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At least 1,261 records · Page 70

Work Function Modification via Combined Charge-Based Through-Space Interaction and Surface Interaction

Work function modification of electrodes is an important factor to achieve high performance in organic electronics. However, a clear explanation of the origin of work function modification has remained elusive. Here, it is investigated how the work function of electrodes is affected by the charge-based through-space interaction with the well-known surface interaction. The studies reveal that the formation of a surface dipole leads to a work function shift, even when the work function modifying layer and substrate are separated. A work function shift is also demonstrated by electrophoretic deposition of ionic polyelectrolytes while the same polyelectrolytes do not cause any work function shift when they are spin cast. More noteworthy is that a neutral (nonionic) polymer which has no specific surface-interacting functional groups can induce work function shift of its substrate by a charge-based through-space interaction when deposited by electrospraying. These results provide a more comprehensive understanding of work function modification and motivate the design and selection of a wide range of effective work function modifying layers for organic electronics.

36 MATERIALS SCIENCE↗

MaTableGPT: GPT‐Based Table Data Extractor from Materials Science Literature

Abstract Efficiently extracting data from tables in the scientific literature is pivotal for building large‐scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule‐based extractions are an ineffective approach. To overcome this challenge, the study presents MaTableGPT, which is a GPT‐based table data extractor from the materials science literature. MaTableGPT features key strategies of table data representation and table splitting for better GPT comprehension and filtering hallucinated information through follow‐up questions. When applied to a vast volume of water splitting catalysis literature, MaTableGPT achieves an extraction accuracy (total F1 score) of up to 96.8%. Through comprehensive evaluations of the GPT usage cost, labeling cost, and extraction accuracy for the learning methods of zero‐shot, few‐shot, and fine‐tuning, the study presents a Pareto‐front mapping where the few‐shot learning method is found to be the most balanced solution owing to both its high extraction accuracy (total F1 score >95%) and low cost (GPT usage cost of 5.97 US dollars and labeling cost of 10 I/O paired examples). The statistical analyses conducted on the database generated by MaTableGPT revealed valuable insights into the distribution of the overpotential and elemental utilization across the reported catalysts in the water splitting literature.

Yi, Gyeong Hoon [Computational Science Research Ce↗

Interphases in Sodium-Ion Batteries

Sodium-ion batteries (SIBs) as economical high energy alternatives to lithium-ion batteries (LIBs) have received significant attention for large-scale energy storage in the last few years. While the efforts of developing SIBs have benefited from the knowledge learned in LIBs, thanks to the apparent proximity between Na-ion and Li-ion, the unique physical and chemical properties of Na-ion also distinctly differ itself from Li-ion. It is expected SIBs have drastically different electrode material structure, solvation-de-solvation behavior, electrode-electrolyte interphase stability, ion transfer property, and hence electrochemical performance of batteries. In this review, we comprehensively summarize the current understanding of the anode solid-electrolyte-interphase (SEI) and cathode cathode-electrolyte-interphase (CEI) in SIBs, with an emphasis on how the tuning of the stability and ion transfer properties of interphases fundamentally determines the reversibility and efficiency of electrochemical reactions. Through these carefully screened references, we intend to reveal the intrinsic correlation between the properties/functionalities of the interphases and the electrochemical performances of batteries.

Song, Junhua↗

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗

Battery‐Grade Lithium Materials: Virgin Production and Recycling, a Techno‐Economic Comparison

Lithium has been identified as an essential mineral to the economic and national security of the United States. It is vital for rechargeable batteries that surround us daily from the personal electronics to large-scale energy storage. With a comprehensive techno-economic analysis, the cost of battery-grade lithium compounds production, i.e., lithium carbonate (LC) is evaluated and lithium hydroxide monohydrate (LHM), from both virgin (spodumene ore and brine) and recycled feedstocks (spent lithium-ion batteries). The goal of this study is to inform about the economics of lithium compounds production with comprehensive insights into differences in manufacturing routes and pave a pathway to explore more innovative, domestic manufacturing processes in future for their cost competitiveness and environmental impact. The study includes details on mining and extraction operations as well as unit level operation in the refining process. Moreover, process level information has been collected for pyrometallurgical and hydrometallurgical battery recycling routes. This analysis shows that brine and direct lithium extraction are the cheapest pathways to produce LC or LHM (between $\$3.39$ and 6.20 kg −1 ). The cost of production in the ore and recycling routes can range between $\$4.17$ and $\$53.41$ kg −1 and is highly depending on capital equipment investment, plant location, and the price of spodumene concentrate SC6.0.

