The computational modeling of nearly incompressible materials is a difficult task for many numerical methods, and even after several decades of investigation, it is still an active research area. This report seeks to address the treatment of incompressible materials in meshfree methods using a synergistic combination of two treatments. The first treatment is an $\bar{F}$ method, where the decomposed dilatational and deviatoric parts are calculated over different smoothing domains. The second treatment “activates” additional nodes throughout the domain to increase the flexibility of the model. We implement this synergistic combination in the context of the reproducing kernel particle method (RKPM) and present results for the Cook’s membrane benchmark problem. The results are compared with those using the composite tet10 finite element with a volume-averaged J formulation. We show that the combined treatment is an effective way to deal with nearly incompressible materials in a meshfree framework and compares well with other highly-effective treatments.
Plasmonic heating by nanoparticles has been used to promote a range of chemical reactions. Now, thermoplasmonic activation has been applied to latent ruthenium catalysts, enabling olefin metathesis initiated by visible and infrared light. Additionally, the desire to harness light to drive chemical transformations has surely existed as long as the study of chemistry itself. In the earliest documented applications, light was used simply as a heat source — for example, in the distillation of liquids. Since that time, our knowledge of how light and matter interact has increased exponentially, with greater mechanistic and molecular understanding enabling modern photochemists to design molecules with a myriad of finely tuned optical properties for catalysis, biochemistry, optoelectronics and more. Nonetheless, the design and optimization of molecules to achieve specific optical properties is still challenging, and for some applications, a return to the ‘simplest’ transformation — that of light to heat — can offer a more efficient approach to achieve light-mediated chemical reactions. Now, writing in Nature Chemistry, Yossi Weizmann and colleagues describe a strategy for organic and polymer synthesis driven by the conversion of light to heat.
Lankiewicz, Thomas S.; Choudhary, Hemant; Gao, Yu; Amer, Bashar; Lillington, Stephen P.; Leggieri, Patrick A.; Brown, Jennifer L.; Swift, Candice L.; Lipzen, Anna; Na, Hyunsoo; Amirebrahimi, Mojgan; Theodorou, Michael K.; Baidoo, Edward E.K.; Barry, Kerrie; Grigoriev, Igor V.; Timokhin, Vitaliy I.; Gladden, John M.; Singh, Seema S.; Mortimer, Jenny C.; Ralph, John; Simmons, Blake A.; Singer, Steven W.; O'Malley, Michelle A.
Lignocellulose forms plant cell walls, and its three constituent polymers, cellulose, hemicellulose and lignin, represent the largest renewable organic carbon pool in the terrestrial biosphere. Insights into biological lignocellulose deconstruction inform understandings of global carbon sequestration dynamics and provide inspiration for biotechnologies seeking to address the current climate crisis by producing renewable chemicals from plant biomass. Organisms in diverse environments disassemble lignocellulose, and carbohydrate degradation processes are well defined, but biological lignin deconstruction is described only in aerobic systems. It is currently unclear whether anaerobic lignin deconstruction is impossible because of biochemical constraints or, alternatively, has not yet been measured. We applied whole cell-wall nuclear magnetic resonance, gel-permeation chromatography and transcriptome sequencing to interrogate the apparent paradox that anaerobic fungi (Neocallimastigomycetes), well-documented lignocellulose degradation specialists, are unable to modify lignin. We find that Neocallimastigomycetes anaerobically break chemical bonds in grass and hardwood lignins, and we further associate upregulated gene products with the observed lignocellulose deconstruction. These findings alter perceptions of lignin deconstruction by anaerobes and provide opportunities to advance decarbonization biotechnologies that depend on depolymerizing lignocellulose.
This report describes the creation process and final content of a spectral irradiance dataset for Albuquerque, New Mexico accompanied by a set of spectral response measurements for modules deployed at the same location. The spectral irradiance measurements were made using horizontally mounted spectroradiometers; therefore, they represent global horizontal irradiance. The dataset combines non-continuous spectroradiometer and weather measurements from a two-year period into a single calendar year. The data files are accompanied by extensive metadata as well as example calculations and graphs to demonstrate the potential uses of this database. The spectral response measurements were carried out by the National Renewable Energy Laboratory using 12 commercial silicon modules types that are undergoing long-term evaluation at Sandia National Laboratories in Albuquerque.
Barekzi, Nazir; Wilkins, Meagan N.; Williams, Aumon L.; Moore, Afiya J.; Duckett, Zachary R.; Tindall, Danielle M.; Eaddy, Donnetta R.; Johnson, Mary B.; Bass, Malcolm; Mageeney, Catherine M.
Bassalto is a newly isolated phage of Mycobacterium smegmatis mc2155 from the campus grounds of Norfolk State University in Norfolk, VA. Bassalto belongs to the cluster B and subcluster B3 mycobacteriophages, based on the nucleotide composition and comparison to known mycobacteriophages.
For computational physics simulations, code verification plays a major role in establishing the credibility of the results by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, surface integral equations, such as the method-of-moments implementation of the magnetic-field integral equation, are frequently used to solve Maxwell's equations on the surfaces of electromagnetic scatterers. These electromagnetic surface integral equations yield many code-verification challenges due to the various sources of numerical error and their possible interactions. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources. We demonstrate the effectiveness of these approaches for cases with and without coding errors.