Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “SCREEN”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Identification of a Class of WNK Isoform-Specific Inhibitors Through High-Throughput Screening

Introduction: WNK [with no lysine (K)] kinases are serine/threonine kinases associated with familial hyperkalemic hypertension (FHHt). WNKs are therapeutic targets for blood pressure regulation, stroke and several cancers including triple negative breast cancer and glioblastoma. Here, we searched for and characterized novel WNK kinase inhibitors. Methods: We used a ~210,000-compound library in a high-throughput screen, re-acquisition and assay, commercial specificity screens and crystallography to identify WNK-isoform-selective inhibitors. Results: We identified five classes of compounds that inhibit the kinase activity of WNK1: quinoline compounds, halo-sulfones, cyclopropane-containing thiazoles, piperazine-containing compounds, and nitrophenol-derived compounds. The compounds are strongly pan-WNK selective, inhibiting all four WNK isoforms. A class of quinoline compounds was identified that further shows selectivity among the WNK isoforms, being more potent toward WNK3 than WNK1. The crystal structure of the quinoline-derived SW120619 bound to the kinase domain of WNK3 reveals active site binding, and comparison to the WNK1 structure reveals the potential origin of isoform specificity. Discussion: The newly discovered classes of compounds may be starting points for generating pharmacological tools and potential drugs treating hypertension and cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Misr: Miniature Ignition Screening Rapid Compression Machine for Kinetic Measurements of Novel Fuels (Final Report)

High throughput ignition screening would be useful for evaluating fuels before scaled production. One method for doing this involves generating a map of ignition delay times over different conditions for each fuel blend. Constant condition ignition delay time maps can be used to estimate ignition for engines in prescribed thermodynamic trajectories. A Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC) intending to generate those constant condition ignition delay time maps for low temperature chemistry relevant conditions. Some design features include a bellows-actuated driver section, which is lighter compared to other RCM designs, an adjustable brake section, and full optical access. The setup was designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions were meant to be relevant to low-to-intermediate temperature auto-ignition and for generation of data for developing relevant chemical kinetics models or ignition maps. Because of the compression characteristics and the heat loss characteristics of the MISR, the apparatus currently tests higher temperatures over shorter test times than what would be desirable, however there are some pathways to improved compression characteristics as detailed in this report. A detailed description of the MISR design and its operating mechanism is discussed. The team faced several challenges and setbacks in the construction and commissioning of the MISR, and those are highlighted, along with the modifications that were performed to get the MISR operational. To demonstrate the performance characteristics of the MISR, limited ignition delay experiments were conducted for ethanol fuel at different equivalence ratios (Φ), and those results were usable, but again test a higher temperature and shorter ignition delay time than initially intended.

02 PETROLEUM↗
DOE OSTI2021

Case Study of High-Throughput Drug Screening and Remote Data Collection for SARS-CoV-2 Main Protease by Using Serial Femtosecond X-ray Crystallography

Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in silico drug screening studies have been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with nine drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

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↗
DOE OSTI2021

Application of the Screened Hydrogenic Model to Light Atoms

The purpose of this work was to develop a Screened Hydrogenic Model (SHM) to accurately calculate the electron energies for light atoms and ions with up to ten electrons for atomic numbers up to 18. The total energy of an atom or ion was calculated with effective nuclear charges and screening parameters for each electron type (1s, 2s and 2p) within a specific electron configuration. Multiple energy states, centered at the total energy, were calculated for elec-tron configurations that have Russell Saunders coupling. The energy of each electron included its relativistic energy, EREL, but close overall agreement between the calculated and experimental energies of multi-electron configura-tions required that the one-electron expression for EREL be modified in a simple manner. In the present work, 98% of the 587 calculated energies for light atoms/ions have a relative error within ±0.1% of the corresponding experimental energies. The effective nuclear charges described in this work allow hydrogen-like wave functions to be defined for the electrons within a multi-electron configuration. The SHM, described in this work, is available for future calculations involving light atoms and ions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Screening of Potential Biomass-Derived Streams as Fuel Blendstocks for Mixing Controlled Compression Ignition Combustion