battery recycling↗

A review of sugarcane bagasse for second-generation bioethanol and biopower production: Biorefining Sugar Bagasse

Sugarcane bagasse is a large-volume agriculture residue that is generated on a ~540 million metric tons per year basis globally with the top-three producing countries in Latin America being Brazil (~181 million metric ton yr -1 ), Mexico (15 million metric ton yr -1 ), and Colombia (7 million metric ton yr -1 ), respectively. Furthermore, given sustainability concerns and the need to maximize the utilization of bioresources, the use of sugarcane bagasse is receiving significant attention in biorefining applications, as it is a promising resource for the conversion to biofuels and biopower. Our review provides a comprehensive review of bagasse and its chemical constituents and on-going research into its utilization as a feedstock for cellulosic ethanol and electricity generation.

09 BIOMASS FUELS↗

Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.

59 BASIC BIOLOGICAL SCIENCES↗

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗

Quantitative Microstructural Characterization of Plutonium Oxalate Auto-Degradation and Evidence for PuO2 Nanocrystal Formation

It has been known since the 1950s that plutonium oxalate powders change color and lose mass over time when stored at room temperature in air. Despite several studies monitoring these changes, there are still discrepancies in the literature regarding the speciation of intermediate and final products that result from this decomposition. Presented here for the first time is a comprehensive series of time-resolved powder X-ray diffraction experiments coupled with solid-state optical spectroscopy and electron microscopy of aged plutonium (III) and (IV) oxalate powders. These data provide fresh insight into the chemical and structural changes that occur in these solids over time at room temperature and represent new evidence suggesting both plutonium (III) and plutonium (IV) oxalates decompose to form nanocrystalline plutonium oxide in the solid state.

Corbey, Jordan F.↗

Design Basis Model for Hosting Small Modular Reactors

An aggressive transition from fossil fuels to other types of energy implies the need to construct a large number of nuclear power plants in the near future. However, the real and perceived risks of nuclear energy remain a significant impediment to this transition. This paper describes a comprehensive work process that combines the rigor of model-based systems engineering (MBSE) with 1) the Idaho National Laboratory's (INL) decades of experience with small reactors and with 2) modern project delivery processes. The objective is to reduce the risk of building new facilities or converting existing facilities to nuclear power generation.

42 ENGINEERING↗

Enhancing Early Systems R&D Capabilities with Systems —Theoretic Process Analysis

Systems engineering today faces a wide array of challenges, ranging from new operational environments to disruptive technological — necessitating approaches to improve research and development (R&D) efforts. Yet, emphasizing the Aristotelian argument that the “whole is greater than the sum of its parts” seems to offer a conceptual foundation creating new R&D solutions. Invoking systems theoretic concepts of emergence and hierarchy and analytic characteristics of traceability, rigor, and comprehensiveness is potentially beneficial for guiding R&D strategy and development to bridge the gap between theoretical problem spaces and engineering-based solutions. In response, this article describes systems–theoretic process analysis (STPA) as an example of one such approach to aid in early-systems R&D discussions. STPA—a ‘top-down’ process that abstracts real complex system operations into hierarchical control structures, functional control loops, and control actions—uses control loop logic to analyze how control actions (designed for desired system behaviors) may become violated and drive the complex system toward states of higher risk. By analyzing how needed controls are not provided (or out of sequence or stopped too soon) and unneeded controls are provided (or engaged too long), STPA can help early-system R&D discussions by exploring how requirements and desired actions interact to either mitigate or potentially increase states of risk that can lead to unacceptable losses. This article will demonstrate STPA's benefit for early-system R&D strategy and development discussion by describing such diverse use cases as cyber security, nuclear fuel transportation, and US electric grid performance. Together, the traceability, rigor, and comprehensiveness of STPA serve as useful tools for improving R&D strategy and development discussions. In conclusion, leveraging STPA as well as related systems engineering techniques can be helpful in early R&D planning and strategy development to better triangulate deeper theoretical meaning or evaluate empirical results to better inform systems engineering solutions.

