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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Non-heme High-Spin {FeNO} 6–8 Complexes: One Ligand Platform Can Do It All

Heme and non-heme iron-nitrosyl complexes are important intermediates in biology. While there are numerous examples of low-spin heme iron-nitrosyl complexes in different oxidation states, much less is known about high-spin (hs) non-heme iron-nitrosyls in oxidation states other than the formally ferrous NO adducts ({FeNO} 7 in the Enemark-Feltham notation). In this study, we present a complete series of hs-{Fe-NO} 6-8 complexes using the TMG 3 tren coligand. Redox transformations from the hs-{FeNO} 7 complex [Fe(TMG 3 tren)(NO)] 2+ to its {FeNO} 6 and {FeNO} 8 analogs do not alter the coordination environment of the iron center, allowing for detailed comparisons between these species. Here, we present new MCD, NRVS, XANES/EXAFS and Mössbauer data, demonstrating that these redox transformations are metal based, which allows us to access hs-Fe(II)-NO¯, Fe(III)-NO¯ and Fe(IV)-NO¯ complexes. Vibrational data, analyzed by NCA, directly quantify changes in Fe-NO bonding along this series. Optical data allow for the identification of a “spectator” charge-transfer transition that, together with Mössbauer and XAS data, directly monitors electronic changes of the Fe center. Using EXAFS, we are also now able to provide structural data for all complexes. The magnetic properties of the complexes are further analyzed (from magnetic Mössbauer). The properties of our hs-{FeNO} 6-8 complexes are then contrasted to corresponding, low-spin iron-nitrosyl complexes, where redox transformations are generally NO-centered. The hs-{FeNO} 8 complex can further be protonated by weak acids, and the product of this reaction is characterized. Altogether, these results provide unprecedented insight into the properties of biologically relevant non-heme iron-nitrosyl complexes in three relevant oxidation states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Separating the effects of nucleotide and EB binding on microtubule structure

Microtubules (MTs) are polymers assembled from αβ-tubulin heterodimers that display the hallmark behavior of dynamic instability. MT dynamics are driven by GTP hydrolysis within the MT lattice, and are highly regulated by a number of MT-associated proteins (MAPs). How MAPs affect MTs is still not fully understood, partly due to a lack of high-resolution structural data on undecorated MTs, which need to serve as a baseline for further comparisons. Here we report three structures of MTs in different nucleotide states (GMPCPP, GDP, and GTPγS) at near-atomic resolution and in the absence of any binding proteins. These structures allowed us to differentiate the effects of nucleotide state versus MAP binding on MT structure. Kinesin binding has a small effect on the extended, GMPCPP-bound lattice, but hardly affects the compacted GDP-MT lattice, while binding of end-binding (EB) proteins can induce lattice compaction (together with lattice twist) in MTs that were initially in an extended and more stable state. We propose a MT lattice-centric model in which the MT lattice serves as a platform that integrates internal tubulin signals, such as nucleotide state, with outside signals, such as binding of MAPs or mechanical forces, resulting in global lattice rearrangements that in turn affect the affinity of other MT partners and result in the exquisite regulation of MT dynamics.

Science & Technology - Other Topics↗
DOE OSTI2019

A JSON to CMake tool

As part of the conversion of the MCNP®testing system to CTest, a tool was needed to generate CMake variables from JSON formatted data structure. The system was first implemented using the JSON to CMake parser which with some slight modifications provided data useful for the MCNP CTest testing system. Upon further evaluation, we found it to be slow when setting up the 1600 tests during the CMake configuration step. Not only was it slow, it did not validate the JSON files during configuration allowing for unexpected behavior. Upon some web searching we came across a simple recursive python example that would provide the same capability needed by our testing system. This python example was effectively wrapped into a single python script that was used to convert the JSON data into CMake variables. This tool is attached as json_to_cmake.py and is listed in the appendix. In essence, the tool provides single variables for each value defined within the JSON file. The name for the variable is constructed by using the associated object names and array indicies needed to deference the variable itself. In the following sections, examples are provided to better describe how this is done.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Neural network representation of electronic structure from ab initio molecular dynamics

Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. Here we introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When it is applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born–Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving the way to previously inaccessible or challenging avenues in materials modeling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Structural Evidence of Interanionic Hydrogen Bonding in Phosphoric Acid Solutions

Interanionic hydrogen bonding (IAHB) is a noncovalent interaction between like-charged ions that challenges conventional electrostatic understanding. This study provides direct structural evidence of IAHB in concentrated aqueous phosphoric acid (PA) solutions, which exhibit >60% dissociation under these conditions. Oxygen K-edge X-ray absorption fine structure spectroscopy, combined with electron affinity time-dependent density functional theory calculations, reveals the formation of stable, cyclic phosphate-phosphate IAHB dimers at PA concentrations ≥7 M. Extended X-ray absorption fine structure data show distinct long-range ordering consistent with these dimers, and near-edge X-ray absorption fine structure spectra confirm a concentration-dependent transition from monomeric to dimeric species. Energy decomposition analysis through density functional theory shows that the formation of solution-phase IAHB is energetically favored and is attributed to polarization of and the charge transfer between the two fragments driven by the surrounding solvent molecules, in addition to the permanent electrostatics. These findings offers crucial structural insights into the H-bonded networks in concentrated PA, highlighting the critical role of solvent in facilitating anion–anion association.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Local spectroscopy of a gate-switchable moiré quantum anomalous Hall insulator

Abstract In recent years, correlated insulating states, unconventional superconductivity, and topologically non-trivial phases have all been observed in several moiré heterostructures. However, understanding of the physical mechanisms behind these phenomena is hampered by the lack of local electronic structure data. Here, we use scanning tunnelling microscopy and spectroscopy to demonstrate how the interplay between correlation, topology, and local atomic structure determines the behaviour of electron-doped twisted monolayer–bilayer graphene. Through gate- and magnetic field-dependent measurements, we observe local spectroscopic signatures indicating a quantum anomalous Hall insulating state with a total Chern number of ±2 at a doping level of three electrons per moiré unit cell. We show that the sign of the Chern number and associated magnetism can be electrostatically switched only over a limited range of twist angle and sample hetero-strain values. This results from a competition between the orbital magnetization of filled bulk bands and chiral edge states, which is sensitive to strain-induced distortions in the moiré superlattice.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evidence for a Single Holocene Paleoseismic Event on the Pajarito Fault, Northern New Mexico

Low-slip rate fault systems tend to be less studied than their high-slip rate counterparts, and paleoseismic techniques used to study them may pose challenges in interpretation that differ from high-slip rate systems. A good example of this is the Pajarito fault system (PFS), a normal fault complex within the Rio Grande rift. Despite numerous previous paleoseismic trenching studies conducted on the PFS between 1990 and 2003, considerable uncertainty remains regarding its Holocene paleoseismic history, particularly for the primary Pajarito fault (PF). To further clarify the PF paleoseismic history, we present data from paleoseismic investigations of 6 trenches at 3 distinct locations along the PF. Though the totality of the age and structural data obtained in this study is complex and not entirely consistent with any one interpretation, a single Holocene paleoearthquake occurring younger than ∼1,600 to 2,300 kcal yr BP is the simplest interpretation. It is possible that the PF records two Holocene events, with a penultimate event 6.9–2.4 kcal yr BP event and the aforementioned most recent event (MRE) between 2.3 and 1.6 kcal yr BP. However, only a single wall of one trench, out of a total of 12 walls in our 6 trenches, provides evidence supporting that interpretation. This study finds evidence of a single late Holocene paleoseismic event on the PF and sparse evidence for 2 Holocene paleoseismic events on the PF and highlights the benefits of logging multiple trench walls to better understand the complexity that results from this low-slip rate, low-deposition-rate fault system.

