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At least 253 records · Page 14

Generation and analysis of chemical compound libraries

Various samples are generated on a substrate. The samples each includes or consists of one or more analytes. In some instances, the samples are generated through the use of gels or through vapor deposition techniques. The samples are used in an instrument for screening large numbers of analytes by locating the samples between a working electrode and a counter electrode assembly. The instrument also includes one or more light sources for illuminating each of the samples. The instrument is configured to measure the photocurrent formed through a sample as a result of the illumination of the sample.

36 MATERIALS SCIENCE↗

Inverse Design of Ultralow Lattice Thermal Conductivity Materials via Materials Database Screening of Lone Pair Cation Coordination Environment

The presence of lone pair (LP) electrons is strongly associated with the disruption of lattice heat transport, which is a critical component of strategies to achieve efficient thermoelectric energy conversion. By exploiting an empirical relationship between lattice thermal conductivity, κ L , and the bond angles of pnictogen group LP cation coordination environments, we develop an inverse design strategy based on a materials database screening to identify chalcogenide materials with ultralow κ L for thermoelectrics. Screening the ~635 000 real and hypothetical inorganic crystals of the Open Quantum Materials Database based on the constituent elements, nominal electron counting, LP cation coordination environment, and synthesizability, we identify 189 compounds expected to exhibit ultralow κ L . As a validation, we explicitly compute the lattice dynamical properties of two of the compounds (Cu 2 AgBiPbS 4 and MnTl 2 As 2 S 5 ) using first-principles calculations and successfully find both achieve ultralow κ L values at room temperature of ~0.3-0.4 W/(m·K) corresponding to the amorphous limit. Furthermore, our data-driven approach provides promising candidates for thermoelectric materials and opens new avenues for the design of phononic properties of materials.

36 MATERIALS SCIENCE↗

Inhibitors of Mycobacterium tuberculosis EgtD target both substrate binding sites to limit hercynine production

Ergothioneine (EGT) is a low molecular weight histidine betaine essential in all domains of life but only synthesized by selected few organisms. Synthesis of EGT by Mycobacterium tuberculosis (M. tb) is critical for maintaining bioenergetic homeostasis and protecting the bacterium from alkylating agents, oxidative stress, and anti-tubercular drugs. EgtD, an S-adenosylmethionine-dependent methyltransferase (AdoMet), catalyzes the trimethylation of L-Histidine to initiate EGT biosynthesis and this reaction has been shown to be essential for EGT production in mycobacteria and for long-term infection of murine macrophages by M. tb. In this work, library screening and structure-guided strategies identified multiple classes of M. tb EgtD inhibitors that bind in various regions of the enzyme active site. X-ray crystal structures of EgtD-inhibitor complexes confirm that L-Histidine analogs bind solely to the L-Histidine binding site while drug-like inhibitors, such as TGX-221, and S-Glycyl-H-1152 span both the L-Histidine and AdoMet binding sites. These enzyme-inhibitor complexes provide detailed structural information of compound scaffolds useful for developing more potent inhibitors that could shorten Tuberculosis treatment regimens by weakening important bacterial defenses.

59 BASIC BIOLOGICAL SCIENCES↗

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of first-in-class inhibitors of ASH1L histone methyltransferase with anti-leukemic activity

ASH1L histone methyltransferase plays a crucial role in the pathogenesis of different diseases, including acute leukemia. While ASH1L represents an attractive drug target, developing ASH1L inhibitors is challenging, as the catalytic SET domain adapts an inactive conformation with autoinhibitory loop blocking the access to the active site. Here, by applying fragment-based screening followed by medicinal chemistry and a structure-based design, we developed first-in-class small molecule inhibitors of the ASH1L SET domain. The crystal structures of ASH1L-inhibitor complexes reveal compound binding to the autoinhibitory loop region in the SET domain. When tested in MLL leukemia models, our lead compound, AS-99, blocks cell proliferation, induces apoptosis and differentiation, downregulates MLL fusion target genes, and reduces the leukemia burden in vivo. This work validates the ASH1L SET domain as a druggable target and provides a chemical probe to further study the biological functions of ASH1L as well as to develop therapeutic agents.

