Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Synthesizers”

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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Combined light- and heat-induced shape memory behavior of anthracene-based epoxy elastomers

Abstract The development of multi-stimuli-responsive shape memory polymers has received increasing attention because of its scientific and technological significance. In this work, epoxy elastomers with reversible crosslinks are synthesized by polymerizing an anthracene-functionalized epoxy monomer, a diepoxy comonomer, and a dicarboxylic acid curing agent. The synthesized elastomers exhibit active responses to both light and heat enabled by the incorporated anthracene groups. When exposed to 365 nm UV light, additional crosslinking points are created by the photo-induced dimerization of pendant anthracene groups. The formation of the crosslinking points increases modulus and glass transition temperature of the elastomers, allowing for the fixation of a temporary shape at room temperature. The temporary shape remains stable until an external heat stimulus is applied to trigger the scission of the dimerized anthracene, which reduces the modulus and glass transition temperature and allows the elastomers to recover their original shapes. The effects of external stimuli on the thermal and dynamic mechanical properties of the elastomers are investigated experimentally and are correlated with molecular dynamics simulations that reveal the changes of structure and dynamics of the anthracene molecules and flexible chains.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI techniques that uncover the relationships between discernible data signatures and model predictions. In this context, counterfactual explanations that synthesize small, interpretable changes to a given query while producing desired changes in model predictions have become popular. This under-constrained, inverse problem is vulnerable to introducing irrelevant feature manipulations, particularly when the model’s predictions are not well-calibrated. Hence, in this paper, we propose the TraCE (training calibration-based explainers) technique, which utilizes a novel uncertainty-based interval calibration strategy for reliably synthesizing counterfactuals. Given the wide-spread adoption of machine-learned solutions in radiology, our study focuses on deep models used for identifying anomalies in chest X-ray images. Using rigorous empirical studies, we demonstrate the superiority of TraCE explanations over several state-of-the-art baseline approaches, in terms of several widely adopted evaluation metrics. Our findings show that TraCE can be used to obtain a holistic understanding of deep models by enabling progressive exploration of decision boundaries, to detect shortcuts, and to infer relationships between patient attributes and disease severity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Complex magnetic properties associated with competing local and itinerant magnetism in \({\text {Pr}}_2 {\text {Co}}_{0.86} {\text {Si}}_{2.88}\)

Ternary intermetallic compound \({\text {Pr}}_2 {\text {Co}}_{0.86} {\text {Si}}_{2.88}\) has been synthesized in single phase and characterized by x-ray diffraction, scanning electron microscopy with energy dispersive x-ray spectroscopy (SEM-EDX) analysis, magnetization, heat capacity, neutron diffraction and muon spin rotation/relaxation ( \(\mu\) SR) measurements. The polycrystalline compound was synthesized in single phase by introducing necessary vacancies in Co/Si sites. Magnetic, heat capacity, and zero-field neutron diffraction studies reveal that the system undergoes magnetic transition below \(\sim\) 4 K. Neutron diffraction measurement further reveals that the magnetic ordering is antiferromagnetic in nature with an weak ordered moment. The high temperature magnetic phase has been attributed to glassy in nature consisting of ferromagnetic clusters of itinerant (3 d ) Co moments as evident by the development of internal field in zero-field \(\mu\) SR below 50 K. The density-functional theory (DFT) calculations suggest that the low temperature magnetic transition is associated with antiferromagnetic coupling between Pr 4 f and Co 3 d spins. Pr moments show spin fluctuation along with unconventional orbital moment quenching due to crystal field. The evolution of the symmetry and the crystalline electric field environment of Pr-ions are also studied and compared theoretically between the elemental Pr and when it is coupled with other elements such as Co. The localized moment of Pr 4 f and itinerant moment of Co 3 d compete with each other below \(\sim\) 20 K resulting in an unusual temperature dependence of magnetic coercivity in the system.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthesis of a novel multifunctional organic–inorganic nanocomposite for metal ions and organic dye removals

