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At least 1,261 records · Page 70

Structure, dynamics, and redox reactivity of an all-purpose flavodoxin

The flavodoxin of Rhodopseudomonas palustris CGA009 (Rp9Fld) supplies highly reducing equivalents to crucial en- zymes such as hydrogenase, especially when the organism is iron-restricted. By acquiring those electrons from photodriven electron flow via the bifurcating electron transfer flavoprotein, Rp9Fld provides solar power to vital metabolic processes. To understand Rp9Fld’s ability to work with diverse partners, we solved its crystal structure. We observed the canonical fla- vodoxin (Fld) fold and features common to other long-chain Flds but not all the surface loops thought to recognize part- ner proteins. Moreover, some of the loops display alternative structures and dynamics. To advance studies of protein– protein associations and conformational consequences, we assigned the 19F NMR signals of all five tyrosines (Tyrs). Our electrochemical measurements show that incorporation of 3- 19 F-Tyr in place of Tyr has only a modest effect on Rp9Fld’s redox properties even though Tyrs flank the flavin on both sides. Meanwhile, the 19 F probes demonstrate the expected paramagnetic effect, with signals from nearby Tyrs becoming broadened beyond detection when the flavin semiquinone is formed. However, the temperature dependencies of chemical shifts and linewidths reveal dynamics affecting loops close to the flavin and regions that bind to partners in a variety of systems. These coincide with patterns of amino acid type conservation but not retention of specific residues, arguing against detailed specificity with respect to partners. We pro- pose that the loops surrounding the flavin adopt altered con- formations upon binding to partners and may even participate actively in electron transfer.

19F NMR↗

Ga speciation in Ga/H-ZSM-5 by in-situ transmission FTIR spectroscopy

H-ZSM-5 supported Ga (Ga/H-ZSM-5) has long been recognized as a promising catalyst for nonoxidative dehydrogenation and dehydroaromatization of alkanes. However, Ga speciation under reaction conditions remains controversial. In this work, in-situ transmission Fourier Transform infrared (FTIR) spectroscopy is employed to systematically investigate Ga speciation in Ga/H-ZSM-5 with three Si/Al ratios (15, 28 and 39) and a wide range of Ga/Al ratios (0–1.7). Quantitative FTIR spectroscopy with pyridine reveals that one Ga atom roughly replaces one Brønsted acid site (BAS) at Ga/BAS ratio up to 0.7, however, only up to ~80% of the BAS on the H-ZSM-5 can be exchanged even with excess amounts of Ga. At a low Si/Al ratio of 15, the intensity of GaH x bands on reduced Ga/H-ZSM-5 at 550 °C increases almost linearly at low Ga loadings (Ga/Al < 0.13), and then levels off. In contrast, no detectable GaH x bands are observed on Ga/H-ZSM-5 with a high Si/Al ratio of 39, with Ga/Al ratios up to 1.3. The dependence of GaH x bands on both the Si/Al ratios and the Ga/Al ratios shows that Ga speciation varies with BAS density in the zeolite. We hypothesize that paired BAS sites are preferentially exchanged with Ga + , leading to the formation of Ga + –H + pair sites, while the exchange of isolated BAS form isolated Ga+ species. Using water as a probe molecule, we show that isolated Ga + and Ga + –H + pair sites have distinct properties, i.e., the former can be easily oxidized by water at 150 °C to form GaOOH species, while the latter is inactive under the same conditions. Furthermore, these results provide direct experimental evidence for the existence of two types of Ga species on reduced Ga/H-ZSM-5, highlighting the possibility that they have different catalytic activities in alkane dehydrogenation reactions.

03 NATURAL GAS↗

Transition state stabilization depends on solvent identity, pore size, and hydrophilicity for epoxidations in zeolites