Mixing controlled compression ignition or diesel engines are highly efficient and are likely to continue to be the primary means for movement of goods for many years to come. Low-carbon biofuels have the potential to significantly reduce the carbon footprint of diesel combustion and could potentially have advantageous properties for combustion such as high cetane number and reduced engine out particle emissions. In this study, we developed a list of potential biomass-derived diesel blendstocks. An online database of properties and characteristics of these bioblendstocks was populated with data. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a bioblendstock met the basic requirements for handling in the diesel distribution system and use as a blend with conventional diesel. Criteria included cetane number =40, flashpoint =52 degrees C, and boiling point or final boiling point <338 degrees C. Blendstocks needed to be soluble in diesel fuel, have a toxicity no worse than conventional diesel, and not be corrosive. Additionally, cloud point or freezing point below 0 degrees C was required. This screening produced a list of 27 potential bioblendstocks. Of these candidates, 13 were available commercially or could be synthesized by biofuels production researchers and included 11 nominally pure components and two mixtures. These 13 candidates were then subjected to further study based on how they impact fuel properties upon blending. Blend properties included cetane number, lubricity, conductivity, oxidation stability and viscosity. Results indicate that all thirteen candidates can meet the basic requirements for diesel fuel blending and are likely to reduce particle emissions from diesel combustion.

09 BIOMASS FUELS↗
DOE OSTI2022

Transmission Constraint Screening for Production Cost Modeling at Scale

Transmission constraint calculation and screening, for both unit commitment and economic dispatch, is a critical feature of a performant solution method, but one that is often overlooked in the literature. In this talk, we will discuss the transmission constraint calculation and screening algorithm implemented in the open-source Egret package for electrical grid optimization and compare it against the more straightforward approach Egret originally implemented. Finally, we discuss the implications for transmission constraint sharing within a production cost modeling simulation.

DCOPF↗
DOE OSTI2024

Screen-Printed Complex Ag Inks for Si HJT Metallization

Metallization using reactive metal inks has recently attracted significant research interest due to its advantages in cost of materials and manufacturing, while still achieving performance comparable to traditional fire-through particle pastes. Here, we present for the first time the use of reactive silver (Ag) inks via industrial screen-printing and inkjet printing methods for the metallization of different Si surfaces used in tunneling oxide passivating contacts (TOPCon) and Silicon heterojunction (SHJ) solar cells. Printed Ag lines exhibit a conductivity of ~5 Mu O·cm, which is approximately 3 times that of bulk Ag (1.59 µO·cm). The printed metal has a thickness of ~0.5-1.5 Mu m, an order of magnitude smaller than the current fire-through metal finger thickness (~15 Mu m). Contact resistivity measurements of the screen-printed and inkjet-printed samples on a transparent conducting oxide (TCO) surface show a very low value of ~0.2-12 mO·cm 2. Photoluminescence images of the metallized samples demonstrate minimal surface passivation degradation compared to the non-metallized areas (?iVoc <3.5 mV). Scanning electron microscopy images (SEM) reveal the structure of the printed metals on the Si surfaces as porous but much denser than fire-through Ag by nanoparticle paste. In the final presentation, we will showcase our results of printing these reactive Ag inks on high-efficiency heterojunction and TOPCon solar cells with full-area M6 wafers. Additionally, the adhesion of these reactive Ag inks on different Si surfaces according to ASTM D3359-17, as well as the performance of solar cells after standard IEC 61215 freeze/thaw and damp heat tests, will be presented. These new metal inks show promising potential as an alternative to the currently dominant particle-based pastes, offering lower Ag consumption and lower processing temperatures without compromising performance.

heterojunction solar cells↗
DOE OSTI2023

Design, Fabrication, and Screening of Environmental‐Thermal Barrier Coatings Prepared by Ultrafast High‐Temperature Sintering

Abstract The demand for more efficient gas turbines relies heavily on the development of new environmental‐thermal barrier coatings (ETBCs). However, there is still uncertainty about which alloys and composites will be used for the next generation of turbine blades, as well as the most promising coating materials. Herein, an ETBCs development strategy is presented by integrating the coating design, synthesis, and screening using an ultrafast high temperature sintering (UHS) technique to accelerate coating improvements. The initial basis for composition selection is their thermal expansion mismatch with the substrate alloys; for which a temperature‐dependent coefficient of thermal expansion database is created. By combining tape casting method with the UHS technique a high‐throughput synthesis of single and multi‐layer coatings are realized with different compositions, layer stacking sequences, and layer thicknesses. To evaluate the coatings, thermal cycling tests from room temperature to 1300 °C are conducted. The approach enabled coatings on objects with complex geometries, multi‐layer ETBCs, and porosity tailoring by using staged UHS that runs with different temperatures and durations. The fast iteration strategy is more cost‐effective for the screening of ETBCs compared to conventional methods and greater throughput which can be further extended for rapid optimization of other materials systems.

