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At least 199 records · Page 11

Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques

Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. Finally, this review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.

59 BASIC BIOLOGICAL SCIENCES↗

Geometric Optimization of an Electrochemical Purification Cell to Prevent Corrosion in CSP Plants During Operation

When exposed to moisture or oxygen, molten chloride salts produce corrosive impurities which degrade containment alloys. This can significantly decrease the lifetime and increase costs of molten-salt-based systems. To overcome this barrier, we designed and modeled an electrochemical purification cell to remove the corrosive impurity MgOH+. Various reactor architectures, including continuous stirred tank reactors (CSTRs) and plug flow reactors (PFRs) were investigated. Steady-state thermoelectric properties were evaluated using analytical methods, allowing assessment of the effects of structure and design parameters such as flow rate, cell length, and cross-sectional area of molten salt. The results suggest that our design could most effectively increase reliability and decrease costs of molten-chloride-salt-based systems by protecting them during continuous operation using an annular plug flow reactor.

analytical modeling↗

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part I: Model Formulation

Here, this paper formulates a new particle-in-cell method for the Vlasov–Maxwell system. Under the Lorenz gauge condition, Maxwell’s equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the generalized (conjugate) momentum. A notable advantage offered by the Hamiltonian formulation is the elimination of time derivatives in the Lorenz gauge formulation that are required by the standard Newton–Lorentz treatment of the particles. This allows the fields to retain the full time-accuracy guaranteed by the field solver. The resulting updates for particles require only knowledge of the fields and their spatial derivatives. An analytical method for constructing these spatial derivatives is presented that exploits the underlying integral solution used in the field solver for the wave equations. Moreover, these derivatives are demonstrated to converge at the same rate as the fields in both time and space. The Method of Lines Transpose field solver we consider in this work is globally first-order accurate in time and high-order accurate in space (e.g., fourth- and fifth-order) and belongs to a larger class of methods which are unconditionally stable, can address geometry, and leverage $\mathcal {O}(N)$ fast summation methods for efficiency. We demonstrate the method on several well-established benchmark problems on bounded domains, including a plasma sheath as well as a relativistic particle beam. The efficacy of the proposed formulation is established by comparing with a second-order accurate finite-difference time-domain method that employs a leapfrog time advance for particles and a charge conserving map suitable for bounded domains. The new method shows mesh-independent numerical heating properties even in cases where the plasma Debye length is smaller than the grid spacing. This is an important feature of the new method for problems defined on bounded domains, because it permits the use of coarser grids in space in the representation of the fields. Such a capability has significant implications for the simulation of plasmas in bounded domains with complex geometry, where the ratio between the largest and smallest cells can vary significantly. The use of high-order spatial approximations in the new method also means that fewer grid points are required in order to achieve a fixed accuracy. Our results also suggest that the new method can be used with fewer simulation particles per cell compared to the benchmark explicit method, which permits further computational savings.

97 MATHEMATICS AND COMPUTING↗

A Critical Review of the Circular Economy for Lithium-Ion Batteries and Photovoltaic Modules: Status, Challenges, and Opportunities

To meet net-zero emissions and cost targets for power production, recent analysis indicates that photovoltaic (PV) capacity in the United States could exceed 1 TW by 2050 alongside comparable levels of energy storage capacity, mostly from batteries. For comparison, the total U.S. utility-scale power capacity from all energy sources in 2020 was 1.2 TW (EIA 2022), of which solar satisfied approximately 3% (DOE 2021). With such massive scales of deployment, questions have arisen regarding issues of material supply for manufacturing, end-of-life management of technologies, environmental impacts across the life cycle, and economic costs to both individual consumers and society at large. A set of solutions to address these issues center on the development of a circular economy - shifting from a take-make-waste linear economic model to one that retains the value of materials and products as long as possible, recovering materials at end of life to recirculate back into the economy. With limited global experience, scholars and practitioners have begun to investigate circular economy pathways, focusing on applying novel technologies and analytical methods to fast-growing sectors like renewable energy. This critical review aims to synthesize the growing literature to identify key insights, gaps, and opportunities for research and implementation of a circular economy for two of the leading technologies that enable the transition to a renewable energy economy: solar PV and lithium-ion batteries (LIBs). We apply state-of-the-science systematic literature review procedures to critically analyze over 3,000 publications on the circular economy of solar PV and LIBs, categorizing those that pass a series of objective screens in ways that can illuminate the current state of the art, highlight existing impediments to a circular economy, and recommend future technological and analytical research. We conclude that while neither PV nor LIB industries have reached a circular economy, they are both on a path towards increased circularity. Based on our assessment of the state of current literature and scientific understanding, we recommend research move beyond its prior emphasis on recycling technology development to more comprehensively investigate other CE strategies, more holistically consider economic, environmental and policy aspects of CE strategies, increase leveraging of digital information systems that can support acceleration towards a CE, and to continue to study CE-related aspects of LIB and PV markets.

