Cellulolytic enzymes production guided by morphology engineering
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Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.
Nucleic acids are versatile scaffolds that accommodate a wide range of precisely defined operational characteristics.
The high activity and selectivity of Fe-based heterogeneous catalysts toward a variety of reactions that require the breaking of strong bonds are offset in large part by their considerable instability with respect to oxidative deactivation. While it has been shown that the stability of Fe catalysts is considerably enhanced by alloying them with precious metals (even at the single-atom limit), rational design criteria for choosing such secondary metals are still missing. Since oxidative deactivation occurs due to the strong binding of oxygen to Fe and reduction by adsorbed hydrogen mitigates the deactivation, we propose here to use the binding affinity of oxygen and hydrogen adatoms as the basis for rational design. As it would also be beneficial to use cheaper secondary metals, we have scanned over a large subset of 3d–5d mid-to late transition metal single atoms and computationally determined their effect on the oxygen and hydrogen adlayer binding as a function of chemical potential and adsorbate coverage. We further determine the underlying chemical origins that are responsible for these effects and connect them to experimentally tunable quantities. Our results reveal a reliable periodic trend wherein oxygen binding is weakened greatest as one moves right and down the periodic table. Hydrogen binding shows the same trend only at high (but relevant) coverages and otherwise tends to have its binding slightly increased in all systems. Trends with secondary metal coverage are also uncovered and connected to experimentally tunable parameters.
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MFiX (Multiphase Flow with Interphase eXchanges) is an open-source multiphase flow solver developed at the National Energy Technology Laboratory. Within the code, users have access to a single phase or interpenetrating continua-based multiphase two-fluid model (TFM), a discrete element model (DEM), and a particle-in-cell model (PIC). TFM, DEM, and PIC can all be used to create multiphase simulations that include hydrodynamics, chemical reactions, and heat transfer.
A programmer's manual is presented for the SEL 840MP multiprocessing control system MPCS. The topics discussed include task control; defining displays; MPCS calls for task control functions; MPCS calls and system interfaces for display functions; MPCS calls for input/output functions and services, file management, and utility services; and MPCS assembly language call sequence summary.
The generation and operational use of the SEL 840MP multiprocessing control system (MPCS) are considered. System initialization, job task table generation, the MPCS command language, display library generation, and system error summary are reviewed.
The DORMAN program was developed to create and modify a data bank containing data decks which serve as input to the DORCA Computer Program. Via a remote terminal a user can access the bank, extract any data deck, modify that deck, output the modified deck to be input to the DORCA program, and save the modified deck in the data bank. This computer program is an assist in the utilization of the DORCA program. The program is dimensionless and operates almost entirely in integer mode. The program was developed on the CDC 6400/7600 complex for implementation on a UNIVAC 1108 computer.
The numerical analysis of composite differential-turn trajectory pairs was studied for 'fast-evader' and 'neutral-evader' attitude dynamics idealization for attack aircraft. Transversality and generalized corner conditions are examined and the joining of trajectory segments discussed. A criterion is given for the screening of 'tandem-motion' trajectory segments. Main focus is upon the computation of barrier surfaces. Fortunately, from a computational viewpoint, the trajectory pairs defining these surfaces need not be calculated completely, the final subarc of multiple-subarc pairs not being required. Some calculations for pairs of example aircraft are presented. A computer program used to perform the calculations is included.
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With geological data available for all inner planets except Venus, we are entering an era of true comparative planetary geology, when knowledge of the differences and similarities for classes of structures (e.g., shield volcanoes) will lead to a better understanding of general geological processes, regardless of planet. Thus, it is imperative that planetologists, particularly those involved in geological mapping and surface feature analysis for terrestrial planets, be familiar with volcanic terrain in terms of its origin, structure, and morphology. One means of gaining this experience is through field trips in volcanic terrains - hence, the Planetology Conference in Hawaii. In addition, discussions with volcanologists at the conference provide an important basis for establishing communications between the two fields that will facilitate comparative studies as more data become available.
The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination, is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS system provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.