Ti-silicates activate H 2 O 2 to form Ti-hydroperoxo and Ti-peroxo intermediates that can react with alkenes to form epoxide products. Comparisons of kinetics for 1-octene epoxidation with H 2 O 2 on Ti-BEA and Ti-MFI catalysts with different hydrophilicities in methanol (CH 3 OH) or acetonitrile (CH 3 CN) solvents show the significance of the solvent for stabilizing catalytically-relevant species and the complex interdependencies between solvent, catalyst topology, and hydrophilicity. Epoxidation turnover rates are higher in CH 3 CN than CH 3 OH for Ti-BEA, but the opposite trend is observed for Ti-MFI. Ti-silicates with greater silanol densities, however, give greater epoxidation turnover rates than their hydrophobic counterparts in both solvents. Kinetic, spectroscopic, and thermodynamic analyses show that differences in turnover rates mainly arise from changes in the stabilization of reactive surface species by solvent mediated interactions, because the mechanism of the reaction and stability of the fluid-phase reactants remain similar in CH 3 CN and CH 3 OH. Specifically, apparent activation free energy values ($ΔG^{‡}_{App}$) indicate that surface intermediates responsible for alkene epoxidation are stabilized to a greater extent in CH 3 CN on Ti-BEA and in CH 3 OH on Ti-MFI. Hydrophilic Ti-silicates present lower ($ΔG^{‡}_{App}$) values regardless of solvent identity, which suggests that these differences correspond to the number of hydrogen-bonding solvent molecules found near reactive species bound to Ti active sites. Finally, taken together, these findings demonstrate the role of solvent molecules in allowing reactive intermediates to recognize the properties of active sites beyond the length-scale of covalent bonds, which carry implications for epoxidation but also other reactions within solvent-filled pores of microporous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Site heterogeneity and broad surface-binding isotherms in modern catalysis: Building intuition beyond the Sabatier principle

Learning the science of heterogeneous catalysis and electrocatalysis always starts with the simple case of a flat, uniform surface with an ideal adsorbate. It has of course been recognized for a century that real catalysts are more complicated. For the increasingly complex catalysts of the 21st century, this Perspective argues that surface heterogeneity and non-ideal binding isotherms are central features, and their implications need to be incorporated in current thinking. A variety of systems are described herein where catalyst complexity leads to broad, non-Langmuirian surface isotherms for the binding of hydrogen atoms – and this occurs even for ideal, flat Pt(111) surfaces. Modern catalysis employs nanoscale materials whose surfaces have substantial step, edge, corner, impurity, and other defect sites, and they increasingly have both metallic and non-metallic elements M n X m , including metal oxides, chalcogenides, pnictides, carbides, doped carbons, etc. The surfaces of such catalysts are often not crystal facets of the bulk phase underneath, and they typically have a variety of potential active sites. Catalytic surfaces in operando are often non-stoichiometric, amorphous, dynamic, and impure, and often vary from one part of the surface to another. Understanding of the issues that arise at such nanoscale, multi-element catalysts is just beginning to emerge. Yet these catalysts are widely discussed using Brønsted/Bell-Evans-Polanyi (BEP) relations, volcano plots, Tafel slopes, the Butler-Volmer equation, and other linear free energy relations (LFERs), which all depend on the implicit assumption that the active sites are “similar” and that surface adsorption is close to ideal. These assumptions underly the ubiquitous intuition based on the Sabatier Principle, that the fastest catalysis will occur when key intermediates have free energies of adsorption that are not too strong nor too weak. Current catalysis research often aims to minimize the complexity of non-ideal isotherms through experimental and computational design (e.g., the use of single crystal surfaces), and these studies are the foundation of the field. In contrast, this Perspective argues that the heterogeneity of binding sites and binding energies is an inherent strength of these catalysts. Here, this diversity makes many nanoscale catalysts inherently a high-throughput screen wrapped in a tiny package. Only by making the heterogeneity part of the foundation of catalysis models, sorting the types of active sites and dissecting non-ideal binding isotherms, will modern catalysis learn to harness the inherent diversity of real catalysts. Controlling and exploiting diversity rather than avoiding it will help to optimize complex modern catalysts and catalytic conditions.

Mayer, James M.↗

Effects of particle shape and surface roughness on van der Waals interactions and coupling to dynamics in nanocrystals

The van der Waals interaction between colloids and nanoparticles is one of the key components to understanding particle aggregation, attachment, and assembly. While the ubiquity of anisotropic particle shapes and surface roughness is well-recognized in nanocrystalline materials, the effect of both on van der Waals forces and torques has not been adequately investigated. Here, in this study, we develop a numerical scheme and determine the van der Waals forces and torques between cubic particles with multiple configurations and relative orientations. Our results show that the van der Waals torque due to anisotropic particle shapes is appreciable at nearly all configurations and mutual angles, outcompeting Brownian motion for various materials systems and conditions. The effect of surface roughness increases this shape effect, resulting in stronger van der Waals interactions ascribed to protrusions in the rough surfaces. Moreover, a scaling analysis indicates that the surface roughness alters the separation dependence of the van der Waals force and, more importantly, significantly influences the dynamics of two approaching particles. Our results clearly demonstrate that surface roughness and anisotropic shape play a crucial role in the energetics and kinetics of various particle-scale and emergent phenomena, such as crystal growth by oriented attachment, nanomaterials synthesis and assembly, mud flow rheology, as well as the deposition of natural nanocrystals within the subsurface.

