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The Effects of Compounded Model Size Reductions on Adversarial Robustness
Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.
Recent Progress in Electrochemical Upgrading of Bio-Oil Model Compounds and Bio-Oils to Renewable Fuels and Platform Chemicals
Sustainable production of renewable carbon-based fuels and chemicals remains a necessary but immense challenge in the fight against climate change. Bio-oil derived from lignocellulosic biomass requires energy-intense upgrading to produce usable fuels or chemicals. Traditional upgrading methods such as hydrodeoxygenation (HDO) require high temperatures (200–400 °C) and 200 bar of external hydrogen. Electrochemical hydrogenation (ECH), on the other hand, operates at low temperatures (<80 °C), ambient pressure, and does not require an external hydrogen source. These environmental and economically favorable conditions make ECH a promising alternative to conventional thermochemical upgrading processes. ECH combines renewable electricity with biomass conversion and harnesses intermediately generated electricity to produce drop-in biofuels. This review aims to summarize recent studies on bio-oil upgrading using ECH focusing on the development of novel catalytic materials and factors impacting ECH efficiency and products. Here, electrode design, reaction temperature, applied overpotential, and electrolytes are analyzed for their impacts on overall ECH performance. We find that through careful reaction optimization and electrode design, ECH reactions can be tailored to be efficient and selective for the production of renewable fuels and chemicals. Preliminary economic and environmental assessments have shown that ECH can be viable alternative to convention upgrading technologies with the potential to reduce CO2 emissions by 3 times compared to thermochemical upgrading. While the field of electrochemical upgrading of bio-oil has additional challenges before commercialization, this review finds ECH a promising avenue to produce renewable carbon-based drop-in biofuels. Finally, based on the analyses presented in this review, directions for future research areas and optimization are suggested.
Synthesis and characterization of isomeric cis- and trans-pyrrone model compounds.
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A Manganese Compound I Model with a High Reactivity in the Oxidation of Organic Substrates and Water
In this work, a high-valent manganese(IV)-hydroxo porphyrin π-cation radical complex, [Mn(IV)(OH)(Porp +• )(X)] + , was synthesized and characterized spectroscopically. The Mn porphyrin intermediate was highly reactive in alkane hydroxylation and oxygen atom transfer reactions. More importantly, the Mn porphyrin intermediate reacted with water at a fast rate, resulting in the dioxygen evolution. To the best of our knowledge, we report the first manganese Cpd I model compound bearing a porphyrin π-cation radical ligand with a high reactivity in oxidation reactions, including water oxidation.
Heme compound II models in chemoselectivity and disproportionation reactions
Heme compound II models bearing electron-deficient and -rich porphyrins, [Fe IV (O)(TPFPP)(Cl)] – (1a) and [Fe IV (O)(TMP)(Cl)] – (2a), respectively, are synthesized, spectroscopically characterized, and investigated in chemoselectivity and disproportionation reactions using cyclohexene as a mechanistic probe. Interestingly, cyclohexene oxidation by 1a occurs at the allylic C–H bonds with a high kinetic isotope effect (KIE) of 41, yielding 2-cyclohexen-1-ol product; this chemoselectivity is the same as that of nonheme iron(IV)-oxo intermediates. In contrast, as observed in heme compound I models, 2a yields cyclohexene oxide product with a KIE of 1, demonstrating a preference for C=C epoxidation. The latter result is interpreted as 2a disproportionating to form [Fe IV (O)(TMP+˙)] + (2b) and Fe III (OH)(TMP), and 2b becoming the active oxidant to conduct the cyclohexene epoxidation. In contrast to 2a, 1a does not disproportionate under the present reaction conditions. DFT calculations confirm that compound II models prefer C–H bond hydroxylation and that disproportionation of compound II models is controlled thermodynamically by the porphyrin ligands. Other aspects, such as acid and base effects on the disproportionation of compound II models, have been discussed as well.
Models for the analysis of CN violet radiation behind shock waves in air contaminated with carbon-bearing compounds
Models for analyzing CN violet radiation effects behind shock waves in air contaminated with carbon-bearing compounds
Data-Centric Development of Lignin Structure–Solubility Relationships in Deep Eutectic Solvents Using Molecular Simulations
Lignin is a natural source of aromatic chemicals with significant potential as an abundant, renewable feedstock for value-added products. Deep eutectic solvents (DES)–solvents composed of a hydrogen bond donor (HBD) and acceptor (HBA) in varying ratios–have emerged as a highly tunable class of solvents for lignin solubilization. However, the variety of possible DES compositions and limited molecular-scale understanding of lignin solubility makes solvent selection a challenge without laborious trial-and-error experimentation. To address these challenges, we use classical molecular dynamics (MD) simulations to study the interactions of lignin model compounds with various DES–water systems. Quantitative parameters (descriptors) were calculated by postprocessing the MD results and used to train a regression model that predicts experimentally determined solubilities of lignin model compounds. This approach revealed that the most important descriptors of solubility are the system temperature, solute hydrophilicity, and metrics quantifying hydrogen bonding. Maximizing the interactions between solute–HBD (hydrophobic group), water–HBD (hydrophilic group), and water–HBA molecules led to the highest model compound solubility. Our results support a hydrotropic mechanism in which extensive DES–water hydrogen bonding and favorable HBD interactions with the solute promote high solubility. We applied the regression model derived using model compounds to predict the solubility of representative lignin oligomers. The model predicted lignin oligomers’ solubilities in good agreement with experiments, indicating that the simulations of model compounds can be extended to predict the solubility of larger lignin compounds across a range of solvent compositions and temperatures. Furthermore, these findings provide new molecular-scale insight into lignin solubilization mechanisms and a new method for computationally screening potential solvent systems for lignin valorization.
