scholarly journals Learning design rules for selective oxidation catalysts from high-throughput experimentation and artificial intelligence

2021 ◽  
Author(s):  
Lucas Foppa ◽  
Christopher Sutton ◽  
Luca M. Ghiringhelli ◽  
Sandip De ◽  
Patricia Löser ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
High Performance ◽  
Heterogeneous Catalysts ◽  
Supported Catalysts ◽  
Value Added ◽  
Theoretical Data ◽  
Catalytic Performance ◽  
Subgroup Discovery ◽  
Data Set ◽  
High Yields

The design of heterogeneous catalysts is challenged by the complexity of materials and processes that govern reactivity and by the fact that the number of good catalysts is very small compared to the number of possible materials. Here, we show how the subgroup-discovery (SGD) artificial-intelligence approach can be applied to an experimental plus theoretical data set to identify constraints on key physicochemical parameters, the so-called SG rules, which exclusively describe materials and reaction conditions with outstanding catalytic performance. By using high-hroughput experimentation, 120 SiO 2 -supported catalysts containing ruthenium, tungsten and phosphorus were synthesized and tested in the catalytic oxidation of propylene. As candidate descriptive parameters, the temperature and ten parameters related to the composition and chemical nature of the catalyst materials, derived from calculated free-atom properties, were offered. The temperature, the phosphorus content, and the composition-weighted electronegativity are identified as key parameters describing high yields towards the value-added oxygenate products acrolein and acrylic acid. The SG rules not only reflect the underlying processes particularly associated to high performance but also guide the design of more complex catalysts containing up to five elements in their composition.

scholarly journals Platinum–copper single atom alloy catalysts with high performance towards glycerol hydrogenolysis

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Xi Zhang ◽  
Guoqing Cui ◽  
Haisong Feng ◽  
Lifang Chen ◽  
Hui Wang ◽  
...  
Keyword(s):  
Active Sites ◽  
High Performance ◽  
Reaction Pathway ◽  
Theoretical Calculations ◽  
Experimental Studies ◽  
Value Added ◽  
Catalytic Performance ◽  
Single Atom ◽  
Glycerol Hydrogenolysis ◽  
Single Atom Alloy

AbstractSelective hydrogenolysis of biomass-derived glycerol to propanediol is an important reaction to produce high value-added chemicals but remains a big challenge. Herein we report a PtCu single atom alloy (SAA) catalyst with single Pt atom dispersed on Cu nanoclusters, which exhibits dramatically boosted catalytic performance (yield: 98.8%) towards glycerol hydrogenolysis to 1,2-propanediol. Remarkably, the turnover frequency reaches up to 2.6 × 103 molglycerol·molPtCu–SAA−1·h−1, which is to our knowledge the largest value among reported heterogeneous metal catalysts. Both in situ experimental studies and theoretical calculations verify interface sites of PtCu–SAA serve as intrinsic active sites, in which the single Pt atom facilitates the breakage of central C–H bond whilst the terminal C–O bond undergoes dissociation adsorption on adjacent Cu atom. This interfacial synergistic catalysis based on PtCu–SAA changes the reaction pathway with a decreased activation energy, which can be extended to other noble metal alloy systems.

Efficient Catalytic Upgrade of Fructose to Alkyl Levulinates with Phenylpyridine- phosphotungstate Solid Hybrids

2019 ◽  
Vol 6 (1) ◽  
pp. 44-52 ◽  
Author(s):  
Chengjiang Fang ◽  
Yan Li ◽  
Zhaozhuo Yu ◽  
Hu Li ◽  
Song Yang
Keyword(s):  
Heterogeneous Catalysts ◽  
Phosphotungstic Acid ◽  
Solvothermal Method ◽  
Low Cost ◽  
Value Added ◽  
Catalytic Performance ◽  
Biomass Valorization ◽  
Methyl Levulinate ◽  
Alkyl Levulinates ◽  
Facile Solvothermal Method