42 ENGINEERING↗

Oxidation and pyrolysis of methyl propyl ether

The ignition, oxidation, and pyrolysis chemistry of methyl propyl ether (MPE) was probed experimentally at several different conditions, and a comprehensive chemical kinetic model was constructed to help understand the observations, with many of the key parameters computed using quantum chemistry and transition state theory. Experiments were carried out in a shock tube measuring time variation of CO concentrations, in a flow tube measuring product concentrations, and in a rapid compression machine (RCM) measuring ignition delay times. The detailed reaction mechanism was constructed using the Reaction Mechanism Generator software. Sensitivity and flux analyses were used to identify key rate and thermochemical parameters, which were then computed using quantum chemistry to improve the mechanism. Validation of the final model against the 1-20 bar 600-1500 K experimental data is presented with a discussion of the kinetics. The model is in excellent agreement with most of the shock tube and RCM data. Strong non-monotonic variation in conversion and product distribution is observed in the flow-tube experiments as the temperature is increased, and unusually strong pressure dependence and significant heat release during the compression stroke is observed in the RCM experiments. These observations are largely explained by a close competition between radical decomposition and addition to O2 at different sites in MPE; this causes small shifts in conditions to lead to big shifts in the dominant reaction pathways. The validated mechanism was used to study the chemistry occurring during ignition in a diesel engine, simulated using Ignition Quality Test (IQT) conditions. At the IQT conditions, where the MPE concentration is higher, bimolecular reactions of peroxy radicals are much more important than in the RCM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Degradation in Photovoltaic Encapsulant Transmittance: Results of the Second PVQAT TG5 Artificial Weathering Study

The optical degradation of encapsulants from ultraviolet (UV) radiation has historically resulted in a significant loss in performance throughout the life of a photovoltaic (PV) module. International Electrotechnical Commission (IEC) test methods have recently been developed to screen for PV encapsulants prone to loss in optical performance. The present study was performed to benchmark polymeric packaging materials relative to IEC 62788-1-4 (covering the measurement of optical transmittance) and IEC 62788-1-7 (on the durability of transmittance), provide feedback toward improvement of the methods, and develop insight regarding optical degradation. Contemporary materials were examined, including poly(ethylene-co-vinyl acetate) (EVA), thermoplastic polyolefin (TPO), polyolefin elastomer (POE), and polyvinyl butyral (PVB) encapsulants; a poly(ethene-co-tetrafluoroethene)/poly(ethylene terephthalate) (ETFE/PET) transparent backsheet; and a polystyrene (PS) working reference material. The use of silica-, specialty-, and rolled-glass was also compared in laminated coupons. Specimen size was separately examined from 2.5 to 12.5 cm. Weathering was performed with a xenon source, using IEC TS 62788-7-2 methods A2, A3, A4, and A5 (chamber temperature of 55 degrees C, 65 degrees C, 75 degrees C, or 85 degrees C), respectively. Characterizations were made using a UV-visible-near-infrared (UV-VIS-NIR) spectrophotometer (transmittance and reflectance, with and without an integrating sphere), a UV-VIS fluorescence spectrophotometer, a camera, and an optical microscope. Performance was analyzed, including solar weighted transmittance, yellowness index, UV cut-off wavelength, and haze (scattering). Separate Arrhenius analyses were performed to assess retention of transmittance and changes in yellowness index. The activation energy for both characteristics was found to range from 15-80 kJ mol-1, with an average of 48 kJ mol-1, similar to the average of 45 kJ mol-1 identified in the previous international PV Quality Assurance Task Force (PVQAT) Task Group 5 (TG5) study of more traditional encapsulants. The separate degradation modes of discoloration and scattering were distinguished in the encapsulants using a comprehensive spectral characterization. Based on these results, the IEC 62788-1-7 pass/fail criteria of 5% change in transmittance was confirmed to identify a known bad encapsulant.

durability↗

Mesoscale to microscale wind farm flow modeling and evaluation

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to direct future research in this area.