60 APPLIED LIFE SCIENCES↗

Screening of bimetallic electrocatalysts for water purification with machine learning

Electrocatalysis provides a potential solution to NO 3 - pollution in wastewater by converting it to innocuous N 2 gas. However, materials with excellent catalytic activity are typically limited to expensive precious metals, hindering their commercial viability. Here, in response to this challenge, we have conducted the most extensive computational search to date for electrocatalysts that can facilitate NO 3 - reduction reaction, starting with 59 390 candidate bimetallic alloys from the Materials Project and Automatic-Flow databases. Using a joint machine learning- and computation-based screening strategy, we evaluated our candidates based on corrosion resistance, catalytic activity, N 2 selectivity, cost, and the ability to synthesize. We found that only 20 materials will satisfy all criteria in our screening strategy, all of which contain varying amounts of Cu. Our proposed list of candidates is consistent with previous materials investigated in the literature, with the exception of Cu–Co and Cu–Ag based compounds that merit further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reformer Fuel Injector

Today's form of jet engine power comes from what is called a gas turbine engine. This engine is on average 14% efficient and emits great quantities of green house gas carbon dioxide and air pollutants, Le. nitrogen oxides and sulfur oxides. The alternate method being researched involves a reformer and a solid oxide fuel cell (SOFC). Reformers are becoming a popular area of research within the industry scale. NASA Glenn Research Center's approach is based on modifying the large aspects of industry reforming processes into a smaller jet fuel reformer. This process must not only be scaled down in size, but also decrease in weight and increase in efficiency. In comparison to today's method, the Jet A fuel reformer will be more efficient as well as reduce the amount of air pollutants discharged. The intent is to develop a 10kW process that can be used to satisfy the needs of commercial jet engines. Presently, commercial jets use Jet-A fuel, which is a kerosene based hydrocarbon fuel. Hydrocarbon fuels cannot be directly fed into a SOFC for the reason that the high temperature causes it to decompose into solid carbon and Hz. A reforming process converts fuel into hydrogen and supplies it to a fuel cell for power, as well as eliminating sulfur compounds. The SOFC produces electricity by converting H2 and CO2. The reformer contains a catalyst which is used to speed up the reaction rate and overall conversion. An outside company will perform a catalyst screening with our baseline Jet-A fuel to determine the most durable catalyst for this application. Our project team is focusing on the overall research of the reforming process. Eventually we will do a component evaluation on the different reformer designs and catalysts. The current status of the project is the completion of buildup in the test rig and check outs on all equipment and electronic signals to our data system. The objective is to test various reformer designs and catalysts in our test rig to determine the most efficient configuration to incorporate into the specific compact jet he1 reformer test rig. Additional information is included in the original extended abstract.

Suder, Jennifer L.↗

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗

Reversible redox chemistry in azobenzene-based organic molecules for high-capacity and long-life nonaqueous redox flow batteries

Redox flow batteries (RFBs), often categorized as aqueous and nonaqueous systems, represent a type of large-scale energy storage technology for renewable energy resources. Redox-active organic molecules have recently drawn extensive interests in RFBs as promising active materials due to their elemental abundance, structural diversity and high tunability of properties, but employing organic molecules in nonaqueous systems is far limited in terms of useable capacity and cycling stability. Here we introduce a class of azobenzene-based organic compounds with the azo group as redox-active center in the p-conjugated structure as new active materials to realize high-performance nonaqueous RFBs with long cycling life and high capacity. By screening suitable organic solvents with high solubility and conductivity, the azobenzene organic molecule was capable to achieve a stable long cycling with a low capacity decay of 0.014% per cycle and 0.16% per day over 1000 cycles. And the stable cycling of electrolytes under a high concentration of 1 M was also realized, delivering a high reversible capacity of ~46 Ah L -1 . The unique lithium-coupled redox chemistry accompanied with a voltage increase was observed and revealed by experimental characterization and theoretical simulation. With the reversible two-electron redox activity of azo group in p-conjugated structures, azobenzene as an azo-aromatic molecule represents a class of promising redox-active organics for potential grid-scale energy storage systems.