circular economy↗

Analytical Study to Use the Excess Digester Gas of Wastewater Treatment Plants

This study presents an analytical method that can be used to enhance the power production rate and the energy-saving at wastewater treatment plants. The digester used at wastewater treatment plants produces digester gas by anaerobic digestion, with which biofuel production can be achieved. Biofuels can be used to meet some of the energy requirements of the wastewater treatment facility through combined heat and power (CHP) gas engines (cogeneration). Using micro gas turbine (MGT), a CHP technology can be introduced in wastewater treatment plants (WWTPs). The combination of MGTs and absorption chillers is a promising technology as it produces electricity, heating, and cooling simultaneously. The study demonstrated how the waste heat of MGTs could be used to drive absorption chillers. In this analytical study, a detailed technical and economic analysis is provided on the trigeneration system, i.e., the integration of MGTs and absorption chillers driven by waste digester gas of the wastewater treatment plants. It can meet the heating and cooling demands of the plants, which promote the reduction of utility costs. The technology presented is also useful for other thermal energy users.

09 BIOMASS FUELS↗

A Review of Nuclear Forensics: 2016-2020

The study of nuclear forensics harkens back to the Manhattan Project-era, when scientists first started to analyze the debris from the 1945 Trinity test. Political turmoil stemming from the Cold War and the rehabilitation of Germany following WWII has led to new challenges in international security involving nuclear proliferation. Nuclear materials have, on occasion, been lost, misplaced, or stolen from former Soviet countries, and illicit materials have been interdicted all over the world. The National Technical Nuclear Forensics Center (NTNFC) was established in 2006, and has been at the forefront of drive to advance nuclear forensic capabilities in the United States. The ultimate goal of nuclear forensics is to examine nuclear and other radioactive materials using analytical techniques to determine origin and history of the material, particularly in the context of law enforcement investigations. Nuclear forensics can be divided into two parts: predetonation and post-detonation. Pre-detonation forensics, as the name implies, is the investigation of a nuclear material or weapon that has not been detonated or involved in an explosion, whereas postdetonation forensics is the study of activation or fission products in debris or the environment following the use of a nuclear or radiological dispersal device (RDD). Both parts require a number of analytical chemical and radiochemical techniques to determine identification of the material. Many advancements in analytical techniques, including rapidity, sample size, and forensic signatures have been made in recent years. The analytical methods that can be used in a nuclear forensic investigation, such as mass spectrometry and gamma spectroscopy, have been described in detail in previous reviews, including Straub et.al, and will not be explained here. This review will discuss recent publications (from 2016 to present) describing advancements of techniques such as radiochronometry, morphology, development of novel reference materials, and inter-laboratory collaborations for both pre- and post-detonation nuclear forensics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoscale modeling and semi-analytical approach for the microstructure-aware effective thermal conductivity of porous polygranular materials

