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At least 1,261 records · Page 70

Reaction mechanism for atmospheric pressure plasma treatment of cysteine in solution

Mechanisms for the cold atmospheric plasma (CAP) treatment of cells in solution are needed for more optimum design of plasma devices for wound healing, cancer treatment, and bacterial inactivation. However, the complexity of organic molecules on cell membranes makes understanding mechanisms that result in modifications (i.e. oxidation) of such compounds difficult. As a surrogate to these systems, a reaction mechanism for the oxidation of cysteine in CAP activated water was developed and implemented in a 0-dimensional (plug-flow) global plasma chemistry model with the capability of addressing plasma-liquid interactions. Reaction rate coefficients for organic reactions in water were estimated based on available data in the literature or by analogy to gas-phase reactions. The mechanism was validated by comparison to experimental mass-spectrometry data for COST-jets sustained in He/O 2 , He/H 2 O and He/N 2 /O 2 mixtures treating cysteine in water. Results from the model were used to determine the consequences of changing COST-jet operating parameters, such as distance from the substrate and inlet gas composition, on cysteine oxidation product formation. Results indicate that operating parameters can be adjusted to select for desired cysteine oxidation products, including nitrosylated products.

60 APPLIED LIFE SCIENCES↗

Atmospheric pressure plasma treatment of skin: penetration into hair follicles

Sterilization of skin prior to surgery is challenged by the reservoir of bacteria that resides in hair follicles. Atmospheric pressure plasma jets (APPJs) have been proposed as a method to treat and deactivate these bacteria as atmospheric plasmas are able to penetrate into structures and crevices with dimensions similar to those found in hair follicles. In this paper, we discuss results from a computational investigation of an APPJ sustained in helium flowing into ambient air, and incident onto a layered dielectric similar to human skin in which there are idealized hair follicles. We found that, depending on the location of the follicle, the bulk ionization wave (IW) incident onto the skin, or the surface IW on the skin, are able to launch IWs into the follicle. The uniformity of treatment of the follicle depends on the location of the first entry of the plasma into the follicle on the top of the skin. Typically, only one side of the follicle is treated on for a given plasma pulse, with uniform treatment resulting from rastering the plasma jet across the follicle over many pulses. Plasma treatment of the follicle is sensitive to the angle of the follicle with respect to the skin, width of the follicle pocket, conductivity of the dermis and thickness of the underlying subcutaneous fat layer, the latter due to the change in capacitance of the tissue.

60 APPLIED LIFE SCIENCES↗

Computational exploration of biomedical HfNbTaTiZr and Hf 0.5 Nb 0.5 Ta 0.5 Ti 1.5 Zr refractory high-entropy alloys

Refractory high entropy alloys (RHEAs) have been proven to be a potential candidate in the biomedical field due to their balanced mechanical properties and biocompatible composition. Recent experimental findings show that RHEAs like HfNbTaTiZr and Hf 0.5 Nb 0.5 Ta 0.5 Ti 1.5 Zr have good mechanical properties such as high polarization and wear resistance than others which establish them as potential materials for biomedical application. In this work, we performed first-principles density functional theory calculations on the mechanical and thermal properties of HfNbTaTiZr and Hf 0.5 Nb 0.5 Ta 0.5 Ti 1.5 Zr. The predicted lattice constant, density, Young's modulus, and Vickers hardness are consistent with the available experimental report, which verifies the accuracy of the applied model. The thermal coefficient of linear expansion of both RHEAs has been investigated by utilizing the Debye theory. The present methods could be applied to study other future RHEAs on exploration of their physical properties.

36 MATERIALS SCIENCE↗

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗

3D small-gain formula allowing strong focusing and harmonic lasing for a ring-based x-ray free electron laser oscillator

