Backdiff: a diffusion model for generalized transferable protein backmapping

Coarse-grained (CG) models play a crucial role in the study of protein structures, protein thermodynamic properties, and protein conformation dynamics. Due to the information loss in the coarse-graining process, backmapping from CG to all-atom configurations is essential in many protein design and drug discovery applications when detailed atomic representations are needed for in-depth studies. Despite recent progress in data-driven backmapping approaches, devising a backmapping method that can be universally applied across various CG models and proteins remains unresolved. In this work, we propose BackDiff, a new generative model designed to achieve generalization and reliability in the protein backmapping problem. BackDiff leverages the conditional score-based diffusion model with geometric representations. Since different CG models can contain different coarse-grained sites which include selected atoms (CG atoms) and simple CG auxiliary functions of atomistic coordinates (CG auxiliary variables), we design a self-supervised training framework to adapt to different CG atoms, and constrain the diffusion sampling paths with arbitrary CG auxiliary variables as conditions. Our method facilitates end-to-end training and allows efficient sampling across different proteins and diverse CG models without the need for retraining. Comprehensive experiments over multiple popular CG models demonstrate BackDiff's superior performance to existing state-of-the-art approaches, and generalization and flexibility that these approaches cannot achieve. A pretrained BackDiff model can offer a convenient yet reliable plug-and-play solution for protein researchers, enabling them to investigate further from their own CG models.Comment: 22 pages, 5 figure

AMP in the wild: Learning robust, agile, natural legged locomotion skills

The successful transfer of a learned controller from simulation to the real world for a legged robot requires not only the ability to identify the system, but also accurate estimation of the robot's state. In this paper, we propose a novel algorithm that can infer not only information about the parameters of the dynamic system, but also estimate important information about the robot's state from previous observations. We integrate our algorithm with Adversarial Motion Priors and achieve a robust, agile, and natural gait in both simulation and on a Unitree A1 quadruped robot in the real world. Empirical results demonstrate that our proposed algorithm enables traversing challenging terrains with lower power consumption compared to the baselines. Both qualitative and quantitative results are presented in this paper.Comment: Video: https://youtu.be/7Ggcj6Izfh

Modeling the Performance of A Flow-Through Gas Diffusion Electrode for Electrochemical Reduction of CO or CO₂

A flow-through gas diffusion electrode (GDE) consisting of agglomerate catalysts for CO or CO₂ reduction, gas channels for reactants, aqueous electrolytes for ionic transport, and metallic current collectors was simulated and evaluated using a numerical model. The geometric partial current densities and Faradaic Efficiencies (FE) for CH₄, C₂H₄ and H₂ generation in GDEs were calculated and compared to the behavior of analogous aqueous-based planar electrodes. The pH-dependent kinetics for CH₄ and C₂H₄ generation were used to represent the intrinsic catalytic characteristics for the agglomerate catalyst. The modeling indicated that relative to planar electrodes for either CO reduction (COR) or CO₂ reduction (CO₂R), substantial increases in electrochemical reduction rates and Faradaic efficiencies are expected when flow-through GDEs are used. The spatially resolved pH and reaction rates within the flow-through GDEs were also simulated for two different operating pHs, and the resulting transport losses were analyzed quantitatively. For CO₂ reduction, substantial loss of CO₂ via chemical reaction with the locally alkaline electrolyte was observed due to the increased pH in operating GDEs

Modeling the Performance of A Flow-Through Gas Diffusion Electrode for Electrochemical Reduction of CO or CO₂

A flow-through gas diffusion electrode (GDE) consisting of agglomerate catalysts for CO or CO₂ reduction, gas channels for reactants, aqueous electrolytes for ionic transport, and metallic current collectors was simulated and evaluated using a numerical model. The geometric partial current densities and Faradaic Efficiencies (FE) for CH₄, C₂H₄ and H₂ generation in GDEs were calculated and compared to the behavior of analogous aqueous-based planar electrodes. The pH-dependent kinetics for CH₄ and C₂H₄ generation were used to represent the intrinsic catalytic characteristics for the agglomerate catalyst. The modeling indicated that relative to planar electrodes for either CO reduction (COR) or CO₂ reduction (CO₂R), substantial increases in electrochemical reduction rates and Faradaic efficiencies are expected when flow-through GDEs are used. The spatially resolved pH and reaction rates within the flow-through GDEs were also simulated for two different operating pHs, and the resulting transport losses were analyzed quantitatively. For CO₂ reduction, substantial loss of CO₂ via chemical reaction with the locally alkaline electrolyte was observed due to the increased pH in operating GDEs

Modeling an integrated photoelectrolysis system sustained by water vapor

Two designs for an integrated photoelectrolysis system sustained by water vapor have been investigated using a multi-physics numerical model that accounts for charge and species conservation, electron and ion transport, and electrochemical processes. Both designs leverage the use of a proton-exchange membrane that provides conductive pathways for reactant/product transport and prevents product crossover. The resistive losses, product gas transport, and gas crossovers as a function of the geometric parameters of the two designs have been evaluated systematically. In these designs, minimization of pathways in the membrane that can support the diffusive transport of product gases from the catalyst to the gas-collecting chamber was required to prevent supersaturation of hydrogen or oxygen gases at the Nafion/catalyst interface. Due to the small, thin membrane layer that was required, a small electrode width (<300 μm) was also required to produce low resistive losses in the system. Alternatively, incorporation of a structured membrane that balances the gas transport and ionic transport allows the maximum electrode width to be increased to dimensions as large as a few millimeters. Diffusive gas transport between the cathode and anode was the dominant source for crossover of the product gases under such circumstances. The critical dimension of the electrode required to produce acceptably low rates of product crossover was also investigated through the numerical modeling and device simulations

