Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network interaction”

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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Information Carried by Electromagnetic Radiation Launched from Accelerated Polarization Currents

We show experimentally that a continuous, linear, dielectric antenna in which a superluminal polarization-current distribution accelerates can be used to transmit a broadband signal that is reproduced in a comprehensible form at a chosen target distance and angle. The requirement for this exact correspondence between broadcast and received signals is that each moving point in the polarization-current distribution approaches the target at the speed of light at all times during its transit along the antenna. This results in a one-to-one correspondence between the time at which each point on the moving polarization current enters the antenna and the time at which all of the radiation emitted by this particular point during its transit through the antenna arrives simultaneously at the target. This has the effect of reproducing the desired time dependence of the original broadcast signal. For other observer-detector positions, the time dependence of the signal is scrambled, due to the nontrivial relationship between emission (retarded) time and reception time. This technique represents a contrast to conventional radio transmission methods; in most examples of the latter, signals are broadcast with little or no directivity, selectivity of reception being achieved through the use of narrow frequency bands. In place of this, the current paper uses a spread of frequencies to transmit information to a particular location; the signal is weaker and has a scrambled time dependence elsewhere. Here, we point out the possible relevance of this mechanism to 5G neighborhood networks and pulsar astronomy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Internal and near nozzle measurements of Engine Combustion Network “Spray G” gasoline direct injectors

Gasoline direct injection (GDI) sprays are complex multiphase flows. When compared to multi-hole diesel sprays, the plumes are closely spaced, and the sprays are more likely to interact. The effects of multi-jet interaction on entrainment and spray targeting can be influenced by small variations in the mass fluxes from the holes, which in turn depend on transients in the needle movement and small-scale details of the internal geometry. In this paper, we present a comprehensive overview of a multi-institutional effort to experimentally characterize the internal geometry and near-nozzle flow of the Engine Combustion Network (ECN) Spray G gasoline injector. In order to develop a complete picture of the near-nozzle flow, a standardized setup was shared between facilities. A wide range of techniques were employed, including both X-ray and visible-light diagnostics. The novel aspects of this work include both new experimental measurements, and a comparison of the results across different techniques and facilities. The breadth and depth of the data reveal phenomena which were not apparent from analysis of the individual data sets. We show that plume-to-plume variations in the mass fluxes from the holes can cause large-scale asymmetries in the entrainment field and spray structure. Both internal flow transients and small-scale geometric features can have an effect on the external flow. The sharp turning angle of the flow into the holes also causes an inward vectoring of the plumes relative to the hole drill angle, which increases with time due to entrainment of gas into a low-pressure region between the plumes. In conclusion, these factors increase the likelihood of spray collapse with longer injection durations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Artificial Neural Network as the FPGA Trigger in the Cyclone V based Front-End for a Detection of Neutrino-Origin Showers

Neutrinos play a fundamental role in the understanding of the origin of ultra-high-energy cosmic rays. They interact through charged and neutral currents in the atmosphere generating extensive air showers. However, their a very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. A trigger based on a artificial neural network was implemented into the Cyclone{sup R} V E FPGA 5CEFA9F31I7 - the heart of the prototype Front-End boards developed for tests of new algorithms in the Pierre Auger surface detectors. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSICA and Offline platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-8-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg-Marquardt algorithm. Results show that a probability of a ADC traces generation is very low due to a small neutrino cross-section. Nevertheless, ADC traces, if occur, for 1-10 EeV showers are relatively short and can be analyzed by 16-point input algorithm. We optimized the coefficients from MATLAB to get a maximal range of potentially registered events and for fixed-point FPGA processing to minimize calculation errors. New sophisticated triggers implemented in Cyclone{sup R} V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support a discovery of neutrino events in the Pierre Auger Observatory. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