We present a detailed derivation of a formula for the small-gain calculation for an x-ray free electron laser oscillator (XFELO) based on a medium-energy (3–4 GeV) storage ring. We found harmonic lasing and strong focusing are essential for this beam energy range. Taking the small-signal low-gain formula developed by Kim and his colleagues, we modified it in such a way that the gain can be calculated without the “no focusing approximation,” and a strong focusing can be applied, as well as harmonic lasing. In this formula, the gain is represented as a product of two factors with one of them depending only on the harmonic number, undulator period, and gap. Using this factor, we show that it is favorable to use harmonic lasing to achieve hard x-ray FEL working in the small-signal low-gain regime with the medium-energy electron beam. Our formula also allows FEL optimization by varying the vertical gradient of the undulator, the vertical dispersion, and the horizontal and vertical focusing, independently. As an example, we applied this formula to study the feasibility of an XFELO option for the National Synchrotron Light Source II (NSLS-II) upgrade. Since a quite high peak current is required for the FEL, collective effects of beam dynamics in medium-energy synchrotrons significantly affect the electron beam parameters. We carried out a multiparameter optimization taking collective effects into account. Note, even though our example is for a ring-based XFELO at 3 to 4 GeV, the formula and, in particular, the approach developed here may be applied to other types of FELs. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Many-Body Quantum Catalysts for Transforming Between Phases of Matter

A catalyst is a substance that enables otherwise impossible transformations between states of a system, without being consumed in the process. In this work, we apply the notion of catalysts to many-body quantum physics. In particular, we construct catalysts that enable transformations between different symmetry-protected topological (SPT) phases of matter using symmetric finite-depth quantum circuits. We discover a wide variety of catalysts, including GHZ-like states that spontaneously break the symmetry, gapless states with critical correlations, topological orders with symmetry fractionalization, and spin-glass states. These catalysts are all united under a single framework that has close connections to the theory of quantum anomalies, and we use this connection to put strong constraints on possible pure- and mixed-state catalysts. We also show how the catalyst approach leads to new insights into the structure of certain phases of matter, and to new methods to efficiently prepare SPT phases with long-range interactions or projective measurements.

quantum many-body systems↗

The ITensor Software Library for Tensor Network Calculations

ITensor is a system for programming tensor network calculations with an interface modeled on tensor diagrams, allowing users to focus on the connectivity of a tensor network without manually bookkeeping tensor indices. The ITensor interface rules out common programming errors and enables rapid prototyping of algorithms. After discussing the philosophy behind the ITensor approach, we show examples of each part of the interface including Index objects, the ITensor product operator, tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, quantum number conserving block sparse tensors, and the NDTensors library. We also review publications that have used ITensor for quantum many-body physics and for other areas where tensor networks are increasingly applied. To conclude we discuss promising features and optimizations to be added in the future.

Fishman, Matthew↗

Codebase release 0.3 for ITensor

ITensor is a system for programming tensor network calculations with an interface modeled on tensor diagrams, allowing users to focus on the connectivity of a tensor network without manually bookkeeping tensor indices. The ITensor interface rules out common programming errors and enables rapid prototyping of algorithms. After discussing the philosophy behind the ITensor approach, we show examples of each part of the interface including Index objects, the ITensor product operator, tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, quantum number conserving block sparse tensors, and the NDTensors library. We also review publications that have used ITensor for quantum many-body physics and for other areas where tensor networks are increasingly applied. To conclude we discuss promising features and optimizations to be added in the future.

Fishman, Matthew↗

Favipiravir Flow Synthesis

Researchers at Los Alamos have invented a novel flow/batch chemistry synthetic process to produce the small molecule anti-viral favipiravir more cheaply and rapidly to enable on-demand production for pandemic response. Current methods for synthesizing favipiravir are constrained by long reaction times and low yields. If ongoing clinical trials for favipiravir demonstrate its effectiveness as a COVID-19 antiviral, and as a broad spectrum anti-viral for treating future viral outbreaks, this synthesis would help alleviate potential drug shortages and supply chain issues for the manufacturing and availability of this small molecule anti-viral. This U.S.-based synthesis route would be capable of scale-up for making large (kilogram) amounts of favipiravir as needed to assist with clinical trial needs and demand for patient treatment, and can also produce isotopically labeled favipiravir. We are seeking a CRADA partner to finalize method development who has interest in licensing the method and employing it for domestic production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing Post-Combustion CO 2 Capture through Increased Mass Transfer and Lower Degradation