Numerical Simulation of Performance and Solar-to-Fuel Conversion Efficiency for Photoelectrochemical Devices

The Industrial Revolution was energized by coal, petroleum, and natural gas. It is clear that fossil fuels, which drive steam and electrical engines, made possible a monumental increase in the amount of productive energy available to humans. But in the meantime, the constant burning of fossil fuels has changed the natural greenhouse, intensified global warming, deteriorated air quality, and eventually caused irreversible environmental damage on our planet. Renewable energy especially solar energy offers a desirable approach toward meeting our growing energy needs while largely reducing fossil fuel burning. The major problems in terms of harvesting energy directly from sunlight turn out to be low energy concentration and intermittency. Building solar-fuel generators, which stores solar energy in chemical bonds, similar to photosynthesis in nature, provides a possible solution to these two problems. Carbon-free chemicals, such as hydrogen gas, which are produced by solar-driven water-splitting, or carbon-neutral chemicals, such as methane and ethylene, which are produced by solar-driven CO₂ reduction, are all promising clean fuels for solar storage. This thesis is focused on studying the performance and solar to fuel conversion efficiency of existing and hypothetical test-bed photoelectrochemical prototypes using multi-physics modeling and simulation to lay a foundation for future implementation and scale-up of the integrated, solar-driven systems. For water-splitting systems, a sensitivity analysis has been made to assess the relative importance of improvements in electrocatalysts, light absorbers, and system geometry on the efficiency of solar-to-hydrogen generators. Besides, an integrated photoelectrolysis system sustained by water vapor is designed and modeled. Under concentrated sunlight, the performance of the photoelectrochemical system with 10× solar concentrators was simulated and the impact of hydrogen bubbles that are generated inside the cathodic chamber on the performance of the photoelectrolysis system was evaluated. For CO₂ reduction systems, operational constraints and strategies for systems to effect the sustainable, solar-driven reduction of atmospheric CO₂ were investigated. The spatial and light-intensity dependence of product distributions in an integrated photoelectrochemical CO₂ reduction system was modeled and simulated. Finally, the performance a flow-through gas diffusion electrode for electrochemical reduction of CO or CO₂ was evaluated. This thesis can be divided into three parts. The first part discusses the importance of solar energy. The second part includes Chapter II, Chapter III, Chapter IV, and Chapter V, which deals with solar-driven water-splitting cells, and the third part includes Chapter VI, Chapter VII, and Chapter VIII, which deals with solar-driven CO₂ reduction cells.</p

THE IMPACT OF POWER BOUNDARY MANAGEMENT ON THE DESIGN OF COMPANY-INITIATED OPEN INNOVATION PLATFORM

Open innovation recognizes potential opportunities and advantages gained from leveraging knowledge and innovations found outside an organization‟s formal boundaries. With the intensive use of Internet-based tools, organizations are actively involved in using Open Innovation Platform (OIP) to attract external knowledge. However, developing a company-initiated OIP is a challenging task because usage of OIP depends on the voluntary participation of external users, which makes companies cannot follow the protocol of developing traditional IS. Furthermore, a company\u27s institutional properties may also impact the design company-initiated OIP. In this research, we focus on one type of organizational property, namely power boundary, and explore its impact on the design of a company-initiated OIP over time. From qualitative analysis of two versions of OIP in a single company, we develop a theoretical model depicting how the changes of power boundary of a firm influence the design of a company-initiated OIP over time. This result generates theoretical and empirical insights into the OIP design and power boundary and thus has important implications for both scholars and practitioners

Modeling the Performance of an Integrated Photoelectrolysis System with 10× Solar Concentrators

Two designs for an integrated photoelectrolysis system that uses a 10× concentrating solar collector have been investigated in detail. The system performance was evaluated using a multi-physics model that accounted for the properties of the tandem photoabsorbers, mass transport, and the electrocatalytic performance of the oxygen-evolution and hydrogen-evolution reactions (OER and HER, respectively). The solar-to-hydrogen (STH) conversion efficiencies and the ohmic losses associated with proton transport in the solution electrolyte and through the membrane of the photoelectrolysis system were evaluated systematically as a function of the cell dimensions, the operating temperatures, the bandgap combinations of the tandem cell, and the performance of both the photoabsorbers and electrocatalysts. Relative to designs of optimized systems that would operate without a solar concentrator, the optimized 10× solar concentrator designs possessed larger ohmic losses and exhibited less uniformity in the distribution of the current density along the width of the photoelectrode. To minimize resistive losses while maximizing the solar-to-hydrogen conversion efficiency, η_(STH), both of the designs, a two-dimensional “trough” design and a three-dimensional “bubble wrap” design, required that the electrode width or diameter, respectively, was no larger than a few millimeters. As the size of the electrodes increased beyond this limiting dimension, the η_(STH) became more sensitive to the performance of the photoabsorbers and catalysts. At a fixed electrode dimension, increases in the operating temperature reduced the efficiency of cells with smaller electrodes, due to degradation in the performance of the photoabsorber with increasing temperature. In contrast, cells with larger electrode dimensions showed increases in efficiency as the temperature increased, due to increases in the rates of electrocatalysis and due to enhanced mass transport. The simulations indicted that cells that contained 10% photoabsorber area, and minimal amounts of Nafion or other permselective membranes (i.e. areal coverages and volumetric fractions of only a few percent of the cell), with the remaining area comprised of a suitable, low-cost inert, non porous material (flexible polymers, inert inorganic materials, etc.) should be able to produce high values of η_(STH), with η_(STH) = 29.8% for an optimized design with a bandgap combination of 1.6 eV/0.9 eV in a tandem photoabsorber system at 350 K