A common strategy for the dimensionality reduction of nonlinear partial differential equations (PDEs) relies on the use of the proper orthogonal decomposition (POD) to identify a reduced subspace and the Galerkin projection for evolving dynamics in this reduced space. However, advection-dominated PDEs are represented poorly by this methodology since the process of truncation discards important interactions between higher-order modes during time evolution. In this study, we demonstrate that encoding using convolutional autoencoders (CAEs) followed by a reduced-space time evolution by recurrent neural networks overcomes this limitation effectively. We demonstrate that a truncated system of only two latent space dimensions can reproduce a sharp advecting shock profile for the viscous Burgers equation with very low viscosities, and a six-dimensional latent space can recreate the evolution of the inviscid shallow water equations. Additionally, the proposed framework is extended to a parametric reduced-order model by directly embedding parametric information into the latent space to detect trends in system evolution. Furthermore, our results show that these advection-dominated systems are more amenable to low-dimensional encoding and time evolution by a CAE and recurrent neural network combination than the POD-Galerkin technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Synthesis, characterization, and anomalous dielectric and conductivity performance of one-dimensional (bdaH)InSe{sub 2} (bda = 1,4-butanediamine)

Graphical abstract: Anomalous dielectric and conductivity performance have been observed in the organic-containing indium selenide (bdaH)InSe{sub 2}, which are attributed to the water molecules existing in the crystal boundary rather than phase transition. Highlights: {yields} The title compound is the first example of organic-containing one-dimensional indium selenide. {yields} The anomalous dielectric peak is attributed to water molecules in crystal boundary. {yields} The inorganic and organic components of the title compound are connected via hydrogen bonding to form a supramolecular three-dimensional network. -- Abstract: A new indium selenide, namely (bdaH)InSe{sub 2} (1) (bda = 1,4-butanediamine) has been solvothermally synthesized and structurally characterized. It belongs to the non-centrosymmetric space group Fdd2. Its structure features an infinite one-dimensional anionic chain of [InSe{sub 2}]{sub n}{sup n-} with monoprotonated [bdaH]{sup +} as charge compensating cation. The organic [bdaH]{sup +} cations are joined into a supramolecular one-dimensional chain via N-H...N hydrogen bonding, which further interacts with the inorganic chain via N-H...Se and C-H...Se hydrogen bonding, forming a supramolecular three-dimensional network. Based on such a well-defined structure, the thermal stability, optical, conductivity, and dielectric properties were systematically investigated, showing that dielectric constant, as well as conductivity, had a hump at about 95 {sup o}C, which could be attributed to water molecules in the crystal boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Alkali-Metal-Intercalated Percolation Network Regulates Self-Assembled Electronic Aromatic Molecules

In the continuously growing field of correlated electronic molecular crystals, there is significant interest in addressing alkali-metal-intercalated aromatic hydrocarbons, in which the possibility of high-temperature superconductivity emerges. However, searching for superconducting aromatic molecular crystals remains elusive due to their small shielding fraction volume. To exploit this potential, a design principle for percolation networks of technologically important film geometry is indispensable. Here the effect of potassium-intercalation is shown on the percolation network in self-assembled aromatic molecular crystals. It is demonstrated that one-dimensional (1D) dipole pairs, induced by dipole interaction, regulate the conductivity, as well as the electronic and optical transitions, in alkalimetal-intercalated molecular electronic crystals. A solid-solution growth methodology of aromatic molecular films with a broad range of stability is developed to uncover electronic and optical transitions of technological importance. The light-induced electron interactions enhance the charge-carrier itinerancy, leading to a switchable metal-to-insulator transition. This discovery opens a route for the development of aromatic molecular electronic solids and long-term modulation of electronic efficacy in nano-technologically important thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2020

What can the GRACE seasonal cycle tell us about lake-aquifer interactions?

