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At least 415 records · Page 23

DNA-encoded chemical libraries yield non-covalent and non-peptidic SARS-CoV-2 main protease inhibitors

The development of SARS-CoV-2 main protease (M pro ) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate M pro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of M pro . An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using M pro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of M pro with low nanomolar K i values. Furthermore, these compounds demonstrate efficacy against mutant forms of M pro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Triacetic Acid Lactone and 4-Hydroxycoumarin as Bioprivileged Molecules for the Development of Performance-Advantaged Organic Corrosion Inhibitors

Biomass conversion, especially the development of bioprivileged molecules utilizing integration of biological and chemical processes, has shown potential to produce novel chemicals with enhanced properties. Here, organic corrosion inhibitors based on triacetic acid lactone and 4-hydroxycoumarin have been synthesized in good yield and tested for corrosion inhibition on mild steel in both sulfuric acid and hydrochloric acid. Sixteen novel corrosion inhibitors derived from triacetic acid lactone and 4-hydroxycoumarin were efficiently synthesized and twelve of them showed high corrosion inhibition efficiency as confirmed by electrochemical impedance spectroscopy (giving values greater than 78%) and polarization analysis. While triacetic acid lactone-based compounds showed good corrosion inhibition performance, the 4-hydroxycoumarin-based compounds showed further improvement in corrosion inhibition performance. Scanning electron microscopy (SEM) analysis of the mild steel coupon in the presence of selected inhibitors showed that corrosion was significantly diminished, with complementary X-ray photoelectron spectroscopy (XPS) analysis suggesting the inhibitor molecules strongly adsorbed on the steel surface. Quantum chemical calculations showed poor correlation between calculated parameters and the performance of these molecules. This large set of corrosion inhibitors containing a dozen promising corrosion inhibitors is useful for future rational design of corrosion inhibitors. In conclusion, the results demonstrate a new direction for the development of bioprivileged molecules.

09 BIOMASS FUELS↗

Crystal growth of new high light yield halide perovskite scintillator RbSrI 3

X-ray radiography systems are a key national security technology enabling non-invasive cargo screening. However, the scintillators currently used in these systems have limitations in performance that prompt research for new suitable materials. Here, in this work, crystal growth, physical properties, and optical and scintillation properties of a new halide perovskite scintillator RbSrI 3 were investigated for the first time. The melting point was determined to be 453 °C. Divalent europium and ytterbium were investigated as potential luminescent activators. Light yield and energy resolution of RbSrI 3 :Eu 5 mol% was 78,700 ph/MeV and 2.8 % at 662 keV, and that of RbSrI 3 :Yb 0.5 mol% was 24,000 ph/MeV and 4.9 % at 662 keV.

36 MATERIALS SCIENCE↗

High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds

Abstract Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

High-throughput characterization of Lu-doped zirconia

Lu-doped zirconia (LuDZ) was reported in the 1960s to be a poor oxygen ion conductor. However, we identified this system as worthy of reexamination based on the results of a machine learning-based screen for promising oxygen ion conductors, further supported by a physical argument: because Lu is the heaviest and smallest of the lanthanides, it should offer the possibility of high conductivity due to its high polarizability and size compatibility with the zirconia structure. Here the relationship between dopant concentration and conductivity in the LuDZ system was determined using a high throughput experimental methodology in which spatially resolved conductivity was measured across a compositionally graded film, spanning from Zr 0.93 Lu 0.07 O 1.965 to Zr 0.82 Lu 0.18 O 1.91 . The conductivity broadly peaks with composition at 15 cation % Lu, coinciding with the approximate phase boundary of the fully stabilized cubic phase. The composition-dependent conductivity measurements reveal a surprising increase in activation energy for ion transport with increasing Lu content with no change in this trend at the composition of the conductivity maximum. The pre-exponential factor increases sharply with Lu content, but displays a distinct plateau once the conductivity maximum composition is attained. At 500 °C, the conductivity of Zr 0.85 Lu 0.15 O 1.925 is 2 × 10 –3 S cm –1 , approaching that of optimally doped Sc-stabilized zirconia, which has the highest reported conductivity among zirconia compounds. In comparison to other oxide ion conductors, Lu-stabilized zirconia offers the advantage over ceria of negligible electronic conductivity and is easier to process than (La,Sr)(Ga,Mg)O 3-δ .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗

Regulatory and Technical Issues Concerning the Detection and Treatment of NDMA-Contaminated Groundwater at NASA WSTF

The National Aeronautics and Space Administration (NASA) White Sands Test Facility (WSTF) was established in 1963 primarily to provide rocket engine testing services for several NASA programs. The groundwater underlying the site has been contaminated as a result of historical operations. Groundwater contaminants include several volatile organic compounds (VOCs) and two semi-volatile compounds: N-nitrosodimethylamine (NDMA) and N-nitrodimethylamine (DMN). This paper discusses some of the technical, analytical, regulatory, and health risk issues associated with the contaminant plume. The plume has moved approximately 2.5 miles downgradient of the facility industrial boundary, with evidence of continued migration. As a result, NASA has proposed a pump and treat system using air strippers and ultraviolet (UV) oxidation to stabilize future movement of the contaminant plume. The system has been designed to treat 1,076 gallons (4,073 liters) per minute, with provisions for future expansion. The UV oxidation process was selected to treat NDMA-contaminated groundwater based on successes at other NDMA-contaminated sites. Bench- and pilot-scale testing of WSTF groundwater confirmed the ability of UV oxidation to destroy NDMA and generated sufficient data to design the proposed full-scale treatment system. NDMA is acutely toxic and is a probable human carcinogen. EPA-recommended health risk criteria for the residential consumption of NDMA/DMN-contaminated groundwater was used to determine that a 1.0 x 10(exp -6) excess cancer risk corresponds to 1.7 parts per trillion (ppt). EPA analytical methods are unable to detect NDMA and DMN in the low ppt range. EPA's current Appendix IX analytical method used to screen for NDMA, Method 8270, can detect NDMA only at levels that are orders of magnitude greater than the recommended health risk level. Additionally, EPA Method 607, the most sensitive EPA approved method, has a detection limit of 150 ppt. This corresponds to an excess cancer risk of 9.0 x 10(exp -5), which exceeds the State of New Mexico's water quality standard of a cancer risk less than 1 x 10(exp -5). The treatment system has been engineered to treat contaminated groundwater to levels significantly below the New Mexico standard. However, the inability of EPA-approved analytical methods to detect NDMA and DMN at low ppt levels, and to provide verification of compliance with the 1 x 10(exp -5) cancer risk, introduces a notable risk to the long-term operation of the system. WSTF has been working with Southwest Research Institute to develop a non-EPA analytical method that can achieve a reporting limit of 1 ppt, which corresponds to an excess cancer risk of 7.6 x 10(exp -7). WSTF is currently developing a proposal to obtain approval from the New Mexico Environment Department (NMED) of this non-EPA method.

Wiebe, D. T.↗

Wilson Corners SWMU 001 2015 Annual Long Term Monitoring Report Kennedy Space Center, Florida