Xie, Hua↗
DOE OSTI2020

Time‐Dependent Density Functional Theory of Narrow Band Gap Semiconductors Using a Screened Range‐Separated Hybrid Functional

Abstract Predicting the band structure and optical absorption spectra of narrow band gap semiconductors is challenging for electronic structure methods. Here, it is shown shown that density functional theory can yield accurate band structures and time‐dependent density functional theory (TDDFT) can yield accurate optical absorption spectra for these systems. This is achieved by using a screened range‐separated hybrid (SRSH) functional with a single empirical parameter, fit to reproduce the experimental band gap. By comparing TDDFT results based on the SRSH approach with those obtained based on the Heyd–Scuseria–Ernzerhof functional it is shown that screened long‐range exact exchange improves the accuracy of the TDDFT spectra for these systems.

Wing, Dahvyd↗
DOE OSTI2025

Screening and Development of Sacrificial Cathode Additives for Lithium‐Ion Batteries

Abstract This work presents a computational screening approach to identify Li‐rich transition‐metal oxide sacrificial cathode additives and provides experimental validation of antifluorite‐structured Li 6 MnO 4 as a potential candidate. Initial attempts to synthesize this compound result in low purity (≤40% by weight) owing to close thermodynamic competition with Li 2 O and MnO at low temperature. However, it is shown that a much higher purity of 85% by weight can be achieved by combining Li excess with rapid cooling from high temperature, which effectively stabilizes the Li 6 MnO 4 phase. The synthesized product delivers a high irreversible Li release capacity that exceeds 700 mAh g −1 by utilizing combined Mn oxidation (Mn 2+/3+ and Mn 3+/4+ ) and O oxidation. These results demonstrate that Li 6 MnO 4 may therefore be useful as a potential sacrificial cathode additive in Li‐ion batteries and motivate further investigation of other structurally‐related compounds. While attempts were made to synthesize two additional compounds among computationally screened candidates, it was not successful to experimentally realize the two candidates. The difficulty of experimental realization of the newly predicted materials remains a challenge and it is suggested that more efforts need to be devoted to developing computational techniques to precisely predict synthesizability and propose potential synthetic routes of the predicted materials.

Kim, Haegyeom↗
DOE OSTI2022

How much have adverse occupational health outcomes among construction workers improved over time? Evidence from 25 years of medical screening

Background Construction workers have always had a high risk of occupational illnesses. We used 25 years of data from a medical screening program serving older construction workers to determine how much health outcomes have improved over the past 60 years. Methods We investigated changes in relative risk for chest radiographs consistent with pneumoconiosis, COPD by spirometry, lung cancer mortality, and audiometry-assessed hearing impairment among workers participating in a medical screening program. Results were stratified by decade of first construction employment: before 1960, 1960–1969, 1970–1979, 1980–1989, and after 1990. Poisson and Cox regression analyses assessed relative risk by decade adjusted for age, sex, smoking, and years of construction trade work. Results Subjects were 94% male and, on average, 60 years old with 25 years of construction work. When compared to workers employed before 1960, those first employed after 1990 experienced the following reductions in model-adjusted relative risks: chronic obstructive pulmonary disease, 32%; all pneumoconiosis, 68%; parenchymal abnormalities, 35%; pleural abnormalities, 71%; hearing impairment, 20%; and lung cancer mortality, 48%. Risks started to decline in the 1960s with greatest reductions among workers first employed after 1970. Conclusions This study demonstrates the positive impact that adoption of occupational health protections have had over the past 60 years. The greatest risk reductions were observed for outcomes with strong regulatory and legal incentives to reduce exposures and associated risks, such as those associated with inhalation hazards (asbestos and silica), while lowest improvement was for hearing impairment, for which little regulatory enforcement and few prevention incentives have been adopted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Screening a knowledge‐based library of low molecular weight compounds against the proline biosynthetic enzyme 1‐pyrroline‐5‐carboxylate 1 ( PYCR1)

Abstract Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H‐dependent reduction of Δ 1 ‐pyrroline‐5‐carboxylate toL‐proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of thePYCR1gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X‐ray crystallography and kinetic assays to determine affinity parameters. The library was counter‐screened against human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)‐tetrahydro‐2H‐pyran‐2‐carboxylic acid (70 μM) has higher affinity than the current best tool compoundN‐formyl‐l‐proline, is 30 times more specific for PYCR1 over human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure‐affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1‐hydroxyethane‐1‐sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed withl‐pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Screening for anticancer properties of thiazolidinedione compounds in a galactose media metastatic breast cancer cell model

