon Storage, Coupled to Existing Low-Carbon Energy), covers the Nuclear Direct Air Capture with Carbon Storage (NuDACCS) project period of performance from 03/31/2022 to 12/27/2024. Battelle Memorial Institute (Battelle) partnered with Aircapture LLC (Aircapture), Southern Company (Southern), Carbonvert, the University of Alabama, and Sargent & Lundy (S&L) to develop a front end engineering design (FEED) study for a direct air capture (DAC) system co-located with Southern Company's Joseph M. Farley Nuclear Plant (Plant Farley) in Columbia, Alabama. The DAC system was designed to capture at least 5,000 net tonnes of carbon dioxide (CO2) per year from ambient air in a form suitable for long duration carbon storage (e.g., geologic storage). To complement and support the FEED study, additional analyses were completed, including a Technology Maturation Plan (TMP); Workforce Readiness Plan; Project Cost Estimate; Business Case Analysis (BCA); Life Cycle Analysis (LCA); Environmental Health and Safety (EH&S) Assessment; and Environmental Justice (EJ) Analysis and Economic Revitalization and Job Creation Outcomes Analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Direct reactions with the AT-TPC

Direct reactions are crucial tools for accessing properties of the atomic nucleus. Fundamental and exotic phenomena such as collective modes, pairing, weakbinding effects and evolution of single-particles energies can be investigated in peripheral collisions between a heavy nucleus and a light target. The necessity of using inverse kinematics to reveal how these structural properties change with isospin imbalance renders direct reactions a challenging technique when using the missing mass method. In this scenario, Active Target Time Projection Chambers (AT-TPC) have demonstrated an outstanding performance in enabling these types of reactions even under conditions of very low beam intensities. The AT-TPC of the Facility for Rare Isotope Beams (FRIB) is a next generation multipurpose Active Target. When operated inside a solenoidal magnet, direct reactions benefit from the measurement of the magnetic rigidity that enables particle identification and the determination of the excitation energy with high resolution without the need of auxiliary detectors. Additionally, the AT-TPC can be coupled to a magnetic spectrometer improving even further its spectroscopic investigation capability. In this contribution, we discuss inelastic scattering and transfer reaction data obtained via the AT-TPC and compare them to theory. In particular, we present the results for the 14 C(p,p′) and 12 Be (p,d) 11 Be reactions. For 14 C, we compare the experimental excitation energy of the first 1 – excited state with coupled-cluster calculationsbased on nuclear interactions from chiral effective field theory and with available shell-model predictions. For 12 Be, we determine the theoretical spectroscopic factors of the 12 Be (p,d) 11 Be transfer reaction in the shell modeland compare them to the experimental excitation spectrum from a qualitative standpoint.

active target↗