This document presents the findings of the 2015 Long Term Monitoring (LTM) that was completed at the Wilson Corners site, located at the National Aeronautics and Space Administration John F. Kennedy Space Center, Florida. The objectives of the 2015 LTM event were to evaluate the groundwater flow direction and gradient, to monitor the vertical and horizontal extent of the volatile organic compounds (VOCs; including the upgradient and sidegradient extents, which are monitored every five years), and to monitor select locations internal to the dissolved groundwater plume. The 2015 LTM event included several upgradient and sidegradient monitoring wells that are not sampled annually to verify the extent of VOCs in this portion of the site. The December 2015 LTM groundwater sampling event included, depth to groundwater measurements, 40 VOC samples collected using passive diffusion bags, and one VOC sample collected using low-flow techniques. Additionally, monitoring well MW0052DD was overdrilled and abandoned using rotasonic drilling techniques. The following conclusions can be made based on the 2015 LTM results: groundwater flow is generally to the west with northwest and southwest flow components from the water table to approximately 55 feet below land surface (ft BLS); peripheral monitoring wells generally delineate VOCs to groundwater cleanup target levels (GCTLs) except for monitoring wells MW0088, MW0090, MW0095, and NPSHMW0039, which had vinyl chloride (VC) concentrations near the GCTL and MW0062, which had trichloroethene (TCE), cis-1,2-dichloroethenen (cDCE), and VC concentrations above natural attenuation default concentrations (NADCs); VOCs in interior downgradient wells generally fluctuate within historic ranges except for monitoring wells in the north-northwest portion of the site, which have increasing VC concentrations indicating potential plume migration and expansion; Historically, the vertical extents of the VOCs were delineated by monitoring wells screened greater than 60 ft BLS (MW0083 through MW0086, and MW0078). The 2015 LTM results indicate that concentrations of daughter product cDCE is greater than the NADC in MW0078 and that cDCE and VC are greater than NADCs in MW0130. TCE was greater than the GCTL in monitoring well MW130 and not detected above method detection limits (9 micrograms per Liter) in monitoring well MW0078. No GCTL exceedances were identified in monitoring wells MW0083 or MW0086; the dissolved plume footprint appears generally stable, though not fully delineated by monitoring well data in the northeast portion of the site; and 2015 LTM results generally support the existing Conceptual Site Model. Geosyntec recommends modifying the LTM program, collecting a verification sample from monitoring well MW0062, and performing a direct push technology instigation in the northnortheastern portion of the site. A cluster of monitoring wells (MW0132 [2 to 12 ft BLS], MW0133 [15 to 25 ft BLS], and MW0134 [29 to 34 ft BLS]) is proposed to delineate impacts in the northnortheast portion of the site. Geosyntec recommends installation of a vertical extent well in the center of the site (Hot Spot 2 area) post-remediation implementation.

groundwater↗

Non-Contact Vapor Detection of Illicit Drugs via Atmospheric Flow Tube-Mass Spectrometry

Real-time, non-contact detection of illicit drugs is a desirable goal for the interdiction of these controlled substances, but the relatively low vapor pressures of such species present a challenge for trace vapor detection technologies. The introduction of atmospheric flow tube-mass spectrometry (AFT-MS), which has previously been demonstrated to detect gas-phase analytes at low parts-per-quadrillion levels for explosives and organophosphorus compounds, also enables the potential for non-contact drug detection. With AFT-MS, direct vapor detection of cocaine and methamphetamine from ~5 µg residues at room temperature is demonstrated herein. Furthermore, thermal desorption of low- to sub-picogram levels of cocaine, methamphetamine, fentanyl, and heroin is observed via AFT-MS using a carrier flow rate of several L/min of air. These low levels can permit non-contact sampling through collection of vapor, effectively preconcentrating the analyte before desorption and analysis. Quantitative evaluation of the thermal desorption approach has yielded limits of detection (LODs) on order of 10 fg for cocaine and fentanyl, 100 fg for methamphetamine, and 1.6 pg for heroin. The LOD for heroin was lowered to 200 fg by using tributyl phosphate as a dopant to form a proton-bound heterodimer with heroin. When used with AFT-MS, the intentional formation of specific drug-dopant adducts has the potential to enhance detection limits and selectivity of additional drug species. Species that are prone to form adducts present a challenge to analysis, but that difficulty can be overcome by the intentional addition of a dopant. Molecules unlikely to form adducts will remain essentially unimpacted, but the adduct-forming species will interact with the dopant to compress the analyte signal into a single peak. This approach would be valuable in the application of non-contact screening for illicit substances via vapor collection followed by thermal desorption for analysis.