Arbitrary configurations↗

Integrating biomass quality variability in stochastic supply chain modeling and optimization for large-scale biofuel production

The production of biofuels using second-generation feedstocks has been recognized as an important alternative source of sustainable energy and its demand is expected to increase due to regulations such as the Renewable Fuel Standard. However, the pathway to biofuel industry maturity faces unique, unaddressed challenges. Here, to address this challenges, this article presents an optimization model which quantifies and controls the impact of biomass quality variability on supply chain related decisions and technology selection. We propose a two-stage stochastic programming model and associated efficient solution procedures for solving large-scale problems to (1) better represent the random nature of the biomass quality (defined by moisture and ash contents) in supply chain modeling, and (2) assess the impact of these uncertainties on the supply chain design and planning. The proposed model is then applied to a case study in the state of Tennessee. Results show that high moisture and ash contents negatively impact the unit delivery cost since poor biomass quality requires the addition of quality control activities. Experimental results indicate that supply chain cost could increase as much as 27%–31% when biomass quality is poor. We assess the impact of the biomass quality on the topological supply chain. Our case study indicates that biomass quality impacts supply chain costs; thus, it is important to consider the impact of biomass quality in supply chain design and management decisions.

09 BIOMASS FUELS↗

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Uncollided flux techniques for arbitrary finite element meshes

The uncollided angular flux can be difficult to compute accurately in discrete-ordinate radiation transport codes, especially in weakly-scattering configurations with localized sources. It has long been recognized that an analytical or semi-analytical treatment of the uncollided flux, coupled with a discrete-ordinate solution for the collided flux, can yield dramatic improvements in solution accuracy and computational efficiency. In this paper, we present such an algorithm for the semi-analytical calculation of the uncollided flux. This algorithm is unique in several aspects: (1) it applies to arbitrary polyhedral cells (and can be thus coupled with collided flux solvers that support arbitrary polyhedral meshes without the need for explicit tetrahedral re-meshing), (2) it provides accurate uncollided solutions near sources, (3) it is devised with parallel implementation in mind, and (4) it minimizes the total number of traced rays and maintains a reasonable ray density on each local subdomain. This paper provides a complete derivation of the algorithm and demonstrates its important features on a set of simple examples and a standard transport benchmark. Assessment of its parallel performance will be the subject of a subsequent paper.

42 ENGINEERING↗

A second-order-in-time, explicit approach addressing the redundancy in the low-Mach, variable-density Navier-Stokes equations

A novel algorithm for explicit temporal discretization of the variable-density, low-Mach Navier-Stokes equations is presented here in this study. Recognizing there is a redundancy between the mass conservation equation, the equation of state, and the transport equation(s) for the scalar(s) which characterize the thermochemical state, and that it destabilizes explicit methods, we demonstrate how to analytically eliminate the redundancy and propose an iterative scheme to solve the resulting transformed scalar equations. The method obtains second-order accuracy in time regardless of the number of iterations, so one can terminate this subproblem once stability is achieved. Hence, flows with larger density ratios can be simulated while still retaining the efficiency, low cost, and parallelizability of an explicit scheme. The temporal discretization algorithm is used within a pseudospectral direct numerical simulation which extends the method of Kim, Moin, and Moser for incompressible flow to the variable-density, low-Mach setting, where we demonstrate stability for density ratios up to ~25.7.

97 MATHEMATICS AND COMPUTING↗

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗

Data driven investigation to understand the influence of total solids on biological biogas upgrading

In situ biogas upgrading achieves CO 2 conversion to CH 4 via hydrogenotrophic methanogenesis; however, gas-liquid mass transfer constraints limit the upgrading performance. Recognizing that optimization studies often underrepresent the effects of total solids (TS) and organic loading rate (OLR), this study undertook a holistic, statistics driven assessment of operating conditions for in situ H 2 assisted biogas upgrading, centering the analysis on TS and OLR. A dataset of 31 studies was compiled and comprised 99 observations. A rigorous analytical framework was employed, combining data standardization, fixed- and random-effects (REML) weighted regressions with cluster-robust errors, stratified analyses, and machine learning. Mixed-effects meta regression indicated that TS was the main factor explaining differences of methane fraction (CH 4 %) when considering the between studies heterogeneity. Focusing on a near-stoichiometric subset (H 2 /CO 2 ≈ 4:1), TS remained significant. Stratified results showed a stronger negative relationship between TS and CH 4 % in UASB reactors than in CSTRs, with a negative effect under mesophilic conditions and no significant effect under thermophilic conditions. A Random Forest model corroborated the statistical findings, consistently ranking H 2 /CO 2 ratio, OLR, TS, and hydrogen injection rate (HIR) as the most influential predictors. These findings delineate trends across increasing TS levels, particularly between 1% and 10%, and provide preliminary insights for TS above 15% in in situ biogas upgrading. They further provide insights for the influence of TS by reactor type and temperature, thereby advancing the evidence base for implementing biological CO 2 conversion to CH 4 in practice.