58 GEOSCIENCES↗
DOE OSTI2019

SUSPECT: MINLP special structure detector for Pyomo

We present SUSPECT, an open source toolkit that symbolically analyzes mixed-integer nonlinear optimization problems formulated using the Python algebraic modeling library Pyomo. We present the data structures and algorithms used to implement SUSPECT. SUSPECT works on a directed acyclic graph representation of the optimization problem to perform: bounds tightening, bound propagation, monotonicity detection, and convexity detection. We show how the tree-walking rules in SUSPECT balance the need for lightweight computation with effective special structure detection. SUSPECT can be used as a standalone tool or as a Python library to be integrated in other tools or solvers. Here, we highlight the easy extensibility of SUSPECT with several recent convexity detection tricks from the literature. We also report experimental results on the MINLPLib 2 dataset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

X-ray crystallography–based structural elucidation of enzyme-bound intermediates along the 1-deoxy-d-xylulose 5-phosphate synthase reaction coordinate

1-Deoxy-D-xylulose 5-phosphate synthase (DXPS) uses thiamine diphosphate (ThDP) to convert pyruvate and D-glyceraldehyde 3-phosphate ( D -GAP) into 1-deoxy-D-xylulose 5-phosphate (DXP), an essential bacterial metabolite. DXP is not utilized by humans; hence, DXPS has been an attractive antibacterial target. In this work, we investigate DXPS from Deinococcus radioduransN (DrDXPS), showing that it has similar kinetic parameters K m D-GAP AND K m pyruvate (54 ± 3 and 11 ± 1 μM, respectively) and comparable catalytic activity (kcat = 45 ± 2 min –1 ) with previously studied bacterial DXPS enzymes and employing it to obtain missing structural data on this enzyme family. In particular, we have determined crystallographic snapshots of DrDXPS in two states along the reaction coordinate: a structure of DrDXPS bound to C2α-phosphonolactylThDP (PLThDP), mimicking the native pre-decarboxylation intermediate C2α-lactylThDP (LThDP), and a native post-decarboxylation state with a bound enamine intermediate. The 1.94-Å-resolution structure of PLThDP-bound DrDXPS delineates how two active-site histidine residues stabilize the LThDP intermediate. Meanwhile, the 2.40-Å-resolution structure of an enamine intermediate-bound DrDXPS reveals how a previously unknown 17-Å conformational change removes one of the two histidine residues from the active site, likely triggering LThDP decarboxylation to form the enamine intermediate. These results provide insight into how the bi-substrate enzyme DXPS limits side reactions by arresting the reaction on the less reactive LThDP intermediate when its cosubstrate is absent. They also offer a molecular basis for previous low-resolution experimental observations that correlate decarboxylation of LThDP with protein conformational changes.

1-deoxy-D-xylulose 5-phosphate synthase (DXPS)↗
DOE OSTI2021

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2019

Clustering of nonvalently bonded NO{sub 2}…O{sub 2}N fragments at C(sp{sup 3}) atoms

Based on the 'invariom' approach and the 'Atoms in Molecules' theory, a simplified method is proposed to reveal and analyze bonding interatomic interactions using large arrays of structural data. The technique was tested taking nonvalent interactions between nitro groups bonded to C(sp{sup 3}) atoms as examples. Geometric clustering of structural fragments was performed and the interaction strength and covalent contribution distributions were analyzed. Relationships between the fragment clustering results and nonvalent bonding pattern features are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural study of hcp and liquid iron under shock compression up to 275 GPa

