Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields

Annals of Operations Research - In recent years, operations research in agriculture has improved the harvested yield, reduced the cost and time required for field operations, and maintained...     

NIFTy 3 – Numerical Information Field Theory: A Python Framework for Multicomponent Signal Inference on HPC Clusters

NIFTy , “Numerical Information Field Theory,” is a software framework designed to ease the development and implementation of field inference algorithms. Field equations are formulated independently of the underlying spatial geometry allowing the user to focus on the algorithmic design. Under the hood, NIFTy ensures that the discretization of the implemented equations is consistent. This enables the user to prototype an algorithm rapidly in 1D and then apply it to high‐dimensional real‐world problems. This paper introduces NIFTy  3, a major upgrade to the original NIFTy  framework. NIFTy  3 allows the user to run inference algorithms on massively parallel high performance computing clusters without changing the implementation of the field equations. It supports n‐dimensional Cartesian spaces, spherical spaces, power spaces, and product spaces as well as transforms to their harmonic counterparts. Furthermore, NIFTy  3 is able to handle non‐scalar fields, such as vector or tensor fields. The functionality and performance of the software package is demonstrated with example code, which implements a mock inference inspired by a real‐world algorithm from the realm of information field theory. NIFTy  3 is open‐source software available under the GNU General Public License v3 (GPL‐3) at https://gitlab.mpcdf.mpg.de/ift/NIFTy/tree/NIFTy_3 .     

What is the role of acid–acid interactions in asymmetric phosphoric acid organocatalysis? A detailed mechanistic study using interlocked and non-interlocked catalysts

Organocatalysis has revolutionized asymmetric synthesis. However, the supramolecular interactions of organocatalysts in solution are often neglected, although the formation of catalyst aggregates can have a strong impact on the catalytic reaction. For phosphoric acid based organocatalysts, we have now established that catalyst–catalyst interactions can be suppressed by using macrocyclic catalysts, which react predominantly in a monomeric fashion, while they can be favored by integration into a bifunctional catenane, which reacts mainly as phosphoric acid dimers. For acyclic phosphoric acids, we found a strongly concentration dependent behavior, involving both monomeric and dimeric catalytic pathways. Based on a detailed experimental analysis, DFT-calculations and direct NMR-based observation of the catalyst aggregates, we could demonstrate that intermolecular acid–acid interactions have a drastic influence on the reaction rate and stereoselectivity of asymmetric transfer-hydrogenation catalyzed by chiral phosphoric acids.

Supramolecular acid–acid interactions lead to competing monomeric and dimeric pathways in phosphoric acid catalysis – so that stereoselectivities depend on catalyst concentration.     

Electronic Finetuning of 8-Methoxy Psoralens by Palladium-Catalyzed Coupling: Acidochromicity and Solvatochromicity

Differently 5-substituted 8-methoxypsoralens can be synthesized by an efficient synthetic route with various cross-coupling methodologies, such as Suzuki, Sonogashira and Heck reaction. Compared to previously synthesized psoralens, thereby promising daylight absorbing compounds as potentially active agents against certain skin diseases can be readily accessed. Extensive investigations of all synthesized psoralen derivatives reveal fluorescence in the solid state as well as several distinctly emissive derivatives in solution. Donor-substituted psoralens exhibit remarkable photophysical properties, such as high fluorescence quantum yields and pronounced emission solvatochromicity and acidochromicity, which were scrutinized by Lippert–Mataga and Stern–Volmer plots. The results indicate that the compounds exceed the limit of visible light, a significant factor for potential applications as an active agent. In addition, (TD)DFT calculations were performed to elucidate the underlying electronic structure and to assign experimentally obtained data.     

Differentiating between Acidic and Basic Surface Hydroxyls on Metal Oxides by Fluoride Substitution: A Case Study on Blue TiO2 from Laser Defect Engineering

Both oxygen vacancies and surface hydroxyls play a crucial role in catalysis. Yet, their relationship is not often explored. Herein, we prepare two series of TiO₂ (rutile and P25) with increasing oxygen deficiency and Ti³⁺ concentration by pulsed laser defect engineering in liquid (PUDEL), and selectively quantify the acidic and basic surface OH by fluoride substitution. As indicated by EPR spectroscopy, the laser-generated Ti³⁺ exist near the surface of rutile, but appear to be deeper in the bulk for P25. Fluoride substitution shows that extra acidic bridging OH are selectively created on rutile, while the surface OH density remains constant for P25. These observations suggest near-surface Ti³⁺ are highly related to surface bridging OH, presumably the former increasing the electron density of the bridging oxygen to form more of the latter. We anticipate that fluoride substitution will enable better characterization of surface OH and its correlation with defects in metal oxides.     

High-Entropy Lithium Argyrodite Solid Electrolytes Enabling Stable All-Solid-State Batteries

Superionic solid electrolytes (SEs) are essential for bulk-type solid-state battery (SSB) applications. Multicomponent SEs are recently attracting attention for their favorable charge-transport properties, however a thorough understanding of how configurational entropy (ΔS_conf) affects ionic conductivity is lacking. Here, we successfully synthesized a series of halogen-rich lithium argyrodites with the general formula Li_5.5PS_4.5Cl_xBr_1.5-x (0≤x≤1.5). Using neutron powder diffraction and ³¹P magic-angle spinning nuclear magnetic resonance spectroscopy, the S²⁻/Cl⁻/Br⁻ occupancy on the anion sublattice was quantitatively analyzed. We show that disorder positively affects Li-ion dynamics, leading to a room-temperature ionic conductivity of 22.7 mS cm⁻¹ (9.6 mS cm⁻¹ in cold-pressed state) for Li_5.5PS_4.5Cl_0.8Br_0.7 (ΔS_conf=1.98R). To the best of our knowledge, this is the first experimental evidence that configurational entropy of the anion sublattice correlates with ion mobility. Our results indicate the possibility of improving ionic conductivity in ceramic ion conductors by tailoring the degree of compositional complexity. Moreover, the Li_5.5PS_4.5Cl_0.8Br_0.7 SE allowed for stable cycling of single-crystal LiNi_0.9Co_0.06Mn_0.04O₂ (s-NCM90) composite cathodes in SSB cells, emphasizing that dual-substituted lithium argyrodites hold great promise in enabling high-performance electrochemical energy storage.     

Peptide Self-Assembly into Amyloid Fibrils at Hard and Soft Interfaces—From Corona Formation to Membrane Activity

Peptides and proteins are exposed to a variety of interfaces in a physiological environment, such as cell membranes, protein nanoparticles (NPs), or viruses. These interfaces have a significant impact on the interaction, self-assembly, and aggregation mechanisms of biomolecular systems. Peptide self-assembly, particularly amyloid fibril formation, is associated with a wide range of functions; however, there is a link with neurodegenerative diseases, such as Alzheimer's disease. This review highlights how interfaces affect peptide structure and the kinetics of aggregation leading to fibril formation. In nature, many surfaces are nanostructures, such as liposomes, viruses, or synthetic NPs. Once exposed to a biological medium, nanostructures are coated with a corona, which then determines their activity. Both accelerating and inhibiting effects on peptide self-assembly have been observed. When amyloid peptides adsorb to a surface, they typically concentrate locally, which promotes aggregation into insoluble fibrils. Starting from a combined experimental and theoretical approach, models that allow for a better understanding of peptide self-assembly near hard and soft matter interfaces are introduced and reviewed. Research results from recent years are presented and relationships between biological interfaces, such as membranes and viruses, and amyloid fibril formation are proposed.