Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

II. Structure of Perovskites 1982 A. Crystal Structure 1982 B. Nonstoichiometry in Perovskites 1983 1. Oxygen Nonstoichiometry 1983 2. Cation Nonstoichiometry 1984 C. Physical Properties 1985 D. Adsorption Properties 1986 1. CO and NO Adsorption 1986 2. Oxygen Adsorption 1987 E. Specific Surface and Porosity 1987 F. Thermal Stability in a Reducing Atmosphere 1989 III. Acid−Base and Redox Properties 1990 A. Acidity and Basicity 1990 B. Redox Processes 1991 1. Kinetics and Mechanisms 1992 2. Reduction−Oxidation Cycles 1993 C. Ion Mobility 1993 1. Oxygen Transport 1993 2. Cation Transport 1994 IV. Heterogeneous Catalysis 1995 A. Oxidation Reactions 1995 1. CO Oxidation 1995 2. Oxidation of Hydrocarbons 1996 B. Pollution Abatement 2001 1. NOx Decomposition 2001 2. Exhaust Treatment 2002 3. Stability 2004 C. Hydrogenation and Hydrogenolysis Reactions 2004 1. Hydrogenation of Carbon Oxides 2004 2. Hydrogenation and Hydrogenolysis Reactions 2006

Chemical structures and performance of perovskite oxides.

UV-Visible ار راد ن .د TiO2 ( تیفرظ راون مان هب نورتکلا یاراد یژرنا زارت لماش VB و ) رگید زارت ی یژرنا اب ( ییاناسر راون مان هب نورتکلا زا یلاخ و رتلااب VB یم ) .دشاب ت ود نیا نیب یژرنا توافت یژرنا فاکش زار ، پگ دناب هدیمان یم .دوش هک ینامز زا نورتکلا لاقتنا VB هب VB یم ماجنا دریگ ، TiO2 اب ودح یژرنا بذج د ev 2 / 3 ، نورتکلا تفج کی دیلوت یم هرفح .دیامن و نورتکلا هرفح ی نا اب هدش دیلوت یم کرتشم حطس هب لاقت ثعاب دناوت شنکاو ماجنا اه یی ددرگ . TiO2 دربراک ،دراد یدایز یاه هلمج زا یم ناوت اوه یگدولآ هیفصت یارب (CO2) و بآ و ... نآ زا هدافتسا درک .

Advanced Nanoarchitectures for Solar Photocatalytic Applications

Cerium dioxide (CeO2, ceria) is becoming an ubiquitous constituent in catalytic systems for a variety of applications. 2016 sees the 40th anniversary since ceria was first employed by Ford Motor Company as an oxygen storage component in car converters, to become in the years since its inception an irreplaceable component in three-way catalysts (TWCs). Apart from this well-established use, ceria is looming as a catalyst component for a wide range of catalytic applications. For some of these, such as fuel cells, CeO2-based materials have almost reached the market stage, while for some other catalytic reactions, such as reforming processes, photocatalysis, water-gas shift reaction, thermochemical water splitting, and organic reactions, ceria is emerging as a unique material, holding great promise for future market breakthroughs. While much knowledge about the fundamental characteristics of CeO2-based materials has already been acquired, new characterization techniques and powerful theoretical methods are dee...

Fundamentals and Catalytic Applications of CeO2-Based Materials

Automotive catalytic converters: current status and some perspectives

Hydrogen is an important raw material in chemical industries, and the steam reforming of light hydrocarbons (such as methane) is the most used process for its production. In this process, the use of a catalyst is mandatory and, if compared to precious metal-based catalysts, Ni-based catalysts assure an acceptable high activity and a lower cost. The aim of a distributed hydrogen production, for example, through an on-site type hydrogen station, is only reachable if a novel reforming system is developed, with some unique properties that are not present in the large-scale reforming system. These properties include, among the others, (i) daily startup and shutdown (DSS) operation ability, (ii) rapid response to load fluctuation, (iii) compactness of device, and (iv) excellent thermal exchange. In this sense, the catalyst has an important role. There is vast amount of information in the literature regarding the performance of catalysts in methane steam reforming. In this short review, an overview on the most recent advances in Ni based catalysts for methane steam reforming is given, also regarding the use of innovative structured catalysts.

https://www.mdpi.com/2073-4344/10/3/352/pdf

A Short Review on Ni Based Catalysts and Related Engineering Issues for Methane Steam Reforming

The steam reforming of biomass-derived ethanol is a promising method for hydrogen production. It needs the development of efficient catalysts, especially when the reaction is carried out at temperature lower than 600 °C. The performances of a bimetallic sample, based on Pt (3 wt.%) and Ni (10 wt.%) and supported on CeO2 were investigated, in terms of activity, selectivity and stability. Very interesting results were obtained in the range 250–600 °C, even with a stoichiometric water/ethanol molar ratio: the ethanol was completely converted at T ≥ 300 °C, with a products distribution extremely close to the equilibrium calculations. Moreover, the selectivity towards the desired compounds was very high, and as a consequence, the sample showed a very low coke selectivity (<1%) and a high stability, that was further improved with higher amount of water in the feed stream. The analysis of the products distribution as a function of contact time (3–600 ms) and temperature (340–480 °C) and the temperature programmed desorption (TPD) experiments, were used to hypothesize the possible reactions involved, in order to develop a mathematical model, able to simulate the kinetic behaviour of the low temperature-ethanol steam reforming over Pt/Ni/CeO2. Finally, a possible Pt/Ni/CeO2 catalyzed reaction pathway at 370 °C, was formulated, that includes the following steps: ethanol adsorption followed by dehydrogenation to acetaldehyde; intermediate decomposition and reforming to CH4, CO, H2 and CO2; CO-WGS and CO2 methanation reaction.