Lake-aquifer interactions have been the subject of investigation and debate for decades. Traditional investigation methods include measurement of water flux across the groundwater-surface water interface, application of heat and environmental tracer methods, conducting numerical simulations of the water flow, and mass balance-based approaches. We first review, evaluate and describe the different approaches that have been applied for examining lake-aquifer interactions and propose an additional complementary approach. While the leakage from lakes and its slow movement through porous media (laminar flow) is well characterized by existing methods, modeling the rapid and turbulent flow through preferred pathways (faults/karst) remains a challenging task. To better understand the nature, and the full scale, of the lake aquifer interactions, and using Lake Nasser and the underlying Dakhla subbasin of the Nubian Sandstone Aquifer System (NSAS) in the Western Desert of Egypt (area: 0.66 x 10 6 km 2 ) as a test site, we examine, model, and correlate temporally and spatially, the variations in Gravity Recovery and Climate Experiment terrestrial water storage (GRACE TWS ) solutions, with precipitation, lake levels, area, and water volume. We review current GRACE applications in hydrology and present our novel approach. Findings include: firstly, large seasonal fluctuations (peak: Nov./Dec.; trough: July/Aug.) in Lake Nasser's surface water levels (average annual fluctuations: from 3.7 m to 7.5 m), area (average area: 3622 km 2 but up to 4530 km 2 ), and volume (annual average: 13.4 km 3 , and up to 34 km 3 ) are observed throughout years 2006 to 2015. These fluctuations are accompanied by an increase in GRACE TWS (average: 50 ± 13 mm/yr, up to 77 ± 18 mm/yr) over Lake Nasser and by a progression of a front of increasing GRACE TWS values (> 50 ± 13 mm) away from the lake reaching distances of up to 700 km some 3 to 5 months following peak lake level periods. The areas witnessing the seasonal increase in GRACE TWS display a progressive increase in phase and decrease in amplitude with distance from the lake. Secondly, the negligible precipitation over the Dakhla subbasin cannot account for the observed seasonal GRACE TWS patterns and neither can the leakage signal from Lake Nasser. Thirdly, overall similarities in the distribution of GRACE TWS seasonal spatial patterns are observed. During high lake level periods (e.g., Dec. 2007; Feb. 2015) additional, and more distant, areas from Lake Nasser saw increases in GRACE TWS and vice versa during low lake level periods (e.g., July 2006; Aug. 2010). These observations are consistent with Lake Nasser being the main source of modern recharge for the Dakhla subbasin and suggest a new conceptual model for the subbasin: a slow groundwater flow through a porous matrix and a rapid groundwater flow along a network of faults, fractures, and karst topography across the matrix. We suggest that the proposed conceptual model for the interaction between Lake Nasser and the Dakhla subbasin could be applicable to aquifers of similar geologic, climatic, and hydrologic settings worldwide and that approaches similar to those advocated here could be used to investigate the validity of this suggestion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Deployment of neural-network-based neutron microscopic cross sections in the Griffin reactor physics application

The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗
DOE OSTI2019

The three-dimensional structure and recognition mechanism of Manduca sexta peptidoglycan recognition protein-1

Peptidoglycan recognition proteins (PGRPs) recognize bacteria through their unique cell wall constituent, peptidoglycans (PGs). PGRPs are conserved from insects to mammals and all function in antibacterial defense. In the tobacco hornworm Manduca sexta, PGRP1 and microbe binding protein (MBP) interact with PGs and hemolymph protease-14 precursor (proHP14) to yield active HP14. HP14 triggers a serine protease network that produces active phenoloxidase (PO), Spätzle, and other cytokines to stimulate immune responses. PGRP1 binds preferentially to diaminopimelic acid (DAP)-PGs of Gram-negative bacteria and Gram-positive Bacillus and Clostridium species than Lys-PGs of other Gram-positive bacteria. In this study, we synthesized DAP- and Lys-muramyl pentapeptide (MPP) and monitored their associations with M. sexta PGRP1 by surface plasmon resonance. The K d values (0.57 μM for DAP-MPP and 45.6 μM for Lys-MPP) agree with the differential recognition of DAP- and Lys-PGs. To reveal its structural basis, we produced the PGRP1 in insect cells and determined its structure at a resolution of 2.1 Å. The protein adopts a fold similar to those from other PGRPs with a classical L-shaped PG-binding groove. A unique loop lining the shallow groove suggests a different ligand-binding mechanism. In summary, this study provided new insights into the PG recognition by PGRPs, a critical first step that initiates the serine protease cascade.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Syntheses, crystal structures, and properties of four complexes based on polycarboxylate and imidazole ligands