Here we established a comprehensive modeling approach for investigating the microstructure-aware effective thermal conductivity ($κ_{eff}$) for porous microstructures containing solid particles and gaseous pores. Our approach combines the mesoscale computational modeling framework and the semi-analytical method, allowing for efficient prediction of $κ_{eff}$ for realistic porous microstructures, while considering complicated microstructural thermal conduction pathways effectively in the prediction. We used the diffuse-interface mesoscale computational model to generate extensive simulated $κ_{eff}$ data for realistic digital representations of microstructures with wide ranges of porosity ($f_p$), thermal conductivity of the gas phase ($κ_g$), and thermal conductivity of the solid phase ($κ_s$). From the simulated data, we identified two property variation regimes for $κ_{eff}$: (1) a slow $κ_{eff}$ increase for $κ_s ~ κ_g$; and (2) a faster $κ_{eff}$ increase for $κ_s \gg κ_g$. To capture the key features of the relationship between the microstructure and $κ_{eff}$, we derived a semi-analytical model by introducing structure and intensification factors. The two new factors incorporate the calibrated effective contribution of the solid volume with $κ_s$ and additional interfacial effects into the prediction of $κ_{eff}$, respectively, allowing for consideration of parallel, serial, and interfacial conduction mechanisms effectively. Using the selected simulation data, we quantified key model parameters within the semi-analytical model and verified that the parameterized model exhibits excellent agreement with simulated $κ_{eff}$ for the entire range of the parameter space.

36 MATERIALS SCIENCE↗

ACS Sustainable Chemistry & Engineering Virtual Special Issue on Recent Advances in Biomass Characterization and Modeling

Recognizing the importance of biomass characterization and modeling, a virtual special issue (VSI) entitled Recent Advances in Biomass Characterization and Modeling was organized to showcase the recent contributions to this emerging field. This VSI features contributions from leading scientists in the biorefinery field, intending to provide the readers with the latest advances in analytical methodology and modeling to characterize biomass feedstocks and biomass-derived products. Further, the VSI contains perspectives and research articles. Advanced analytical methods that measure the mechanical, chemical, physical, biological, and other properties of biomass and biomass pyrolysis products are described along with their application’s limitations in two perspectives. Biomass is a multicomponent/multiscale, complex, nonconducting, and highly heterogeneous material; thus, it could be problematic for many characterization techniques. Traditional biomass analysis tools that are slow, laborious, and generally require harsh reagents have been replaced or supplemented by simpler and more rapid chromatographic and spectroscopic approaches such as GC-MS, HPLC, FTIR, Raman, and NMR spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multimode two-dimensional vibronic spectroscopy. I. Orientational response and polarization-selectivity

Two-dimensional Electronic–Vibrational (2D EV) spectroscopy and two-dimensional Vibrational–Electronic (2D VE) spectroscopy are among the newest additions to the coherent multidimensional spectroscopy toolbox, and they are directly sensitive to vibronic couplings. In this first of two papers, the complete orientational response functions are developed for a model system consisting of two coupled anharmonic oscillators and two electronic states in order to simulate polarization-selective 2D EV and 2D VE spectra with arbitrary combinations of linearly polarized electric fields. Here, we propose analytical methods to isolate desired signals within complicated spectra and to extract the relative orientation between vibrational and vibronic dipole moments of the model system using combinations of polarization-selective 2D EV and 2D VE spectral features. Time-dependent peak amplitudes of coherence peaks are also discussed as means for isolating desired signals within the time-domain. This paper serves as a field guide for using polarization-selective 2D EV and 2D VE spectroscopies to map coupled vibronic coordinates on the molecular frame.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogenolysis of Polypropylene and Mixed Polyolefin Plastic Waste over Ru/C to Produce Liquid Alkanes