In this study, we used solvent assisted mechano-synthesis strategies to form multifunctional organic–inorganic nanocomposites capable of removing both organic and inorganic contaminants. A zeolite X (Ze) and activated carbon (AC) composite was synthesized via state-of-the-art mechanical mixing in the presence of few drops of water to form Ze/AC. The second composite (Ze/L/AC) was synthesized in a similar fashion, however this composite had the addition of disodium terephthalate as a linker. Both materials, Ze/AC and Ze/L/AC, were characterized using scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), Powdered X-ray diffraction (P-XRD), Fourier-transform infrared spectrometry (FTIR), Accelerated Surface Area and Porosimetry System (ASAP), and thermal gravimetric analysis (TGA). The SEM–EDS displayed the surface structure and composition of each material. The sodium, oxygen and carbon contents increased after linker connected Ze and AC. The P-XRD confirmed the crystallinity of each material as well as the composites, while FTIR indicated the function groups (C=C, O–H) in Ze/L/AC. The contaminant adsorption experiments investigated the effects of pH, temperature, and ionic strength on the adsorption of methylene blue (MB) and Co(II) for each material. In MB adsorption, the first-order reaction rate of Ze/L/AC (0.02 h -1 ) was double that of Ze/AC (0.01 h -1 ). The reaction rate of Ze/L/AC (4.8 h -1 ) was also extraordinarily higher than that of Ze/AC (0.6 h -1 ) in the adsorption of Co(II). Ze/L/AC composite achieved a maximum adsorption capacity of 44.8 mg/g for MB and 66.6 mg/g for Co(II) ions. The MB adsorption of Ze/AC and Ze/L/AC was best fit in Freundlich model with R 2 of 0.96 and 0.97, respectively, which indicated the multilayer adsorption. In the Co(II) adsorption, the data was highly fit in Langmuir model with R 2 of 0.94 and 0.92 which indicated the monolayer adsorption. These results indicated both materials exhibited chemisorption. The activation energy of Ze/L/AC in MB adsorption (34.9 kJ mol -1 ) was higher than that of Ze/L/AC in Co (II) adsorption (26 kJ mol -1 ).

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

GAHLS: an optimized graph analytics based high level synthesis framework

The urgent need for low latency, high-compute and low power on-board intelligence in autonomous systems, cyber-physical systems, robotics, edge computing, evolvable computing, and complex data science calls for determining the optimal amount and type of specialized hardware together with reconfigurability capabilities. With these goals in mind, we propose a novel comprehensive graph analytics based high level synthesis (GAHLS) framework that efficiently analyzes complex high level programs through a combined compiler-based approach and graph theoretic optimization and synthesizes them into message passing domain-specific accelerators. This GAHLS framework first constructs a compiler-assisted dependency graph (CaDG) from low level virtual machine (LLVM) intermediate representation (IR) of high level programs and converts it into a hardware friendly description representation. Next, the GAHLS framework performs a memory design space exploration while account for the identified computational properties from the CaDG and optimizing the system performance for higher bandwidth. The GAHLS framework also performs a robust optimization to identify the CaDG subgraphs with similar computational structures and aggregate them into intelligent processing clusters in order to optimize the usage of underlying hardware resources. Finally, the GAHLS framework synthesizes this compressed specialized CaDG into processing elements while optimizing the system performance and area metrics. Evaluations of the GAHLS framework on several real-life applications (e.g., deep learning, brain machine interfaces) demonstrate that it provides 14.27× performance improvements compared to state-of-the-art approaches such as LegUp 6.2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Synthesis of 2D layered transition metal (Ni, Co) hydroxides via edge-on condensation