Here we combine nanosecond laser shock compression with in situ picosecond x-ray diffraction to provide structural data on iron up to 275 GPa. We constrain the extent of hcp-liquid coexistence, the onset of total melt, and the structure within the liquid phase. Our results indicate that iron, under shock compression, melts completely by 258(8) GPa. A coordination number analysis indicates that iron is a simple liquid at these pressure-temperature conditions. We also perform texture analysis between the ambient body-centered-cubic (bcc) α, and the hexagonal-closed-packed (hcp) high-pressure ε-phase. We rule out the Rong-Dunlop orientation relationship (OR) between the α and ε - phase s. However, we cannot distinguish between three other closely related ORs: Burger's, Mao-Bassett-Takahashi, and Potter's OR. The solid-liquid coexistence region is constrained from a melt onset pressure of 225(3) GPa from previously published sound speed measurements and full melt [246.5(1.8)–258(8) GPa] from x-ray diffraction measurements, with an associated maximum latent heat of melting of 623 J/g. This value is lower than recently reported theoretical estimates and suggests that the contribution to the earth's geodynamo energy budget from heat release due to freezing of the inner core is smaller than previously thought. Melt pressures for these nanosecond shock experiments are consistent with gas gun shock experiments that last for microseconds, indicating that the melt transition occurs rapidly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exploring Integer Sum Reduction using Atomics on Intel CPU

Atomic functions are useful in updating a shared variable by multiple threads, barrier synchronizations, constructing complex data structures, and building high-level frameworks. In this paper, we focus on the evaluation and analysis of integer sum reduction, a common data parallel primitive. We convert the sequential reduction into parallel OpenCL implementations on the CPU. We also develop three micro kernels, which allow us to understand the relationships between the kernel performance and the operations involved in reduction. The results of the micro kernels show that increasing the work-group size linearly can linearly improve the kernel performance. There is a sweet spot in the relationship between the work-group size and barrier synchronization overhead. The performance of the atomics over local memory are not sensitive to the work-group size. The sum reduction kernel with vectorized memory accesses can improve the performance of the baseline kernel for a wide range of work-group sizes. However, the vectorization efficiency shrinks with the growing work-group size. We also find that the vendor’s default OpenCL kernel optimization does not improve the kernel performance. On average, disabling the optimization can reduce the execution time of the kernel with vectorized memory accesses by 15%. We attribute the performance drop to the fact that the default kernel optimizations instantiate a large number of atomics over global memory when implicitly vectorizing the kernel computation.

atomics↗
DOE OSTI2023

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Probing the Cys-Tyr Cofactor Biogenesis in Cysteine Dioxygenase by the Genetic Incorporation of Fluorotyrosine

Cysteine dioxygenase (CDO) is a nonheme iron enzyme that adds two oxygen atoms from dioxygen to the sulfur atom of L -cysteine. Adjacent to the iron site of mammalian CDO, there is a post-translationally generated Cys-Tyr cofactor, whose presence substantially enhances the oxygenase activity. The formation of the Cys-Tyr cofactor in CDO is an autocatalytic process, and it is challenging to study by traditional techniques because the cross-linking reaction is a side, uncoupled, single-turnover oxidation buried among multiple turnovers of L -cysteine oxygenation. Here, we take advantage of our recent success in obtaining a purely uncross-linked human CDO due to site-specific incorporation of 3,5-difluoro- L -tyrosine (F 2 -Tyr) at the cross-linking site through the genetic code expansion strategy. Using EPR spectroscopy, we show that nitric oxide ( • NO), an oxygen surrogate, similarly binds to uncross-linked F 2 -Tyr157 CDO as in wild-type human CDO. Additionally, we determined X-ray crystal structures of uncross-linked F 2 -Tyr157 CDO and mature wild-type CDO in complex with both L -cysteine and • NO. These structural data reveal that the active site cysteine (Cys93 in the human enzyme), rather than the generally expected tyrosine (i.e., Tyr157), is well-aligned to be oxidized should the normal oxidation reaction uncouple. This structure-based understanding is further supported by a computational study with models built on the uncross-linked ternary complex structure. Together, these results strongly suggest that the first target to oxidize during the iron-assisted Cys-Tyr cofactor biogenesis is Cys93. Based on these data, a plausible reaction mechanism implementing a cysteine radical involved in the cross-link formation is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