The over-arching goal of the proposed project is to develop three techniques to enable aqueous post-combustion CO 2 capture technologies to meet the DOE performance and cost targets of 90% CO 2 capture, 95% purity, at a cost of less than $30/tonne CO 2 captured. This will be accomplished by the development of materials and processes to increase mass transfer in the absorber and reduce the environmental impacts. While constantly working to reduce the cost of CO 2 capture via solvent development and process & heat integration, increasing CO 2 mass transfer through development of custom dynamic packing materials and tuning solvent physical properties may offer a route to increased solvent capacity, lower energy consumption and reduced aerosol formation. The environmental concerns that have been identified in amine-based CO 2 capture systems, nitrosamines specifically, are another critical element that will be addressed in this project. The specific objectives of the project were to: 1) conduct detailed studies to understand how solvent physical properties and aerosol formation are impacted by additives; 2) quantify the CO 2 mass transfer improvement from the dynamic polarity packing in the absorber and the additive-modified solvent using the existing UK bench-scale CO 2 capture unit; 3) quantify the energy consumption savings associated with enhanced mass transfer; 4) quantify the benefits of the UK’s electrochemical cell to decompose nitrosamines; and 5) collect the necessary information/data to conduct a high-level TEA assessment of the proposed technologies. The project involved the fabrication and installation of customized dynamic polarity packing and an investigation into the understanding of the impact of chemical additives on solvent properties to increase CO 2 mass transfer in the absorber column, and lastly the design of an electrochemical cell to decompose nitrosamines in a water wash. After both systems were fabricated, they were tested at UK facilities, including on the bench-scale CO 2 capture unit under parametric and long-term operation.

20 FOSSIL-FUELED POWER PLANTS↗

Functional Biomimetic Polymers with Antimicrobial Activity

At PNNL, we have developed a completely new class of synthetic biomimetic sequence-defined polymers based on triazine chemistry, which we call TZPs. PNNL's new polymers offer the opportunity to achieve similar functions to natural macromolecules; specifically we designed and synthesized a diversity of test molecules for antimicrobial activity. Antimicrobial activity against a variety of wild type and drug resistant pathogens was found.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Performance Advantaged Biobased Chemicals Utilizing Bioprivileged Molecules

Two technology areas were advanced; a) novel molecules with improved performance in the end use application of organic corrosion inhibitors and flame retardant nylon polymers and b) development of a systematic process for identifying biomass-derived molecules with improved performance in end use applications. In total 17 novel organic corrosion inhibitors were identified that had significantly better performance than the commercial reference organic corrosion inhibitor and 7 novel nylons were synthesized with improved flame retardant properties relative to standard nylon-6,6. While an end-to-end systematic process for identifying biomass-derived molecules with improved end use performance was not completed, important progress was made computational tools for mining chemical structures from the literature and databases as well as establishing reaction network generation algorithms to aid in the discovery of novel molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating engineered microbe optimization through machine learning and multi-omics datasets

This project demonstrated the use of a combination of multi-omics data with deep learning and a high-throughput Design- Build-Test-Learn (DBTL) cycle to improve the production of malonic acid, a versatile product with a large market. The project leveraged the unique capabilities of both Lygos and the Agile BioFoundry (ABF): Lygos provided its expertise efficiently designing, building, and cultivating P. kudriavzevii strains; LBNL, PNNL, and NTESS provided multi-omics analysis in the Test phase, LBNL provided machine learning techniques in the Learn phase to analyze the -omics datasets and make recommendations so as to increase malonic acid production in the next DBTL cycle. This project is the first to use large amounts of multi-omics time-series data to feed deep learning models, creating around 80,000 data points in a single DBTL cycle. This project has 1) demonstrated the utility of combining deep learning and multi-omics data sets by improving the production of malonic acid two fold, 2) created a large time-series datasets to be released publicly for external development of new machine learning algorithms, and 3) shown that supply chain problems, strain building bottlenecks, and adaptation times for new ML approaches are key obstacles for fast DBTL cycle times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon optimized production of 3-hydroxypropionic acid in the Agile BioFoundry organism Rhodosporidium toruloides

The modern global economy relies heavily on carbon-based products that are derived from petroleum, which presents sustainability, resource management, and greenhouse gas exacerbated climate change challenges. Due to these challenges, there is the need for a global industrial transition towards green and sustainable production. Microbial production of valuable chemicals from renewable biomass represents one promising route. However, high-volume low-value products such as commodity chemicals are still difficult to make profitable. One fundamental bottleneck is a waste of more than 1/3 of the feedstock carbon as CO 2 in the fermentation process. Here the project focuses on fundamentally reconfiguring the metabolism to reduce CO 2 loss in central metabolic pathways thereby also improving bioproduct yields. Here we present technologies to prevent CO 2 loss and balance reducing equivalents within the cell to enable complete conversion of glucose from renewable feedstocks into bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