Catalytic depolymerization of polyolefins is a promising chemical recycling strategy to create value-added products from waste plastics, which are accumulating in landfills and the natural environment at unsustainable rates. The cleavage of strong C–C bonds in polyolefins can be performed using a noble metal and hydrogen via a hydrogenolysis mechanism. Previously, we identified ruthenium nanoparticles supported on carbon (Ru/C) as a highly active heterogeneous catalyst for the conversion of polyethylene into liquid and gaseous n-alkanes under mild conditions. In the present study, we investigated the catalytic depolymerization of polypropylene (PP) under mild conditions (200–250 °C, 20–50 bar H 2 ). We demonstrate that Ru/C produces C 5 –C 32 iso-alkane yields above 68% in the absence of solvent and identify trade-offs between product yield and temperature, hydrogen pressure, and reaction time. We apply a rigorous analytical method to quantify all liquid and gaseous alkane products. The characterized catalyst was found to be recyclable after the complete depolymerization of high molecular weight PP (M w ~ 340,000 Da) to liquid and gaseous hydrocarbons and after depolymerization of a postconsumer PP centrifuge tube. Finally, the catalyst was shown to be effective in depolymerizing a mixture of high-density polyethylene and PP to produce a mixture of linear and branched liquid alkanes, demonstrating feasibility for the depolymerization of streams of mixed polyolefin waste.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Elastic, Plastic, and Damage Features in Fracturing of Self-reinforced Thermoplastic Composites via Non-destructive Digital Imaging Correlation

This work demonstrated the utilization of non-destructive Digital Imaging Correlation (DIC) method to characterize the elastic, plastic, and damage features during the Mode I intra-laminar fracturing process of self-reinforced thermoplastic composites by using a self-reinforced polypropylene (PP) composite as an example. The DIC results clearly showed the development of huge plastic zone (PZ) and non-negligible Fracture Process Zone (FPZ) in front of the notch tip during the fracturing process, and the geometries and sizes of the foregoing zones at the peak load were further quantified. Such an interesting fracturing behavior of self-reinforced thermoplastic composites is way different from brittle materials (e.g., glass, acrylic, etc.), ductile materials (e.g., aluminum, steel, etc.), and even quasi-brittle materials (e.g., concrete, nanoparticle-reinforced composites, tough ceramics, wood, cement, carbon/glass fiber-reinforced polymers, etc.). Thus, understanding the elastic, plastic, and damage features is the first step before better characterizing the material fracture properties of self-reinforced thermoplastic composites through new analytical methods and computational modeling. These efforts are of utmost importance for wide applications of self-reinforced thermoplastic composites in various engineering fields in the future.

Lightweight Composites, Self-reinforced Thermoplas↗

An economic assessment of behind-the-meter photovoltaics paired with batteries on the Hawaiian Islands.

Due to natural variability and uncertainty, the ever-increasing penetration of solar generation in Hawaii presents challenges to power grid operators to maintain reliable system operation. Demand response (DR) has the potential to be a cost-effective tool for Hawaii to reach its aggressive renewable energy goals while maintaining the reliability of power grids. The Hawaii Public Utilities Commission has approved the Hawaiian Electric Company's revised portfolio of DR programs. The companies have released a grid services purchase agreement and subscribed an initial tranche of load into their DR programs. This paper presents innovative analytical methods and comprehensive economic assessment for distributed photovoltaics (PV) paired with battery energy storage systems (BESSs) for two new DR programs, including fast frequency response and capacity grid service. Optimal dispatch and sizing methods are proposed for the paired system considering different tariff schedules and PV compensation programs across five islands. It was found that while the best resource configuration and potential economic benefits vary with tariff structure, a BESS paired with PV can be optimally dispatched to generate multiple value streams simultaneously. Compensation from DR programs is an important value stream to help increase the cost-effectiveness of the integrated system.

Battery energy storage system↗

A Synchrotron-Based Vacuum Ultraviolet Photoionization Mass Spectrometer-Coupled Microreactor To Probe Thermocatalysis