17 WIND ENERGY↗

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

Environmental Molecular Sciences Laboratory↗

Two-Scale 13 C Metabolic Flux Analysis for Metabolic Engineering

Accelerating the Design-Build-Test-Learn (DBTL) cycle in synthetic biology is critical to achieving rapid and facile bioengineering of organisms for the production of, e.g., biofuels and other chemicals. The Learn phase involves using data obtained from the Test phase to inform the next Design phase. As part of the Learn phase, mathematical models of metabolic fluxes give a mechanistic level of comprehension to cellular metabolism, isolating the principle drivers of metabolic behavior from the peripheral ones, and directing future experimental designs and engineering methodologies. Furthermore, the measurement of intracellular metabolic fluxes is specifically noteworthy as providing a rapid and easy-to-understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis in the Learn phase of the DBTL cycle, where we show how one can take the isotope labeling data from a 13 C labeling experiment and immediately turn it into a determination of cellular fluxes that points in the direction of genetic engineering strategies that will advance the metabolic engineering process.For our modeling purposes we use the Joint BioEnergy Institute (JBEI) Quantitative Metabolic Modeling (jQMM) library, which provides an open-source, python-based framework for modeling internal metabolic fluxes and making actionable predictions on how to modify cellular metabolism for specific bioengineering goals. It presents a complete toolbox for performing different types of flux analysis such as Flux Balance Analysis, 13 C Metabolic Flux Analysis, and it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) [1]. In addition to several other capabilities, the jQMM is also able to predict the effects of knockouts using the MoMA and ROOM methodologies. The use of the jQMM library is illustrated through a step-by-step demonstration, which is also contained in a digital Jupyter Notebook format that enhances reproducibility and provides the capability to be adopted to the user's specific needs. As an open-source software project, users can modify and extend the code base and make improvements at will, providing a base for future modeling efforts.

13C Metabolic flux analysis↗

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

Software developers must adapt to keep up with the changing capabilities of platforms so that they can utilize the power of High-Performance Computers (HPC), including exascale systems. OpenMP, a directive-based parallel programming model, allows developers to include directives to existing C, C++, or Fortran code to allow node level parallelism without compromising performance. This paper describes our CI/CD efforts to provide easy evaluation of the support of OpenMP across different compilers using existing testsuites and benchmark suites on HPC platforms. Our main contributions include (1) the set of a Continuous Integration (CI) and Continuous Development (CD) workflow that captures bugs and provides faster feedback to compiler developers, (2) an evaluation of OpenMP (offloading) implementations supported by AMD, HPE, GNU, LLVM, and Intel, and (3) evaluation of the quality of compilers across different heterogeneous HPC platforms. With the comprehensive testing through the CI/CD workflow, we aim to provide a comprehensive understanding of the current state of OpenMP (offloading) support in different compilers and heterogeneous platforms consisting of CPUs and GPUs from NVIDIA, AMD, and Intel.

Jarmusch, Aaron↗

Precision measurements of Higgs hadronic decay modes at the FCC-ee

The expected precision at the FCC-ee on the product $σ$ x $\mathcal{B} \large{(}H → b\bar{b}, c\bar{c}, s\bar{s}, gg\large{)}$ of Higgs boson production cross sections times branching ratios of hadronic decays is presented. This study provides the first comprehensive determination of all major hadronic Higgs decay modes in a combined fit at future $e^+e^−$ colliders, using both Higgs-strahlung $(ZH)$ and Vector boson fusion $(v\bar{v}H)$ production processes, with a full treatment of interference effects in the $v\bar{v}jj$ final state. It assumes four identical IDEA detectors collecting $e^+e^−$ collisions at $\sqrt{s}$ = 240 and 365 GeV. The combination of all channels across both energies, with full covariance between production and decay modes, yields a production cross-section times branching-ratio precision at the percent to per-mil level for the dominant hadronic final states $(b\bar{b}, c\bar{c}, gg)$. These results provide a comprehensive input to the determination of Higgs coupling projections at the FCC-ee, and they establish for the first time sensitivity to the rare decay $H → s\bar{s}$, demonstrating that FCC-ee has the potential to provide evidence of the strange-quark Yukawa coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