Wholly Aromatic Ether-imides. Potential Materials for n-Type Semiconductors
We report on the synthesis and characterization of a novel series low-molar-mass ether-imide rod-shaped model compounds. All ether-imides were obtained by terminating the appropriate rigid core dianhydride, i.e. pyromellitic dianhydride (PMDA), 1,4,5,8-naphthalenetetracarboxylic dianhydride (NDA), 3,3',4,4'-biphenyltetracarboxylic dianhydride (BPDA), and 3,3,4,4'-oxydiphthalic dianhydride (ODPA) with three flexible aryl-ether tails of different chain length. The mono-functional aryl-ether amines, i.e. 4-(3-phenoxy-phenoxy)-phenylamine (2) and 4-(3-phenoxy-3-phenoxy-phenoxy)-phenylamine (4), were synthesized using standard fluoro-displacement and Ullmann condensation techniques. The corresponding ether-imide model compounds were obtained in high yields using a one-step solution imidization procedure. Increasing the number of meta-substituted aryl-ether units reduces the melt transition temperatures and at the same time it increases the solubility of the model compounds. Most model compounds are crystalline solids and form isotropic melts upon heating. 2,7-Bis-(-4-phenoxy-phenyl)-benzo[Imn][3,8]phenanthroline1,3,6,8-tetraone (NDA-n0), however, displays a smectic A (SA) when cooled from the isotropic phase, followed by what appears to be either a highly ordered smectic phase or a, columnar phase. This is the first example, known to date, in which a mesophase is detected in a wholly aromatic ether-imide compound. For all compounds we present spectroscopic data and X-ray diffraction data. Cyclic voltammetry was used to determine the redox behavior and pertinent energy levels of the model compounds.
Variable Ion Compositions of Solar Energetic Particle Events in the Inner Heliosphere: A Field Line Braiding Model with Compound Injections
We propose a model for interpreting highly variable ion composition ratios in solar energetic particle (SEP) events recently observed by the Parker Solar Probe (PSP) at 0.3–0.45 au. We use numerical simulations to calculate SEP propagation in a turbulent interplanetary magnetic field with a Kolmogorov power spectrum from large scales down to the gyration scale of energetic particles. We show that when the source regions of different species are offset by a distance comparable to the size of the source regions, the observed energetic particle composition He/H can be strongly variable over more than two orders of magnitude, even if the source ratio is at the nominal value. Assuming a 3 He/ 4 He source ratio of 10% in impulsive 3 He-rich events and the same spatial offset of the source regions, the 3 He/ 4 He ratio at observation sites also vary considerably. The variability of the ion composition ratios depends on the radial distance, which can be tested by observations made at different radial locations. We discuss the implications of these results on the variability of ion composition of impulsive events and on further PSP and Solar Orbiter observations close to the Sun.
The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates (CRADA Final Report)
Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.
Prediction of crosslink density of solid propellant binders
A quantitative theory is outlined which allows calculation of crosslink density of solid propellant binders from a small number of predetermined parameters such as the binder composition, the functionality distributions of the ingredients, and the extent of the curing reaction. The parameter which is partly dependent on process conditions is the extent of reaction. The proposed theoretical model is verified by independent measurement of effective chain concentration and sol and gel fractions in simple compositions prepared from model compounds. The model is shown to correlate tensile data with composition in the case of urethane-cured polyether and certain solid propellants. A formula for the branching coefficient is provided according to which if one knows the functionality distributions of the ingredients and the corresponding equivalent weights and can measure or predict the extent of reaction, he can calculate the branching coefficient of such a system for any desired composition.
Estimation in a modified binomial distribution
Estimation techniques in a modified binomial distribution, developed to describe thunderstorm activity over a small area at Cape Kennedy, Florida, are compared. A compound model is also developed and compared with the original model. The minimum Chi square technique is compared with the maximum likelihood and method of moments techniques. The minimum Chi square technique, although useful in complicated models, compared poorly compared to the other techniques. The maximum likelihood and method of moments were comparable. The compound model fit better in every case based on a likelihood ratio test comparing the compound model with the modified binomial model using maximum likelihood estimators.