CeO2-supported Pt/Ni catalyst for the renewable and clean H2 production via ethanol steam reforming

Catalytic activity, selectivity and stability of a Pt/CeO2 (5wt% Pt) catalyst were investigated in the low temperature ethanol steam reforming reaction for hydrogen production. Experimental results showed that the catalyst is very active and selective, with negligible CO production and complete ethanol conversion already at 300 °C. The main promoted reactions are ethanol decomposition, ethanol steam reforming and CO water gas shift, and a preliminary kinetic investigation showed that the apparent reaction orders are 0.5 and 0 for ethanol and steam respectively, with an apparent activation energy of 18 kJ mol−1 evaluated in the range 300–450 °C. Kinetic evaluations and temperature programmed desorption experiments suggest a surface reaction mechanism involving the following step: (i) ethanol dissociative adsorption on catalyst surface to form acetaldehyde intermediate, (ii) decarbonylation to produce mainly H2, CH4 and CO, and (iii) WGS reaction of CO adsorbed on Pt sites to produce H2 and CO2.

Low temperature catalytic steam reforming of ethanol. 2. Preliminary kinetic investigation of Pt/CeO2 catalysts

Since the late 1980s, the scientific community has been attracted to microwave energy as an alternative method of heating, due to the advantages that this technology offers over conventional heating technologies. In fact, differently from these, the microwave heating mechanism is a volumetric process in which heat is generated within the material itself, and, consequently, it can be very rapid and selective. In this way, the microwave-susceptible material can absorb the energy embodied in the microwaves. Application of the microwave heating technique to a chemical process can lead to both a reduction in processing time as well as an increase in the production rate, which is obtained by enhancing the chemical reactions and results in energy saving. The synthesis and sintering of materials by means of microwave radiation has been used for more than 20 years, while, future challenges will be, among others, the development of processes that achieve lower greenhouse gas (e.g., CO2) emissions and discover novel energy-saving catalyzed reactions. A natural choice in such efforts would be the combination of catalysis and microwave radiation. The main aim of this review is to give an overview of microwave applications in the heterogeneous catalysis, including the preparation of catalysts, as well as explore some selected microwave assisted catalytic reactions. The review is divided into three principal topics: (i) introduction to microwave chemistry and microwave materials processing; (ii) description of the loss mechanisms and microwave-specific effects in heterogeneous catalysis; and (iii) applications of microwaves in some selected chemical processes, including the preparation of heterogeneous catalysts.

/pdf/microwaves-and-heterogeneous-catalysis-a-review-on-selected-4ktd31ozg7.pdf

Microwaves and heterogeneous catalysis: A review on selected catalytic processes

The effects of the support (alumina or ceria) on the activity, selectivity and stability of 1 wt% Pt catalyst for the low temperature ethanol steam reforming reaction have been investigated. Experimental results in the range 300–450 °C showed a better performance of ceria supported catalyst, especially with reference to deactivation rate. The characterizations of catalysts reveal the presence of very well dispersed PtOx in the ceria that, during the calcination step, is stabilized in the highest oxidation state, in contrast with Al2O3. Moreover, H2 TPR, and TPD showed that the better performances of the ceria supported catalyst are strictly linked to the greater ability of CeO2 to release and store oxygen, resulting in higher stability with respect to alumina supported catalysts. Coke formation, investigated by TPO experiments, occurred on supports and catalysts. However, more stable carbonaceous species were found on Al2O3 and Pt/Al2O3, likely responsible for the higher deactivation rate with respect to CeO2 supported Pt catalyst. Finally, catalytic activity, selectivity and stability of Pt/CeO2 catalyst increase by increasing the Pt load in the range 1–5 wt%. The best catalyst formulation (5 wt% Pt on CeO2) was selected for further studies. It is worthwhile that this catalyst is also active for the water gas shift conversion of CO to CO2, resulting in the absence of CO in the reformate product.

Vincenzo Palma

Papers

A Short Review on Ni Based Catalysts and Related Engineering Issues for Methane Steam Reforming

CeO2-supported Pt/Ni catalyst for the renewable and clean H2 production via ethanol steam reforming

Low temperature catalytic steam reforming of ethanol. 2. Preliminary kinetic investigation of Pt/CeO2 catalysts

Microwaves and heterogeneous catalysis: A review on selected catalytic processes

Low temperature catalytic steam reforming of ethanol. 1. The effect of the support on the activity and stability of Pt catalysts