Abstract Layered transition metal hydroxides (LTMHs) with transition metal centers sandwiched between layers of coordinating hydroxide anions have attracted considerable interest for their potential in developing clean energy sources and storage technologies. However, two-dimensional (2D) LTMHs remain largely understudied in terms of physical properties and applications in electronic devices. Here, for the first time we report > 20 μm α-Ni(OH) 2 2D crystals, synthesized from hydrothermal reaction. And an edge-on condensation mechanism assisted with the crystal field geometry is proposed to understand the 2D intra-planar growth of the crystals, which is also testified through series of systematic comparative studies. We also report the successful synthesis of 2D Co(OH) 2 crystals (> 40 μm) with more irregular shape due to the slightly distorted octahedral geometry of the crystal field. Moreover, the detailed structural characterization of synthesized α-Ni(OH) 2 are performed. The optical band gap energy is extrapolated as 2.54 eV from optical absorption measurements and the electronic bandgap is measured as 2.52 eV from reflected electrons energy loss spectroscopy (REELS). We further demonstrate its potential as a wide bandgap (WBG) semiconductor for high voltage operation in 2D electronics with a high breakdown strength, 4.77 MV/cm with 4.9 nm thickness. The successful realization of the 2D LTMHs opens the door for future exploration of more fundamental physical properties and device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF

The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always obtained. In this work, we report a methodology that uses a joint machine learning and experimental approach to optimize the synthesis conditions of Al-PMOF (Al 2 (OH) 2 TCPP) [H 2 TCPP = meso-tetra(4-carboxyphenyl)porphine], a promising material for carbon capture applications. Al-PMOF was previously synthesized using a hydrothermal reaction, which gave a low throughput yield due to its relatively long reaction time (16 hours). Here, we use a genetic algorithm to carry out a systematic search for the optimal synthesis conditions and a microwave-based high-throughput robotic platform for the syntheses. We show that, in just two generations, we could obtain excellent crystallinity and yield close to 80% in a much shorter reaction time (50 minutes). Moreover, by analyzing the failed and partially successful experiments, we could identify the most important experimental variables that determine the crystallinity and yield.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Creation of discrete active site domains via mesoporous silica poly(styrene) composite materials for incompatible acid–base cascade reactions

This work highlights the design and synthesis of bifunctional mesoporous silicate – polymer composite dual acid–base supported cascade catalysts. Compartmentalization of the two incompatible active sites is sought by segregating acid sites on the silica surface, and base sites within polymer chains and/or polymer domains. The ability to isolate and segregate active sites via control of the mesoporous silica pore size and polymer molecular weight is probed with silica samples functionalized by a grafting-to process. Supplemental activator and reducing agent (SARA) atom transfer radical polymerization is used to synthesize random copolymers containing protected primary amines. Thiol–ene ‘click’ chemistry facilitates silica functionalization via a convergent approach, with the ene-functionalized polymer end group and silica-grafted thiols forming SBA/MCM-SH-poly(styrene-co-2-(4-vinylbenzyl)isoindoline-1,3-dione). Polymer deprotection and thiol oxidation produces primary amine/sulfonic acid containing composite catalysts. With the polymer supported Lewis base and silica grafted Brønsted acid, the two-step deacetalization – Knoevenagel condensation cascade is explored to assess the ability of these polymer/silica hybrids to segregate active sites, allowing both acid and base site accessibility. Six composite catalysts are synthesized and tested in individual and cascade reactions with kinetic results demonstrating that lower molecular weight SBA-15-P1 and MCM-41-P1 catalysts outperform (higher turnover frequencies and initial rates) their higher molecular weight analogues, as well as a polymer-free system containing molecular active sites dispersed on the silica surface. Higher molecular weight composite catalysts perform more poorly due to limited chain solubility, mass transfer limitations, and poor catalyst accessibility. In many cases, the polymer chains effectively thread into the mesopores, with higher molecular weight polymers leading to pore blockage and inhibited mass transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed. While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Here, starting with 70 150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

08 HYDROGEN↗
DOE OSTI2020

Here aqueous solubilization of hydrophobic tetrapyrrole macrocycles by attachment to an amphiphilic single-chain nanoparticle (SCNP)