methamphetamine, cocaine, heroin, fentanyl, atmosp↗

The Ability of AMSTAR Dechlorination Solution to Remove and Degrade PCBs from Contaminated Surfaces

Polychlorinated biphenyls (PCBs) are a group of synthetic aromatic compounds with the general formula C12H(10-x)Cl(-x) that were historically used in industrial paints, caulking material and adhesives, as their properties enhanced structural integrity, reduced flammability and boosted antifungal properties. Although the United States Environmental Protection Agency (USEPA) has banned the manufacture of PCBs since 1979, they have been found in at least 500 of the 1,598 National Priorities List (Superfund) sites identified by the USEPA. Prior to the US EPA's ban on PCB production, PCBs were commonly used as additives in paints and asphalt-based adhesives that were subsequently applied to a variety of structures. Government facilities constructed as early as 1930 utilized PCB-containing binders or PCB-containing paints, which are now leaching into the environment and posing ecological and worker health concerns. In 2006, a commercially available product known as AMSTAR Dechlorination Solution was tested at NASA's Kennedy Space Center for its ability to remove and degrade PCBs from structural materials. This evaluation was requested by the Environmental Security Technology Certification Program (ESTCP) evaluating the ability of NASA's Bimetallic Treatment System (BTS) to remove and degrade PCBs from structural materials. The results of the laboratory testing are to be used to determine if a side-by-side field-scale test comparing BTS to AMSTAR was warranted. A recommended sampling and analysis testing program was submitted to ESTCP that included triplicate screening of AMSTAR's PCB dechlorination capabilities on a variety of surfaces including glass, bare metal, and painted metal coupons. The test procedures, analytical techniques and results obtained are presented in this interim report to ESTCP.

Quinn, Jacqueline E.↗

Technical Background and Validation Report on the Residential Water Inhalation Risk Calculator Presented in the Risk Assessment Information System

Indoor air quality (IAQ) is critical for human health. Poor IAQ is linked to respiratory issues, cardiovascular diseases, and cancer. Indoor pollutants are emitted by typical household items such as cleaning products, personal care items, building materials, and tap water - an understudied volatile organic compound (VOC) source. This document presents the Residential Water Inhalation Risk Calculator (RWIRC), which estimates daily VOC exposure concentrations from various household water uses, such as showering and dishwashing, to assess exposure risks for the most vulnerable occupant. Integrated into the Risk Assessment Information System (RAIS) and sponsored by the US Department of Energy (DOE), the calculator divides a house into three compartments: shower, bathroom, and other spaces, accounting for daily water usage patterns and calculating VOC concentrations. Exposure data generated using the calculator can assist health assessors in estimating excess lifetime cancer risk (ELCR) and hazard index (HI) from VOC inhalation. Unlike traditional exposure models that utilize Andelman’s constant, the RWIRC continuously assesses variability in VOC concentrations and environmental conditions using differential equations to track VOC concentrations and air exchange between compartments. The calculator also provides unique volatilization fractions for each chemical and appliance, enhancing accuracy of the exposure concentration estimation. The RWIRC is accessible online and allows users to customize parameters (i.e., number of bathrooms, water temperature, and exhaust fan conditions) and input VOC characteristics (i.e., tap water and ambient air concentrations). This document provides a step-by-step guide on implementing the calculator. It also provides comparisons with the ATSDR-SHOWER calculator, using eight VOCs with varying physicochemical properties to reveal differences in algorithms and output concentrations. Simulations also assess how bathroom door positions and exhaust fan usage affect VOC exposure. The calculator results can enhance EPA risk screening levels for inhalation exposure to VOCs from tap water, offering a sophisticated tool for assessing inhalation risks and improving public health protection.