In situ biogas upgrading↗

High-performance LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode by nanoscale lithium sulfide coating via atomic layer deposition

The commercialization of nickel-rich LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) has been hindered by its continuous loss of practical capacity and reduction in average working voltage. To address these issues, surface modification has been well-recognized as an effective strategy. Different from the coatings reported in literature to date, in this work, we for the first time report a sulfide coating, amorphous Li 2 S via atomic layer deposition (ALD). Here, our study revealed that the conformal nano-Li 2 S coating shows exceptional protection over the NMC811 cathodes, accounting for the dramatically boosted capacity retention from ~11.6% to ~71% and the evidently mitigated voltage reduction from 0.39 to 0.18 V after 500 charge–discharge cycles. In addition, the Li 2 S coating remarkably improved the rate capability of the NMC811 cathode. Our investigation further revealed that all these beneficial effects of the ALD-deposited nano-Li 2 S coating lie in the following aspects: (i) maintain the mechanical integrity of the NMC811 electrode; (ii) stabilize the NMC electrode/electrolyte interface; and (iii) suppress the irreversible phase transition of NMC structure. Particularly, this study also has revealed that the nano-Li 2 S coating has played some unique role not associated with traditional non-sulfide coatings such as oxides. In this regard, we disclosed that the Li 2 S layer has reacted with the released O 2 from the NMC lattices, and thereby has dramatically mitigated electrolyte oxidation and electrode corrosion. Thus, this study is significant and has demonstrated that sulfides may be an important class of coating materials to tackle the issues of NMCs and other layered cathodes in lithium batteries.

36 MATERIALS SCIENCE↗

Nuclear waste Educator's workshop: What and how do we teach about nuclear waste?

A workshop was held at the Massachusetts Institute of Technology (MIT) on July 25th and 26th, 2022. The objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste management and disposal, which requires knowledge from diverse disciplines, including nuclear, chemical, civil, environmental, and geological science and engineering. The 49 participants included university professors, researchers, industry experts, and government officials from different areas. First, we have developed a list of key fundamental knowledge on waste management and disposal across the nuclear fuel cycle. In addition, we discussed strategies on how to teach students with diverse backgrounds through innovative teaching strategies as well as how to attract students into this area. Through the workshop, we identified the critical needs to (1) develop community resources for nuclear waste education; (2) synthesize historical perspectives, including past contamination and the management of general hazardous waste; (3) emphasize a complete life-cycle perspective, including proper waste management as the key component for energy sustainability; (4) teach students how to communicate about the key facts and risks to technical and non-technical audiences; and (5) accelerate the use of the state-of-art-technologies to attract and retain a young workforce. Furthermore, we aim to build a diverse, inclusive community that supports students in developing their own narratives about nuclear waste, particularly in recognizing that antagonistic views have been important to improving safety and protecting public health and the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Critical review of functionalized silica sorbent strategies for selective extraction of rare earth elements from acid mine drainage

We report the ubiquitous and growing global reliance on rare earth elements (REEs) for modern technology and the need for reliable domestic sources underscore the rising trend in REE-related research. Adsorption-based methods for REE recovery from liquid waste sources are well-positioned to compete with those of solvent extraction, both because of their expected lower negative environmental impact and simpler process operations. Functionalized silica represents a rising category of low cost and stable sorbents for heavy metal and REE recovery. These materials have collectively achieved high capacity and/or high selective removal of REEs from ideal solutions and synthetic or real coal wastewater and other leachate source. These sorbents are competitive with conventional materials, such as ion exchange resins, activated carbon; and novel polymeric materials like ion-imprinted particles and metal organic frameworks (MOFs). This critical review first presents a data mining analysis for rare earth element recovery publications indexed in Web of science, highlighting changes in REE recovery research foci and confirming the sharply growing interest in functionalized silica sorbents. A detailed examination of sorbent formulation and operation strategies to selectively separate heavy (HREE), middle (MREE), and light (LREE) REEs from the aqueous sources is presented. Selectivity values for sorbents were largely calculated from available figure data and gauged the success of the associated strategies, primarily: (1) silane-grafted ligands, (2) impregnated ligands, and (3) bottom-up ligand/silica hybrids. These were often accompanied by successful co-strategies, especially bite angle control, site saturation, and selective REE elution. Recognizing the need to remove competing fouling metals to achieve purified REE “baskets,” we highlight techniques for eliminating these species from acid mine drainage (AMD) and suggest a novel adsorption-based process for purified REE extraction that could be adapted to different water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bisphenol A degradation by manganese oxides at circumneutral pH: Quantitative evaluation of dissolved Mn(III) species with pyrophosphate