Solubilization of hydrophobic tetrapyrrole macrocycles and other fluorophores in aqueous solution has been achieved by covalent attachment to the terminus of an amphiphilic polymer, thereby affording a single-fluorophore–single-chain nanoparticle (SCNP). The polymer is a heterotelechelic random polyacrylate/polyacrylamide copolymer bearing hydrophobic and hydrophilic pendant groups. The polymer has a folded unimeric morphology (~13 nm hydrodynamic diameter) in 1 M NaCl aqueous solution as indicated by dynamic light-scattering spectroscopy. Five hydrophobic organic fluorophores (coumarin, perylene, two chlorins, one phthalocyanine) have been synthesized with a conjugatable tether. Covalent conjugation of the fluorophore–maleimide to the polymer terminus via thiol–maleimide reaction was carried out in DMF. The resulting fluorophore–SCNP in 1 M NaCl aqueous solution exhibited retained spectral features and fluorescence quantum yield comparable to those of the respective hydrophobic benchmark in toluene. This single-fluorophore–single-polymer strategy simplifies the challenging and often idiosyncratic syntheses of water-soluble tetrapyrrole macrocycles by using the polymer as a general aqueous solubilization package, and in so doing opens up opportunities for the application of hydrophobic fluorophores in the life sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Mesoporous silica-encapsulated gold core–shell nanoparticles for active solvent-free benzyl alcohol oxidation

Silica-encapsulated gold core@shell nanoparticles (Au@SiO2 CSNPs) were synthesized via a bottom-up procedure and used to catalyze the selective oxidation of benzyl alcohol. The pore size, morphology, crystallinity and composition of Au@SiO2 was evaluated using non-local density functional theory, transmission electron microscopy, high-energy x-ray diffraction and inductively coupled plasma-mass spectroscopy, respectively. The nanoparticles exhibit a mesoporous shell with an average thickness of 25.5 Å which can enhance selectivity via preferential transport of the desired product (i.e., benzaldehyde) relative to larger, undesired products (i.e, benzoic acid/benzyl benzoate). GC-FID analysis revealed the addition of potassium carbonate to the solvent-free oxidation of benzyl alcohol increased conversion from 17.3 to 60.4% while decreasing selectivity from 98.7 to 75.0%. Under equivalent conditions, a bare gold nanoparticle control catalyst deposited on a silica support with a similar gold surface area took 6 times as long to reach the same conversion, achieving only 49.4% selectivity. These results suggest that the pore size distribution within the inert silica shell of Au@SiO2 CSNPs inhibits the formation of undesired products to facilitate the selective oxidation of benzaldehyde despite a basic environment, which reduces selectivity under typical conditions. The CSNPs demonstrated a much lower activation energy than the Au-SiO2 control catalyst, 37 ± 1.9 kJ/mol and 72 ± 7.1 kJ/mol, respectively. Thiele modulus analysis indicates the CSNP pore structure does not create a mass transport limitation due to the nano-scale path of diffusion through the pore structure to the active surface. The lower activation energy and mesopore distribution together suggest the Au@SiO2 catalyst demonstrates higher activity through beneficial in-pore orientation, both reducing competitive adsorption and promoting a single, lower activation energy mechanistic pathway.

benzyl alcohol oxidation, catalysis, confinement↗
DOE OSTI2020

Structural trends in the dehydrogenation selectivity of palladium alloys

Alloying is well-known to improve the dehydrogenation selectivity of pure metals, but there remains considerable debate about the structural and electronic features of alloy surfaces that give rise to this behavior. To provide molecular-level insights into these effects, a series of Pd intermetallic alloy catalysts with Zn, Ga, In, Fe and Mn promoter elements was synthesized, and the structures were determined using in situ X-ray absorption spectroscopy (XAS) and synchrotron X-ray diffraction (XRD). The alloys all showed propane dehydrogenation turnover rates 5–8 times higher than monometallic Pd and selectivity to propylene of over 90%. Moreover, among the synthesized alloys, Pd 3 M alloy structures were less olefin selective than PdM alloys which were, in turn, almost 100% selective to propylene. This selectivity improvement was interpreted by changes in the DFT-calculated binding energies and activation energies for C–C and C–H bond activation, which are ultimately influenced by perturbation of the most stable adsorption site and changes to the d-band density of states. Furthermore, transition state analysis showed that the C–C bond breaking reactions require 4-fold ensemble sites, which are suggested to be required for non-selective, alkane hydrogenolysis reactions. These sites, which are not present on alloys with PdM structures, could be formed in the Pd 3 M alloy through substitution of one M atom with Pd, and this effect is suggested to be partially responsible for their slightly lower selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