54 ENVIRONMENTAL SCIENCES↗

High-dimensional isotomics, part 2: Observations of over 100 constraints on methionine's isotome

The abundances of different isotopic forms of a compound, or isotopologues, will vary based on its physical and chemical history. The number of isotopologues increases combinatorically with the size of a molecule, and even small molecules such as amino acids have thousands of potentially observable isotopic variants. However, due to the analytical challenges of separating and observing isotopologues, only a few dimensions of isotopic diversity are routinely measured. Overcoming these challenges requires both an experimental method to observe many isotopic properties and a theoretical framework for interpreting these experiments. In Part 1, we presented such a theoretical framework; here, we demonstrate an experimental method, which we apply to methionine. Our approach uses a Q Exactive HF Orbitrap to perform several “M + N experiments”, where a sample is ionized, a subset of its isotopologues with cardinal mass N daltons greater than the unsubstituted isotopologue is selected and fragmented, and the proportions of all detectable isotopic forms of those fragment ions are quantified. We perform M + 1, M + 2, M + 3, and M + 4 experiments of a methionine sample and standard where the sample has a 100 ‰ enrichment of 13C at the methyl carbon relative to the natural 13C abundance at that position in the standard, and is otherwise identical to the standard. We observe isotopic forms of 8 fragment ion species for each version of the M + N experiment. With the assistance of a forward model of expected mass spectra, we identify isotopic peaks for each fragment ion based on observed mass and abundance, screen these for data quality, and quantify abundances for 146 unique isotopic peaks at precisions of ≈ 0.3–3 ‰. We present our direct observations and use them to reconstruct the concentrations of 19 individual singly, doubly, and triply-substituted isotopologues; doing so gives fewer constraints and broader error bars than working with the direct observations, but may be more interpretable for some applications. We also examine possibilities for measuring additional peaks, which are primarily limited by the detection limit of the Orbitrap-IRMS method. We then suggest some possible uses of our direct measurements for chemical forensics and hypothesis testing. Furthermore, our results demonstrate the diversity of isotopic constraints currently observable and interpretable for organic molecules.

58 GEOSCIENCES↗

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

60 APPLIED LIFE SCIENCES↗

Radiation Protection Using Carbon Nanotube Derivatives

BHA and BHT are well-known food preservatives that are excellent radical scavengers. These compounds, attached to single-walled carbon nanotubes (SWNTs), could serve as excellent radical traps. The amino-BHT groups can be associated with SWNTs that have carbolyxic acid groups via acid-base association or via covalent association. The material can be used as a means of radiation protection or cellular stress mitigation via a sequence of quenching radical species using nano-engineered scaffolds of SWNTs and their derivatives. It works by reducing the number of free radicals within or nearby a cell, tissue, organ, or living organism. This reduces the risk of damage to DNA and other cellular components that can lead to chronic and/or acute pathologies, including (but not limited to) cancer, cardiovascular disease, immuno-suppression, and disorders of the central nervous system. These derivatives can show an unusually high scavenging ability, which could prove efficacious in protecting living systems from radical-induced decay. This technique could be used to protect healthy cells in a living biological system from the effects of radiation therapy. It could also be used as a prophylactic or antidote for radiation exposure due to accidental, terrorist, or wartime use of radiation- containing weapons; high-altitude or space travel (where radiation exposure is generally higher than desired); or in any scenario where exposure to radiation is expected or anticipated. This invention s ultimate use will be dependent on the utility in an overall biological system where many levels of toxicity have to be evaluated. This can only be assessed at a later stage. In vitro toxicity will first be assessed, followed by in vivo non-mammalian screening in zebra fish for toxicity and therapeutic efficacy.