Vacuum ultraviolet photoionization (VUV-PI) mass spectrometry offers an isomer-selective and universal ionization with minimal fragmentation detection of organics in complex chemical systems such as pyrolysis and combustion. Here, in this study, we report a state-of-the-art experimental setup of a universal catalytic microreactor combined with a molecular beam to investigate the thermocatalytic oxidation of a heterogeneous system relevant for probing reactions at gas–solid interfaces. In strong contrast to traditional off-line analytical methods, this technique is capable of identifying and quantifying short-lived species (radicals) as well as stable products to decipher initial reaction steps via the detection of nascent products. The thermocatalytic oxidative degradation of exo-tetrahydrodicyclopentadiene (JP-10), a high energy-density hydrocarbon fuel, over solid titanium–aluminum–boron reactive mixed metal nanopowder (Ti-Al-B RMNP) is exploited to showcase potential applications. Overall, some 59 nascent gas-phase products are identified via photoionization efficiency (PIE) curves, including oxygenated species and hydrocarbons comprising closed-shell molecules and radicals. The critical temperature for complete oxidative decomposition of JP-10 was lowered by 450 K from 1400 K to 950 K, indicating an efficient thermocatalytic action of Ti-Al-B nanoparticles on JP-10. The enabling of a universal chemical microreactor along with VUV-PI mass spectrometry broadens the applicability of this technique to hydrocarbon fuel oxidation and pyrolysis characterization. This isomer-selective sensitive probing along with the detection of radical transients makes the aforementioned technique superior to other conventional analytical techniques such as microflow tube and pyrolysis-gas chromatography coupled with mass spectrometry for investigating similar pyrolysis reactions and comprehensive quantification.

Paul, Dababrata [Univ. of Hawaii at Manoa, Honolul↗

Final Report on Aerosol Pretreatment Technology Performance and Benchmarking

Solvent-based post-combustion CO 2 capture (PCC) technology remains one of the leading methods to combat global CO 2 emissions produced from large-scale coal-fired power production. Advanced solventbased PCC technology has made significant improvements in design and performance that reduce capital and operating costs to enable its commercial use. Key to low cost, manageable logistics, and environmentally safe operation of solvent-based PCC technology are minimal solvent losses from the process through the treated gas stream exiting PCC plant absorbers. High flue gas aerosol particle concentrations (>10 5 particles/cm 3 ) for particles in the range of 70-200 nm have been shown to cause significant amine solvent losses for solvent-based PCC processes through several mechanisms including absorption of solvent and water into growing aerosol particles. Flue gas aerosol pretreatment technology is the only realistic and economically attractive method to reduce very high aerosol particle concentrations (>10 7 particles/cm 3 ) to enable solvent-based PCC for existing power plants lacking sufficient particle removal systems, such as baghouses. The overall goal of this project was to design, construct, independently test, and evaluate three flue gas aerosol pretreatment technologies identified to significantly reduce high aerosol particle concentrations (>10 7 particles/cm 3 ) in the 70-200 nm particle size range: (1) a novel, high-velocity water injection spray concept developed by RWE and tested by Linde, (2) an innovative electrostatic precipitator (ESP) device with optimized operating conditions developed by Washington University in St. Louis (WUSTL), and (3) a non-regenerative sorbent-based filter technology developed by InnoSepra for SO x and NO x removal from coal-fired power plant flue gas. Each technology has been validated with tests on 500-1000 scfm of actual coal-fired flue gas and evaluated in terms of particle removal efficiency (%), cost competitiveness, and environmental impact. Aerosol measurements were performed upstream and downstream of each aerosol reduction unit during independent testing of each technology using advanced instrumentation and analytical methods provided by WUSTL. To perform aerosol measurements, isokinetic probes were inserted into flanged pipes attached to the flue gas piping, and a small suction pump was used to sample gas containing aerosol particles. Aerosol particle number concentrations (# particles/cm 3 ) and size distributions were then measured using a scanning mobility particle sizer (SMPS, TSI Inc.) for very fine particles (<1,000 nm) and a particle counter manufactured by GRIMM for particles larger than 1,000 nm. This report summarizes the aerosol removal performance results from pilot scale testing of each technology. Performance results have been benchmarked against pre-defined targets and other flue gas aerosol pretreatment technologies with documented performance. Linde Gas North America LLC has been the prime contractor to DOE responsible for overall project management and provided the design for the high-velocity water spray-based aerosol removal technology based on a design concept developed by the German utility company RWE.