Four metal–organic coordination polymers [Zn(HL)(H{sub 2}O)]·4H{sub 2}O (1), [Zn(HL)(L{sub 1})]·4H{sub 2}O (2), [Cu(HL)(H{sub 2}O)]·3H{sub 2}O (3) and [Cu(HL)(L{sub 1})]·5H{sub 2}O (4) were synthesized by reactions of the corresponding metal(II) salts with semirigid polycarboxylate ligand (5-((4-carboxypiperidin-1-yl)methyl)isophthalic acid hydrochloride, H{sub 3}L·HCl) or auxiliary ligand (1,4-di(1H-imidazol-4-yl)benzene, L{sub 1}). The structures of the compounds were characterized by elemental analysis, FT-IR spectroscopy and single-crystal X-ray diffraction. The use of auxiliary ligand L{sub 1} has great influence on the structures of two pairs of complexes 1, 2 and 3, 4. Complex 1 is a uninodal 3-connected rare 2-fold interpenetrating ZnSc net with a Point (Schlafli) symbol of (10{sup 3}) while 2 is a one-dimensional (1D) ladder structure. Compound 3 features a two-dimensional (2D) honeycomb network with typical 6{sup 3}-hcb topology, while 4 is 2D network with (4, 4) sql topology based on binuclear Cu{sup II} subunits. The non-covalent bonding interactions such as hydrogen bonds, π···π stacking and C–H···π exist in complexes 1–4, which contributes to stabilize crystal structure and extend the low-dimensional entities into high-dimensional frameworks. And the photoluminescent property of 1 and 2 and gas sorption property of 4 have been investigated. - Graphical abstract: Four new coordination polymers have been obtained and their photoluminescent and gas sorption properties have also been investigated. - Highlights: • Two pairs of Zn{sup II}/ Cu{sup II} compounds have been synthesized. • Auxiliary ligand-controlled assembly of the complexes is reported. • The luminescent properties of complexes 1–2 were investigated. • The gas sorption property of 4 has been investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Nanoscale structure, mechanics and growth of epidermal cell walls

This article briefly reviews recent advances in nano-scale and micro-scale assessments of primary cell wall structure, mechanical behaviors and expansive growth. Cellulose microfibrils have hydrophobic and hydrophilic faces which may selectively bind different matrix polysaccharides and adjacent microfibrils. Furthermore, these distinctive binding interactions may guide partially aligned cellulose microfibrils in primary cell walls to form a planar, load-bearing network within each lamella of polylamellate walls. Consideration of expansive growth of cross-lamellate walls leads to a surprising inference: side-by-side sliding of microfibrils may be a key rate-limiting physical step, potentially targeted by specific wall loosening agents. Atomic force microscopy shows different patterns of microfibril movement during force-driven extension versus enzymatic loosening. Consequently, simulations of cell growth as elastic deformation of isotropic cell walls may need to be augmented to incorporate the distinctive behavior of growing cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗
DOE OSTI2025

Multifunctional Silk Fibroin Hydrogels with Strong Adhesion for Tissue Sealing and Wearable Electronic Sensors

