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Invention:

Multi-fidelity scale bridging between various flavors of molecular dynamics (i.e. ab-initio, classical and coarse-grained models) has remained a long-standing challenge. BLAST (Bridging Length/time scales via Atomistic Simulation Toolkit) is a framework that leverages machine learning principles to address this challenge.

Opportunity and Solution 

BLAST provides users with the capabilities to train and develop their own classical atomistic and coarse-grained interatomic potentials (i.e., force fields) for molecular simulations. BLAST is designed to address several long-standing problems in the molecular simulation community, such as unintended misuse of existing force fields due to a knowledge gap between developers and users, bottlenecks in traditional force field development approaches, and other issues relating to the accuracy, efficiency, and transferability of force fields. The BLAST architecture consists of a web user-friendly interface, front-end and back-end web services, and machine learning algorithms that run on high-performance computing (HPC) clusters.

Cybersecurity issues are a day-to-day struggle for businesses and organizations. Keeping information secure can be a herculean task. SMORE-MTD, developed by Argonne’s Joshua Lyle and Nate Evans with laboratory funding, defends against cybersecurity attacks by using software-defined networking to manipulate network paths that service user requests.

By randomly selecting which server and service will respond to a given user’s request, SMORE-MTD makes it more difficult for an attacker to identify which services to attack. SMORE-MTD also increases organizations’ resilience by preventing an attacker exploit from being routed to the vulnerable software, forcing attackers into repeated attacks that are more likely to be noticed. SMORE-MTD also eliminates the need to install and maintain configuration software on each host in rotation, which reduces complexity and increases the amount of software available for use.

A method of upcycling polymers to useful hydrocarbon materials. A catalyst with nanoparticles on a substrate selectively docks and cleaves longer hydrocarbon chains over shorter hydrocarbon chains. The catalyst includes metal nanoparticles in an order array on a substrate, and the nanoparticles exhibit an edge to facet ratio to provide for more interactions with the facets. The catalyst can be used to produce lubricants with superior tribological performance.

A method for synthesis of PtNi nanocages by synthesizing Pt₁Ni₆ nanoparticles and acid leaching to form PtNi nanocages. The acid leaching removes nickel selectively from the core of the nanoparticle.

This invention comprises methods, for typical small nanoparticles, of removing elements distribution heterogeneity in the particle to significantly improve performance. For big nanoparticles, the performance of 3-D architecture made from the segregated nanoparticle could be further improved by increasing the elements distribution heterogeneity with proper post-treatment. Can be used in applications such as fuel cell electric cars, back up power for remote communication tower and other stationary applications.

A method for scaled-up synthesis of PtNi nanoparticles. Synthesizing a Pt nanoparticle catalyst comprises the steps of: synthesizing PtNi nanoparticles, isolating PtNi/substrate nanoparticles, acid leaching the PtNi/substrate, and annealing the leached PtNi/substrate nanoparticles, and forming a Pt-skin on the PtNi/substrate nanoparticles.

This invention could be used to make high performance PEM fuel cell catalyst. PEM fuel cell have variety application potentials such as fuel cell electric cars, back up power for remote communication tower and other stationary application. This invention fulfills the needs of high performance fuel cell catalyst with high Pt surface area and Pt loading. Compared with existing Pt/C catalyst, the Pt mass activity of catalyst made by this invention is 13 times higher, Pt loading could be controlled in a much wider range, Pt surface area could be much higher. It may also be used to make other core/shell structure with variety application potentials in catalysis.

This invention describes a system for crystallization and data collection of proteins using fixed-target serial crystallography using microfluidic droplet crystallography for the generation of uniform small crystals and a nylon mesh holder for positioning of droplets with crystal (or batch crystal slurries). While the use of nylon has previously been reported in the literature, this invention includes a method and device design for sealing the droplet/slurry loaded mesh between Mylar sheets.