Biomass, as the most abundant and renewable organic carbon source, can be upgraded into various value-added platform molecules. To implement more sustainable and economic catalytic biomass valorization, reusable heterogeneous catalysts would be one of the preferable choices. In this work, a series of phosphotungstic acid-based solid hybrids were produced by assembly of phosphotungstic acid with different pyridines using a facile solvothermal method. The obtained 3- phenylpyridine-phosphotungstate hybrid displayed superior catalytic performance in the upgrade of fructose to methyl levulinate with 71.2% yield and 83.2% fructose conversion at 140 ºC for 8 h in methanol, a bio-based and environmentally friendly solvent, which was probably due to its relatively large pore size and high hydrophobicity. This low-cost and eco-friendly catalytic process could be simply operated in a single pot without cumbersome separation steps. In addition, the 3- phenylpyridine-phosphotungstate catalyst was able to be reused for four times with little deactivation.

scholarly journals Fe3O4@chitosan-tannic acid bionanocomposite as a novel nanocatalyst for the synthesis of pyranopyrazoles

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maryam Kamalzare ◽  
Mohammad Reza Ahghari ◽  
Mohammad Bayat ◽  
Ali Maleki
Keyword(s):  
Reaction Time ◽  
Tannic Acid ◽  
High Performance ◽  
Catalytic Performance ◽  
Natural Material ◽  
Magnetic Nanocatalyst ◽  
Reaction Conditions ◽  
One Pot ◽  
Short Reaction Time ◽  
High Yields

AbstractRecently magnetic nanocatalyst has attracted considerable attention because of its unique properties, including high performance, easy separation from the reaction mixture, and recyclability. In this study, a novel magnetic bionanocomposite was synthesized with chitosan and tannic acid as a natural material. The synthesized bionanocatalyst was characterized by essential analysis. Fe3O4@chitosan-tannic acid as a heterogeneous nanocatalyst was successfully applied to synthesize pyranopyrazole and its derivatives by a one-pot four-component reaction of malononitrile, ethyl acetoacetate, hydrazine hydrate, and various aromatic aldehyde. At the end of the reaction, the nanocatalyst was separated from the reaction mixture and was reused several times with no significant decrease in its catalytic performance. Simple purification of products, the ability for recovering and reusing the nanocatalyst, eco-friendliness, high yields of pure products, mild reaction conditions, short reaction time, non-toxicity, economically affordable are some of the advantages of using the fabricated nanocatalyst in the synthesis of pyranopyrazole.

scholarly journals Artificial-intelligence-driven discovery of catalyst “genes” with application to CO2 activation on semiconductor oxides

2021 ◽  
Author(s):  
Aliaksei Mazheika ◽  
Yanggang Wang ◽  
Rosendo Valero ◽  
Francesc Vines ◽  
Francesc Illas ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Rational Design ◽  
Chemical Conversion ◽  
Catalytic Performance ◽  
Linear Molecule ◽  
Subgroup Discovery ◽  
Catalytic Activation ◽  
Semiconductor Oxides ◽  
Global Regression ◽  
The Common

Abstract Using subgroup discovery, an artificial intelligence (AI) approach that identifies statistically exceptional subgroups in a dataset, we develop a strategy for a rational design of catalytic materials. We identify “materials genes” (features of catalyst materials) that correlate with mechanisms that trigger, facilitate, or hinder the activation of carbon dioxide (CO2) towards a chemical conversion. The approach is used to address the conversion of CO2 to fuels and other useful chemicals. The AI model is trained on high-throughput first-principles data for a broad family of oxides. We demonstrate that bending of the gas-phase linear molecule, previously proposed as the indicator of activation, is insufficient to account for the good catalytic performance of experimentally characterized oxide surfaces. Instead, our AI approach identifies the common feature of these surfaces in the binding of a molecular O atom to a surface cation, which results in a strong elongation and therefore weakening of one molecular C-O bond. The same conclusion is obtained by using the bending indicator only when incombination with the Sabatier principle. Based on these findings, we propose a set of new promising oxide-based catalyst materials for CO2 conversion, and a recipe to find more. Our analysis also reveals advantages of local pattern discovery methods such as subgroup discovery over standard global regression approaches in discovering combinations of materials properties that result in a catalytic activation.

scholarly journals High-Performance Deep learning to Detection and Tracking Tomato Plant Leaf Predict Disease and Expert Systems

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Yaser AbdulAali Jasim
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
High Performance ◽  
Plant Disease ◽  
Detection System ◽  
Open Data ◽  
Data Set ◽  
Performance Rate