Conyers, Jodie L., Jr.↗

Identification of Known and Novel Monomers for Poly(hydroxyurethanes) from Biobased Materials

Sourcing polymers from biobased materials is desirable for a transition to a more sustainable world. However, finding new monomers sourced from biobased molecules requires extensive experimental effort, due to the fact that most biomolecules lack the functional groups or properties needed to serve as a monomer in a particular polymeric system without chemical modification. In this work, we demonstrate a computational screening method to obtain monomers of a non-isocyanate polyurethane (NIPU), polyhydroxyurethane (PHU), from biomolecules. Our method generates candidate monomers from a list of 15 selected biobased starting molecules by performing chemical transformations that are standard to chemical catalysis and organic synthesis on these starting molecules and then screening the results for molecules with moieties that can be used as monomers for a PHU. Product molecules from two generations of reaction, a total number of 20,057, were analyzed automatically to identify molecules that have two or more epoxy or cyclic carbonate functional groups as candidates for further derivatization. These 21 candidate molecules were then subjected to another two generations of reaction, producing a set of 17,913 additional molecules. Further scrutiny of this set for desired functional groups characterizing PHUs and querying against the PubChem database was carried out, and 15 known molecules that are commercially available were identified, with the desirable features that they are predicted to be derived from biobased starting molecules in four or fewer steps. Moreover, molecule space generated from this process was primarily comprised of molecules that were not known to PubChem, indicating the framework also has the ability to generate novel candidate monomers that originate from biobased starting points.

36 MATERIALS SCIENCE↗

Machine Learning-Driven Solvent Screening for Biobased 2,3-Butanediol Extraction

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method not only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.

Extraction↗

Plant Responses to Increased UV-B Radiation: A Research Project

Ozone decrease implies more ultraviolet-B (UV-B) radiation reaching the surface of the Earth. Increased UV-B radiation triggers responses by living organisms. Despite the large potential impacts on vegetation, little is known about UV-B effects on terrestrial ecosystems. Long-term ecological studies are needed to quantify the effects of increased UV radiation on terrestrial ecosystems, asses the risks, and produce reliable data for prediction. Screening pigments are part of one of the protective mechanism in plants. Higher concentrations of screening pigments in leaves may be interpreted as a response to increased UV radiation. If the screening effect is not sufficient, important molecules will be disturbed by incoming radiation. Thus, genetics, photosynthesis, growth, plant and leaf shape and size, and pollen grains may be affected. This will have an impact on ecosystem dynamics, structure and productivity. It is necessary to monitor selected terrestrial ecosystems to permit detection and interpretation of changes attributable to global climate change and depleted ozone shield. The objectives of this project are: (1) To identify and measure indicators of the effects of increased solar UV-B radiation on terrestrial plants; (2) to select indicators with the greatest responses to UV-B exposure; (3) to test, adapt or create ecosystem models that use the information gathered by this project for prediction and to enhance our understanding of the effects of increased UV-B radiation on terrestrial ecosystems. As a first step to achieve these objectives we propose a three-year study of forest and steppe vegetation on the North slope of the Brooks Range (within the Arctic circle, in Alaska), in the Saguaro National Monument (near Tucson, Arizona) and in the forests and steppes of Patagonia (Argentina). We selected (1) vegetation north of the Polar Circle because at 70N there is 8% risk of plant damage due to increased UV-B radiation; (2) the foothills of Catalina Mountains because there is anecdotal evidence of plant damage on the saguaros that has been linked to increased UV radiation, and (3) the forests of Nothofagus spp. and the steppe of Patagonia where the risk of plant damage at 35S is 5% and increases to as much as 15% at 55S due to increased UV-B radiation. Measurements of UV-B radiation impinging on the surface at 55S largely exceed the predicted UV-B radiation values at 50 latitude and 0% ozone depletion. Preliminary HPLC analyses of UV-B absorbing compounds in Nothofagus antartica, N. pumilio, N. betuloides and Rumex sp. in natural conditions show species-specific patterns. The spectrum of N. antartica grown at 38S differs significantly from that of N. antartica in natural conditions in Ushuaia (55S). These results suggest that the selected main area (Patagonia) is appropriate for assessing the problem and its magnitude and that Nothofagus is appropriate for our study.

DAntoni, H. L.↗