Synthesis of low color, atomic oxygen resistant polyimides
The purpose of this project was to develop low color, atomic oxygen resistant polyimides for potential applications on spacecraft in low earth orbit. The material is needed in order to protect satellites and spacecraft from the gases and radiation found at those altitudes. Phosphorous containing polyimides have been shown to be especially resistant to corrosion and weight loss under oxygen plasma. Unfortunately the color of these phosphorous containing polyimides is still too high for them to be good heat insulators. While they are not as effective as teflon, the current material of choice. polyimides are much less dense than teflon and would be especially valuable if they could be made with low color. The approach taken was to synthesize a monomer which would contain the elements needed for giving the final polyimide its desired properties. In particular the monomer should incorporate phosphine or phosphine oxides and have bulky side groups to block any color forming charge transfer structures. The target molecule, 3,5-di-(trifluoromethylphenyl)-bis(3-aminophenyl) phosphine oxide, (containing both a phosphine oxide group and a bulky ditrifluoromethylphenyl group) was synthesized via three reactions in overall yield of 21 percent. In addition, a model compound, bis(3-phenylamine) phenyl phosphine oxide, was synthesized two different ways in order to establish the conditions for the nitration of phosphine oxides and their reduction to the amine. Finally, a trisubstituted phosphine oxide was synthesized. In all, seven phosphorus containing organic compounds were synthesized, purified and characterized. The model compound was reacted with oxydiphthalic anhydride to form a polyamic acid with inherent viscosity of 0.34. This material was cast into a film and heated, forming a normally colored fairly strong polyimide with a Tg of 240 C. The target compound was reacted with 6-fluorodiphthalic anhydride to give a polyamic acid with inherent viscosity of 0.19 and cast to give a heavily cracked colored film with a Tg of 230 C.
Microwave-Assisted dry reforming of toluene as a model tar compound using low-cost iron catalyst for syngas clean-up
Gasification of waste feedstock such as biomass, waste plastics suffers from high tar yields during hydrogen-rich syngas production. The presence of tars result in lower quality syngas, lower syngas yields, reactor blockage, reactor down time, and costly maintenance. Therefore, removal of tar from syngas during gasification is essential. Catalytic reforming of tars via in-situ syngas cleanup is an effective way of mitigating tars. This work explores the possibility of microwave-assisted catalytic dry reforming of tars for syngas production. Further, due to its chemical complexity, toluene, which is one of the main tar constituents, could be used as a model tar compound. Toluene dry reforming was studied using the Fe/Al 2 O 3 catalyst under CO 2 under the temperature range of 400–700 °C. The toluene reforming reaction was conducted using microwave and conventional thermal reactors. Under microwave irradiation, CO 2 and toluene conversions are boosted to 80% at 500 °C. Hydrogen and carbon monoxide yields were approximately five times and ten times higher in the microwave reactor at 500 °C, respectively, compared to the productions obtained in the conventional fixed-bed reactor at 700 °C. Filamentous carbon was also produced as a valuable side product to improve the economy of this process and such value-added carbon was only observed in the microwave reactor. Three reaction pathways were observed during microwave reaction: the toluene decomposition produces an initial hydrogen and carbon deposit on the catalyst; the formation of methane and benzene suggests toluene hydrodemethylation as a secondary reaction; and toluene hydrogenolysis forms light alkanes such as methane, and through reforming reaction under CO 2 to syngas.
Lower temperature curing thermoset polyimides utilizing a substituted norbornene endcap
Methoxycarbonyl bridgehead substituted nadic diacid monomethyl ester, when used as an endcapping monomer, lowered the cure temperature of thermoset PMR polyimides without seriously affecting other desirable properties, such as glass transition temperature and thermal oxidative stability. The C-13 CP/MAS NMR of model compounds was used to follow the cure of resin systems using both the unmodified nadic endcap and the methoxycarbonyl-substituted endcap. Rheological analysis and differential scanning calorimetry DSC also provided evidence for the lower curing nature of the substituted endcap. Two regioisomers of the bridgehead-substituted endcap were isolated, and their chemical structures were elucidated by X-ray crystallography. The model compound and molecular modeling studies conducted ruled out the possibility of regioisomeric imide formation in the substituted endcaps.
Lower-curing-temperature PMR polyimides
Studies were performed to achieve a lower-curing-temperature PMR polyimide. The use of m-aminostyrene as the end-cap instead of the monoalkyl ester of 5-normbornene-2,3 dicarboxylic acid was investigated in typical PMR formulations. Model compound studies were also performed. Differential scanning calorimetry studies were performed on model compounds and neat resins to establish their melting and curing characteristics. The elevated temperature weight loss characteristics of neat resins and graphite fiber composites were determined. The room temperature and short-time 260 C (500 F) mechanical properties of the composites were also determined. The use of m-aminostyrene end-caps reduced the final cure temperature of PMR resins by about 55 C (100 F), but the composites prepared with these resins are limited to use temperatures of about 260 C (500 F).