Although trivalent manganese (Mn(III)) species have been recognized as crucial intermediates in the degradation of organic contaminants by Mn oxides, quantitative research on their specific roles remains scarce. Here, our study investigated the degradation processes of an organic pollutant, Bisphenol A (BPA), by dissolved Mn(III) and Mn(III)-bearing oxides, and elucidated the differences of the underlying mechanisms and reaction pathways between several Mn oxides and dissolved Mn(III). Our results indicated that BPA degradation rates with Mn(III)-bearing oxides alone follow the order: δ-MnO 2 >> γ-MnOOH > Mn 3 O 4 . Adding pyrophosphate (PP) significantly enhanced BPA degradation by promoting the formation of Mn(III)-PP complexes and exposing more reactive sites, achieved through destabilizing the crystal structure and mitigating of Mn(II) readsorption, particularly in γ-MnOOH and Mn 3 O 4 . Our kinetic model revealed that heterogeneous degradation by Mn oxides is the predominant reaction pathway, accounting for 61.4 %, 87.8 %, and 73.8 % of the total degraded BPA for δ-MnO 2 , γ-MnOOH, and Mn 3 O 4 , respectively, even in the presence of significant amount of dissolved Mn(III) intermediates due to high PP concentrations. These results offer mechanistic details on BPA degradation by Mn oxides and the influence of ligand concentration, providing helpful insights for optimizing degradation strategies of organic pollutants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Soil frost controls streamflow generation processes in headwater catchments

The relationship between snowmelt and spring streamflow is changing under warming temperatures and diminishing snowpack. At the same time, the hydrologic connectivity across catchment landscape elements, such as snowpack and surface wetlands, can play a critical role in controlling the routing of snowmelt to streams. The role of hydrologic connectivity is important in headwater regions of the continental northern latitudes, where catchments have low topographic relief and seasonally frozen ground. Nevertheless, the effects of soil frost on the sequence, timing, and magnitudes of hydrologic events that drive the movement of water from a snowpack to a stream are not fully understood. Therefore, we examine two questions: First, what is the flowpath that snow melt and precipitation from spring rain events takes to generate spring streamflow, and second, what hydrologic, climatic, or landscape variables exert the most control on the magnitude of streamflow? In this work, we use long-term hydrological records from the two reference basins at the Marcell Experimental Forest in northern Minnesota to analyze the cascading effects across precipitation, snow, water table elevation, soil frost, and streamflow in peatland-dominated headwater catchments. We identify a sequence of fill-and-spill effects across the landscape that control the timing of spring streamflow generation. Then, we use stepwise regression to show that soil frost is a key supporting predictor for both the magnitude of streamflow in the spring as it adds significantly to the predictive power of precipitation and water table elevation. Our results highlight the importance of recognizing the role of soil frost, when present, on the partitioning of snowmelt between overland runoff and water table recharge during the critical snowmelt period, as well as the later partitioning between evapotranspiration and subsurface flows.

54 ENVIRONMENTAL SCIENCES↗

Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.

60 APPLIED LIFE SCIENCES↗

Pulse radiolysis studies of the reaction of nitrogen dioxide with the vitamin B₁₂ complexes Cob(II)alamin and nitrocobalamin

Although now recognized to be an important reactive nitrogen species in biological systems that modifies the structures of proteins, DNA and lipids, there few studies on the reactivity of ˙NO2, including the reactions between ˙NO2 and transition metal complexes. We report kinetic studies on the reaction of ˙NO2 with two forms of vitamin B12 – cob(II)alamin and nitrocobalamin. UV-vis spectroscopy and HPLC analysis of the product solution show that ˙NO2 cleanly oxidizes the metal center of cob(II)alamin to form nitrocobalamin, with a second-order rate constant of (3.5 ± 0.3) × 10⁸ M⁻¹ s ⁻¹ (pH 7.0 and 9.0, RT, I = 0.20 M). The stoichiometry of the reaction is 1:1. No reaction is detected by UV-vis spectroscopy and by HPLC analysis of the product solution when nitrocobalamin is exposed to up to 2.0 mol equiv.˙NO2.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