20 FOSSIL-FUELED POWER PLANTS↗

Fluorescence Microscopic Investigations of Molecular Dynamics in Self–Assembled Nanostructures

Many analytical methods employ self-assembled nanostructured materials as chemical recognition media. Molecular permeation through these materials exhibits unique selectivity owing to nanoconfinement-induced enhancement of permeant–nanostructure interactions. This Personal Account introduces our efforts to investigate the detailed dynamics of single or a small number of molecules in nanostructured materials. Here, we developed new experimental and analysis approaches built upon laser-based fluorescence microscopy to measure the detailed translational and orientational dynamics of molecules diffusing in horizontally-oriented, cylindrical nanostructures, including surfactant micelles, silica mesopores, block copolymer microdomains, and bolaamphiphile-based organic nanotubes. Our studies clarified nanoscale details on the structural/chemical heterogeneity of the nanostructures, and their impacts on molecular mass transport dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2D HSQC Chemical Shifts of Impurities from Biomass Pretreatment

Two dimensional (2D) heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) is a powerful analytical method which can be used to elucidate the structure of biomass. During processing, biomass is typically subjected to some form of chemical treatment which can be performed with a variety of compounds. The presence of these compounds, even in trace amounts, has the potential to contaminate the sample and lead to misinterpretation of the HSQC spectra. Here we report the chemical shifts of 29 compounds commonly used in biomass processing which have the potential to contaminate the biomass samples and lead to the misinterpretation of peaks associated with biomass (Populus trichocarpa ) pretreated via autohydrolysis. The identification of these chemical shifts could serve as a valuable tool in preventing errors in characterizing biomass via HSQC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Formation of monomeric Sn(ii) and Sn(iv) perfluoropinacolate complexes and their characterization by 119 Sn Mössbauer and 119 Sn NMR spectroscopies

The synthesis and characterization of a series of Sn(II) and Sn(IV) complexes supported by the highly electron-withdrawing dianionic perfluoropinacolate (pinF) ligand are reported herein. Three analogs of [Sn IV (pin F ) 3 ] 2- with NEt 3 H + (1), K + (2), and {K(18C6)} + (3) counter cations and two analogs of [SnII(pinF)2]2- with K+ (4) and {K(15C5) 2 } + (5) counter cations were prepared and characterized by standard analytical methods, single-crystal X-ray diffraction, and 119 Sn Mössbauer and NMR spectroscopies. The six-coordinate SnIV(pinF) complexes display 119 Sn NMR resonances and 119 Sn Mössbauer spectra similar to SnO 2 (cassiterite). In contrast, the four-coordinate SnII(pinF) complexes, featuring a stereochemically-active lone pair, possess low 119 Sn NMR chemical shifts and relatively high quadrupolar splitting. Furthermore, the Sn(II) complexes are unreactive towards both Lewis bases (pyridine, NEt 3 ) and acids (BX 3 , Et 3 NH + ). Calculations confirm that the Sn(II) lone pair is localized within the 5s orbital and reveal that the Sn 5p x LUMO is energetically inaccessible, which effectively abates reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enter Gaussian Mixture Modeling Extensions for Improved False Discovery Rate Estimation in GC-MS Metabolomics

Identifying small molecules (e.g., metabolites) is key towards driving scientific advancement in metabolomics, and gas chromatography–mass spectrometry (GC-MS) is an analytic method that may be applied to facilitate this process. The typical GC-MS identification workflow involves quantifying the similarity of an observed sample spectrum and other features (e.g. retention index) to that of several references, noting the compound of the best-matching reference spectrum as the identified metabolite. While a deluge of similarity metrics exists, none characterize the error rate of generated identifications, thereby presenting an unknown risk of false identification or discovery. To quantify this unknown risk, we propose a model-based framework for estimating the false discovery rate (FDR) among a set of identifications. Extending the traditional mixture modeling framework, our method incorporates both similarity score and experimental information in estimating the FDR. We apply these models to identification lists derived from across 548 samples of varying complexity and sample type (e.g., fungal species, standard mixtures, etc.), comparing their performance to that of the traditional Gaussian mixture model (GMM). Through simulation, we additionally assess the impact of reference library size on the accuracy of FDR estimates. In comparing the best performing model extensions to the GMM, our results indicate relative decreases in median absolute estimation error (MAE) ranging from 12% to 70%, based on comparisons of the median MAEs across all hit-lists. Results indicate that these relative performance improvements generally hold despite library size, however FDR estimation error typically worsens as the set of reference compounds diminishes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