Multifunctional hydrogels with excellent adhesion, biodegradability, and conductivity are essential for overcoming the obstacles of postoperative secondary injury, flexible sensing instability, and so on. Herein, we develop a multifunctional silk fibroin (SF) hydrogel modified with poly(acrylic acid). Owing to the stable chemical cross-linking network and the abundant carboxylic acid groups of the SF network, the SF hydrogel exhibits a high tensile strength of 74.34 kPa due to sufficient cohesion and interfacial interactions. Additionally, the tensile strain reaches a maximum of 414.6%, the compressive strength is 0.9 MPa, and the shear adhesive strength for pig skin tissues is as high as 64 kPa. Compared with most hydrogels, our multifunctional SF hydrogel with a low swelling ratio provides excellent adhesion, biodegradation, and conductivity, which shows advantages in terms of invasive tissue sealing. Furthermore, the use of self-adhesive SF hydrogels as conductive hydrogels in flexible sensors also benefits the collection of physiological electricity and human motion signals in the field of wearable and implantable electronic devices.

adhesive↗
DOE OSTI2022

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm –2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Gene loss during a transition to multicellularity

Multicellular evolution is a major transition associated with momentous diversification of multiple lineages and increased developmental complexity. The volvocine algae comprise a valuable system for the study of this transition, as they span from unicellular to undifferentiated and differentiated multicellular morphologies despite their genomes being similar, suggesting multicellular evolution requires few genetic changes to undergo dramatic shifts in developmental complexity. Here, the evolutionary dynamics of six volvocine genomes were examined, where a gradual loss of genes was observed in parallel to the co-option of a few key genes. Protein complexes in the six species exhibited novel interactions, suggesting that gene loss could play a role in evolutionary novelty. This finding was supported by gene network modeling, where gene loss outpaces gene gain in generating novel stable network states. These results suggest gene loss, in addition to gene gain and co-option, may be important for the evolution developmental complexity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Investigation of the role of hydrogen bonding in ionic liquid-like salts with both N- and S-soft donors

In search of ionic liquids (ILs) with multiple types of soft donor atoms capable of preferentially complexing a range of soft metal ions over harder ions, we investigated structural clues to the role of hydrogen bonding in IL behavior through a series of salts with anions containing both N- and S-donor atoms based on azole thiolates. Reaction of equimolar amounts of triethylamine (Et 3 N) or diisobutylamine (DBA) with 1-phenyl-1H-tetrazole-5-thiol (PhTzSH), 1-methyl-1H-tetrazole-5-thiol (MeTzSH), or 5-methyl-1,3,4-dithiazole-2-thiol (MeDiTSH) yielded [Et 3 NH][MeTzS] (1), a yellow liquid, and the low melting yellow solids [DBAH][MeTzS] (2), [Et 3 NH][PhTzS] (3), [DBAH][PhTzS] (4), [Et 3 NH][MeDiTS] (5), and [DBAH][MeDiTS] (6). Thermal analysis revealed that all of them qualify as ILs with melting points below 100 °C. Single crystal X-ray structure analysis of 2–6 revealed the presence of an extensive H-bonding network that includes the rare N–H$\cdots$S hydrogen bonds in 3, 4, and 6. These weaker interactions appear to significantly influence thermal behavior, where strong bonding leads to higher melting temperatures and lower decomposition points.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Moving beyond the constraints of chemistry via crystal structure discovery with isotropic multiwell pair potentials

The rigid constraints of chemistry-dictated by quantum mechanics and the discrete nature of the atom-limit the set of observable atomic crystal structures. What structures are possible in the absence of these constraints? Here, we systematically crystallize one-component systems of particles interacting with isotropic multiwell pair potentials. We investigate two tunable families of pairwise interaction potentials. Our simulations self-assemble a multitude of crystal structures ranging from basic lattices to complex networks. Sixteen of the structures have natural analogs spanning all coordination numbers found in inorganic chemistry. Fifteen more are hitherto unknown and occupy the space between covalent and metallic coordination environments. The discovered crystal structures constitute targets for self-assembly and expand our understanding of what a crystal structure can look like.

crystal structures↗