Hydrogen storageSeveral methods exist for storing hydrogen. These include mechanical approaches such as using high pressures and low temperatures, or employing chemical compounds that release H2 upon demand. While large amounts of hydrogen are produced by various industries, it is mostly consumed at the site of production, notably for the synthesis of ammonia. For many years hydrogen has been stored as compressed gas or cryogenic liquid, and transported as such in cylinders, tubes, and cryogenic tanks for use in industry or as propellant in space programs.
Water–gas shift reactionThe water–gas shift reaction (WGSR) describes the reaction of carbon monoxide and water vapor to form carbon dioxide and hydrogen: CO + H2O CO2 + H2 The water gas shift reaction was discovered by Italian physicist Felice Fontana in 1780. It was not until much later that the industrial value of this reaction was realized. Before the early 20th century, hydrogen was obtained by reacting steam under high pressure with iron to produce iron oxide and hydrogen.
Thermodynamic equilibriumThermodynamic equilibrium is an axiomatic concept of thermodynamics. It is an internal state of a single thermodynamic system, or a relation between several thermodynamic systems connected by more or less permeable or impermeable walls. In thermodynamic equilibrium, there are no net macroscopic flows of matter nor of energy within a system or between systems. In a system that is in its own state of internal thermodynamic equilibrium, no macroscopic change occurs.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Hydrogen productionHydrogen production is the family of industrial methods for generating hydrogen gas. As of 2020, the majority of hydrogen (~95%) is produced from fossil fuels by steam reforming of natural gas and other light hydrocarbons, partial oxidation of heavier hydrocarbons, and coal gasification. Other methods of hydrogen production include biomass gasification, methane pyrolysis, and electrolysis of water. Methane pyrolysis and water electrolysis can use any source of electricity including solar power.
Thermodynamic processClassical thermodynamics considers three main kinds of thermodynamic process: (1) changes in a system, (2) cycles in a system, and (3) flow processes. (1)A Thermodynamic process is a process in which the thermodynamic state of a system is changed. A change in a system is defined by a passage from an initial to a final state of thermodynamic equilibrium. In classical thermodynamics, the actual course of the process is not the primary concern, and often is ignored.
Thermodynamic systemA thermodynamic system is a body of matter and/or radiation, considered as separate from its surroundings, and studied using the laws of thermodynamics. Thermodynamic systems may be isolated, closed, or open. An isolated system exchanges no matter or energy with its surroundings, whereas a closed system does not exchange matter but may exchange heat and experience and exert forces. An open system can interact with its surroundings by exchanging both matter and energy.
Hydrogen economyThe hydrogen economy uses hydrogen to decarbonize economic sectors which are hard to electrify, essentially, the "hard-to-abate" sectors such as cement, steel, long-haul transport, etc. In order to phase out fossil fuels and limit climate change, hydrogen can be created from water using renewable sources such as wind and solar, and its combustion only releases water vapor into the atmosphere. Although with a very low volumetric energy density hydrogen is an energetic fuel, frequently used as rocket fuel, but numerous technical challenges prevent the creation of a large-scale hydrogen economy.
Thermodynamic stateIn thermodynamics, a thermodynamic state of a system is its condition at a specific time; that is, fully identified by values of a suitable set of parameters known as state variables, state parameters or thermodynamic variables. Once such a set of values of thermodynamic variables has been specified for a system, the values of all thermodynamic properties of the system are uniquely determined. Usually, by default, a thermodynamic state is taken to be one of thermodynamic equilibrium.
Ensemble learningIn statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Thermodynamic equationsThermodynamics is expressed by a mathematical framework of thermodynamic equations which relate various thermodynamic quantities and physical properties measured in a laboratory or production process. Thermodynamics is based on a fundamental set of postulates, that became the laws of thermodynamics. One of the fundamental thermodynamic equations is the description of thermodynamic work in analogy to mechanical work, or weight lifted through an elevation against gravity, as defined in 1824 by French physicist Sadi Carnot.
Thermal equilibriumTwo physical systems are in thermal equilibrium if there is no net flow of thermal energy between them when they are connected by a path permeable to heat. Thermal equilibrium obeys the zeroth law of thermodynamics. A system is said to be in thermal equilibrium with itself if the temperature within the system is spatially uniform and temporally constant. Systems in thermodynamic equilibrium are always in thermal equilibrium, but the converse is not always true.
Thermodynamic potentialA thermodynamic potential (or more accurately, a thermodynamic potential energy) is a scalar quantity used to represent the thermodynamic state of a system. Just as in mechanics, where potential energy is defined as capacity to do work, similarly different potentials have different meanings. The concept of thermodynamic potentials was introduced by Pierre Duhem in 1886. Josiah Willard Gibbs in his papers used the term fundamental functions. One main thermodynamic potential that has a physical interpretation is the internal energy U.
Mathematical optimizationMathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.
Green hydrogenGreen hydrogen (GH2 or GH2) is hydrogen generated by renewable energy or from low-carbon power. Green hydrogen has significantly lower carbon emissions than grey hydrogen, which is derived from fossil fuels without carbon capture. Green hydrogen may be used to decarbonize sectors that are hard to electrify, such as cement and iron production. Green hydrogen can be used to produce green ammonia, the main constituent of synthetic fertilizer. It can also be used for long-duration grid energy storage, and for long-duration seasonal energy storage.
Optimizing compilerIn computing, an optimizing compiler is a compiler that tries to minimize or maximize some attributes of an executable computer program. Common requirements are to minimize a program's execution time, memory footprint, storage size, and power consumption (the last three being popular for portable computers). Compiler optimization is generally implemented using a sequence of optimizing transformations, algorithms which take a program and transform it to produce a semantically equivalent output program that uses fewer resources or executes faster.
Non-equilibrium thermodynamicsNon-equilibrium thermodynamics is a branch of thermodynamics that deals with physical systems that are not in thermodynamic equilibrium but can be described in terms of macroscopic quantities (non-equilibrium state variables) that represent an extrapolation of the variables used to specify the system in thermodynamic equilibrium. Non-equilibrium thermodynamics is concerned with transport processes and with the rates of chemical reactions.
Hydrogen infrastructureA hydrogen infrastructure is the infrastructure of hydrogen pipeline transport, points of hydrogen production and hydrogen stations (sometimes clustered as a hydrogen highway) for distribution as well as the sale of hydrogen fuel, and thus a crucial prerequisite before a successful commercialization of automotive fuel cell technology. A hydrogen highway is a chain of hydrogen-equipped filling stations and other infrastructure along a road or highway which allow hydrogen vehicles to travel.
Water gasWater gas is a kind of fuel gas, a mixture of carbon monoxide and hydrogen. It is produced by "alternately hot blowing a fuel layer [coke] with air and gasifying it with steam". The caloric yield of this is about 10% of a modern syngas plant. Further making this technology unattractive, its precursor coke is expensive, whereas syngas uses cheaper precursor, mainly methane from natural gas. Synthesis gas is made by passing steam over a red-hot carbon fuel such as coke: (ΔH = +131 kJ/mol) The reaction is endothermic, so the fuel must be continually re-heated to maintain the reaction.
Hyperparameter optimizationIn machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process. By contrast, the values of other parameters (typically node weights) are learned. The same kind of machine learning model can require different constraints, weights or learning rates to generalize different data patterns.