25 ENERGY STORAGE↗

Study, selection, and preparation of solid cationic conductors

Crystal chemical principles and transport theory have been used to predict structures and specific compounds which might find application as solid electrolytes in rechargeable high energy and high power density batteries operating at temperatures less than 200 C. Structures with 1-, 2-, and 3-dimensional channels were synthesized and screened by nuclear magnetic resonance, dielectric loss, and conductivity. There is significant conductivity at room temperature in some of the materials but none attain a level that is comparable to beta-alumina. Microwave and fast pulse methods were developed to measure conductivity in powders and in small crystals.

Roth, W. L.↗

QFD analysis of RSRM aqueous cleaners

This paper presents a Quality Function Deployment (QFD) analysis of the final down-selected aqueous cleaners to be used on the Redesigned Solid Rocket Motor (RSRM) program. The new cleaner will replace solvent vapor degreasing. The RSRM Ozone Depleting Compound Elimination program is discontinuing the methyl chloroform vapor degreasing process and replacing it with a spray-in-air aqueous cleaning process. Previously, 15 cleaners were down-selected to two candidates by passing screening tests involving toxicity, flammability, cleaning efficiency, contaminant solubility, corrosion potential, cost, and bond strength. The two down-selected cleaners were further evaluated with more intensive testing and evaluated using QFD techniques to assess suitability for cleaning RSRM case and nozzle surfaces in preparation for adhesive bonding.

Marrs, Roy D.↗

Suspect and Nontarget Screening for Contaminants of Emerging Concern in an Urban Estuary

This study used suspect and nontarget screening with high-resolution mass spectrometry to characterize the occurrence of contaminants of emerging concern (CECs) in the nearshore marine environment of Puget Sound (WA). In total, 87 non-polymeric CECs were identified; those confirmed with reference standards (45) included pharmaceuticals, herbicides, vehicle-related compounds, plasticizers, and flame retardants. Eight polyfluoroalkyl substances were detected; perfluorooctanesulfonic acid (PFOS) concentrations were as high as 72-140 ng/L at one location. Low levels of methamphetamine were detected in 41% of the samples. Transformation products of pesticides were tentatively identified, including two novel transformation products of tebuthiuron. While a hydrodynamic simulation, analytical results, and dilution calculations demonstrated the prevalence of wastewater effluent to nearshore marine environments, the identity and abundance of selected CECs revealed the additional contributions from stormwater and localized urban and industrial sources. For the confirmed CECs, risk quotients were calculated based on concentrations and predicted toxicities, and eight CECs had risk quotients >1. Dilution in the marine estuarine environment lowered the risks of most wastewater-derived CECs, but dilution alone is insufficient to mitigate risks of localized inputs. These findings highlighted the necessity of suspect and nontarget screening and revealed the importance of localized contamination sources in urban marine environments.

Tian, Zhenyu↗

Ab initio calculation of carrier mobility in semiconductors including ionized-impurity scattering

The past decade has seen the emergence of ab initio computational methods for calculating phonon-limited carrier mobilities in semiconductors with predictive accuracy. More realistic calculations ought to take into account additional scattering mechanisms such as, for example, impurity and grain-boundary scattering. Here, in this paper, we investigate the effect of ionized-impurity scattering on the carrier mobility. We model the analytical impurity potential parameterized from first principles by a collection of randomly distributed Coulomb scattering centers, and we include this relaxation channel into the ab initio Boltzmann transport equation, as implemented in the EPW code. We demonstrate this methodology by considering silicon, silicon carbide, and gallium phosphide, for which detailed experimental data are available. Our calculations agree well with experiments over a broad range of temperatures and impurity concentrations. For each compound investigated here, we compare the relative importance of electron-phonon scattering and ionized-impurity scattering, and we critically assess the reliability of Matthiessen's rule. We also show that an accurate description of dielectric screening and carrier effective masses can improve quantitative agreement with experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