The metastatic tumors of breast cancer lead to the mortality of patients in part due to the failure of chemotherapeutics to reach the brain and emergence of drug resistance. With the increase in drug resistance, we focused on targeting mitochondrial metabolism, which was recently found to be a viable and novel drug target in breast cancer. Here we screened several ligands for anticancer activity in a phenotypic screen using the MTT dye as a marker for cell proliferation. MCF-7 breast cancer cells were treated with compounds in the presence of galactose to ensure mitochondrial interaction by the compounds. The lead compound of our group, NL-1, a thiazolidinedione (TZD), was found to inhibit cell proliferation with an IC{sub 50} of 7.1 μM, whereas its unsaturated derivative CI-987 was more potent with a IC{sub 50} of 3.3 μM. The TZDs were affected by substitution on both the aromatic ring and the TZD warhead. Taken together, these compounds can serve as lead structures for mitochondrial targeted drug discovery programs in breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

High-throughput screening of environmental polysaccharide-degrading bacteria using biomass containment and complex insoluble substrates

Abstract Carbohydrate degradation by microbes plays an important role in global nutrient cycling, human nutrition, and biotechnological applications. Studies that focus on the degradation of complex recalcitrant polysaccharides are challenging because of the insolubility of these substrates as found in their natural contexts. Specifically, current methods to examine carbohydrate-based biomass degradation using bacterial strains or purified enzymes are not compatible with high-throughput screening using complex insoluble materials. In this report, we developed a small 3D printed filter device that fits inside a microplate well that allows for the free movement of bacterial cells, media, and enzymes while containing insoluble biomass. These devices do not interfere with standard microplate readers and can be used for both short- (24–48 h) and long-duration (> 100 h) experiments using complex insoluble substrates. These devices were used to quantitatively screen in a high-throughput manner environmental isolates for their ability to grow using lignocellulose or rice grains as a sole nutrient source. Additionally, we determined that the microplate-based containment devices are compatible with existing enzymatic assays to measure activity against insoluble biomass. Overall, these microplate containment devices provide a platform to study the degradation of complex insoluble materials in a high-throughput manner and have the potential to help uncover ecologically important aspects of bacterial metabolism as well as to accelerate biotechnological innovation.

3D printing↗
DOE OSTI2025

Sample screening of uranium ore concentrates using portable spectrophotometers: investigating the correlation between visible colors and chemical signatures

A research collaboration between the Japan Atomic Energy Agency and the Department of Energy’s National Nuclear Security Administration examined nuclear forensic signatures and analytical methods for tracing the origins of uranium ore concentrates (UOCs). Here, this study focuses on utilizing portable spectrophotometers capable of reflectance measurements in the visible light spectrum as a potential rapid screening tool for nuclear forensics analysis. Unlike laboratory-based near-infrared spectroscopy or digital image analysis, this research investigated the potential to correlate visible color measurements with key nuclear forensics signatures using seven types of UOC samples with known origins and three UOC certified reference materials. Results demonstrated that distinct color groups, quantified using CIELAB values, correlated with major uranium compounds. Furthermore, the findings indicated that trace elements can influence the UOC colors, providing additional insights into material characteristics. Although this approach requires further validation across a broader range of UOC species, this study demonstrated that simple colorimetric analysis using visible spectrophotometry, which does not require complex sample preparation or data processing, can serve as a practical and novel rapid tool for preliminary screening and attribution in nuclear forensics investigations.

and nuclear chemistry↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The use of gas chromatography – high resolution mass spectrometry for suspect screening and non-targeted analysis of per- and polyfluoroalkyl substances

This study is a workflow development for the analysis, identification, and categorization of per- and polyfluoroalkyl substances (PFAS) using gas chromatography-high resolution mass spectrometry (GC-HRMS) with non-targeted analysis (NTA) and suspect screening techniques. The behavior of various PFAS in a GC-HRMS was studied with regards to retention indices, ionization susceptibility, fragmentation patterns, etc. A custom PFAS database was constructed from 141 diverse PFAS. The database contains mass spectra from electron ionization (EI) mode, as well as MS and MS/MS spectra from positive and negative chemical ionization (PCI and NCI, respectively) modes. Common fragments of PFAS were identified across a diverse set of 141 PFAS analyzed. A workflow for suspect screening of PFAS and partially fluorinated products of incomplete combustion/destruction (PICs/PIDs) was developed which utilized both the custom PFAS database and external databases. PFAS and other fluorinated compounds were identified in both a challenge sample (designed to test the identification workflow) and incineration samples suspected to contain PFAS and fluorinated PICs/PIDs. The challenge sample resulted in a 100% true positive rate (TPR) for PFAS which were present in the custom PFAS database. In conclusion, several fluorinated species were tentatively identified in the incineration samples using the developed workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