The role of toxicology in the Apollo space program

Some of the major considerations are presented which governed the formation and application of the toxicology program employed in support of the Apollo program. The overriding concern of the program was the safety of crews exposed to trace contaminant gases for extended periods of time. The materials screening program employed, in conjunction with a well designed spacecraft environmental control system, helped to attain the goals set forth for the Apollo program. The knowledge gained from working with the toxicity problems and the identification of compounds in the space cabin atmosphere are of importance for continued efforts in manned space flight. Tabular data of spacecraft contaminants are presented.

Wayland J. Rippstein, Jr↗

Toxicity of pyrolysis gases from polyether sulfone

A sample of polyether sulfone was evaluated for toxicity of pyrolysis gases, using the toxicity screening test method developed at the University of San Francisco. Animal response times were relatively short at pyrolysis temperatures of 600 to 800 C, with death occurring within 6 min. The principal toxicant appeared to be a compound other than carbon monoxide.

Hilado, C. J.↗

Database and deep-learning scalability of anharmonic phonon properties by automated brute-force first-principles calculations

Understanding the anharmonic phonon properties of crystal compounds—such as phonon lifetimes and thermal conductivities—is essential for investigating and optimizing their thermal transport behaviors. These properties also impact optical, electronic, and magnetic characteristics through interactions between phonons and other quasiparticles and fields. In this study, we develop an automated first-principles workflow to calculate anharmonic phonon properties and build a comprehensive database encompassing more than 6500 inorganic compounds. Utilizing this dataset, we train a graph neural network model to predict thermal conductivity values and spectra from structural parameters, demonstrating a scaling law in which prediction accuracy improves with increasing training data size. High-throughput screening with the model enables the identification of materials exhibiting extreme thermal conductivities—both high and low. The resulting database offers valuable insights into the anharmonic behavior of phonons, thereby accelerating the design and development of advanced functional materials.

Ohnishi, Masato [University of Tokyo (Japan); Inst↗

Total hydrocarbon analysis by ion mobility spectrometry

Astronauts must be alerted quickly to chemical leaks that compromise their health and the success of their missions. An ideal leak detector would be equally sensitive to all compounds that might constitute a hazard and insensitive to nontoxic compounds. No ideal sensor exists; thus, selection of a methodology is a series of compromises. The commonly used methods are either insensitive at the low exposure levels set by OSHA, NASA, and other organizations or are selectively insensitive to important classes of chemicals such as Freons. After extensive study and experience, the Toxicology Group at JSC has selected ion mobility spectrometry (IMS) for development into a broad range, sensitive detector. In addition to the sensing method, signal processing is important leak detection because a background signal can be expected at all times. The leak-detecting instrument must be programmed to discriminate between authentic leaks and background fluctuations caused by routine operations. The results of an evaluation of the prototype THA is presented in terms related to spacecraft operations. The evaluation included determination of instrumental parameters such as stability and response times. We also included responses to some common components of spacecraft atmospheres in pure form and in binary and ternary mixtures. The output of the four algorithms to the mixtures was found to be noticeably different. These responses are compared on the basis of their utility for signaling a chemical leak. As a means of evaluating its resistance to a falsely positive response, the THA was challenged with carbon dioxide and methane, compounds whose concentrations normally increase in spacecraft air during human habitation. The instrument showed virtually no response to these interferences. Although the prototype THA is designed for space flight, this detector is expected to be useful for field screening at chemical waste dumps and other environmentally sensitive locations.

Cross, John H.↗