Nowadays, technology and computer science are rapidly developing many tools and algorithms, especially in the field of artificial intelligence.  Machine learning is involved in the development of new methodologies and models that have become a novel machine learning area of applications for artificial intelligence. In addition to the architectures of conventional neural network methodologies, deep learning refers to the use of artificial neural network architectures which include multiple processing layers. In this paper, models of the Convolutional neural network were designed to detect (diagnose) plant disorders by applying samples of healthy and unhealthy plant images analyzed by means of methods of deep learning. The models were trained using an open data set containing (18,000) images of ten different plants, including healthy plants. Several model architectures have been trained to achieve the best performance of (97 percent) when the respectively [plant, disease] paired are detected. This is a very useful information or early warning technique and a method that can be further improved with the substantially high-performance rate to support an automated plant disease detection system to work in actual farm conditions.

scholarly journals Hydrogen Production from Formic Acid Attained by Bimetallic Heterogeneous PdAg Catalytic Systems

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4027 ◽  
Author(s):  
Miriam Navlani-García ◽  
David Salinas-Torres ◽  
Diego Cazorla-Amorós
Keyword(s):  
Formic Acid ◽  
High Performance ◽  
Heterogeneous Catalysts ◽  
Carbon Materials ◽  
Pd Nanoparticles ◽  
Catalytic Performance ◽  
Catalytic Systems ◽  
Storage Technologies ◽  
The Impact ◽  
Great Focus

The production of H2 from the so-called Liquid Organic Hydrogen Carriers (LOHC) has recently received great focus as an auspicious option to conventional hydrogen storage technologies. Among them, formic acid, the simplest carboxylic acid, has recently emerged as one of the most promising candidates. Catalysts based on Pd nanoparticles are the most fruitfully investigated, and, more specifically, excellent results have been achieved with bimetallic PdAg-based catalytic systems. The enhancement displayed by PdAg catalysts as compared to the monometallic counterpart is ascribed to several effects, such as the formation of electron-rich Pd species or the increased resistance against CO-poisoning. Aside from the features of the metal active phases, the properties of the selected support also play an important role in determining the final catalytic performance. Among them, the use of carbon materials has resulted in great interest by virtue of their outstanding properties and versatility. In the present review, some of the most representative investigations dealing with the design of high-performance PdAg bimetallic heterogeneous catalysts are summarised, paying attention to the impact of the features of the support in the final ability of the catalysts towards the production of H2 from formic acid.

scholarly journals Efficient Electrocatalytic Upgrading of Furan-Based Biomass: Key Roles of Two-Dimensional Mesoporous Heterostructure and Ternary Electrolyte

2021 ◽  
Author(s):  
Haoran Wu ◽  
Yashi Zou ◽  
Haishan Xu ◽  
Jianming Yang ◽  
Qinye Bao ◽  
...  
Keyword(s):  
High Performance ◽  
Biomass Conversion ◽  
Value Added ◽  
Mesoporous Structure ◽  
Catalytic Performance ◽  
Active Species ◽  
Heterocyclic Carbenes ◽  
Two Dimensional ◽  
Mechanism Study ◽  
Efficient Conversion

Abstract Development of high-performance electrocatalytic systems for efficient conversion of biomass to value-added chemicals under mild conditions and understanding of their mechanisms are of profound significance, but have remained a great challenge. Here, we report the first development of two-dimensional mesoporous electrocatalyst for biomass conversion. The electrocatalyst (meso-PA/PmPD/GO) consists of phytic acid (PA)-doped mesoporous poly(m-phenylenediamine) layers coated on graphene oxide nanosheets. Meanwhile, a high-performance ternary electrolyte containing 1-butyl-3-methylimidazolium tetrafluoroborate (BmimBF4), acetonitrile and H2O is developed. The combination of meso-PA/PmPD/GO and the ternary electrolyte realizes highly efficient conversion of two important biomass derivatives at room temperature. One involves a hardly achieved oxidation of furfuryl alcohol to 6-hydroxy-2,3-dihydro-6H-pyrano-3-one with high faradic efficiency (FE: 83.7%) and selectivity (87.9%). The other involves the oxidation of furfural to 5-hydroxy-2(5H)-furanone with record-high FE (98.9%) and selectivity (93.6%). Mechanism study including DFT calculations unveils that N-heterocyclic carbenes (Bmim*) generated from BmimBF4 act as the reaction-determining active species. Additionally, the synergistic effect of the PA doping, mesoporous structure and p-n heterojunction interface in meso-PA/PmPD/GO favors the mass transport and the transfer of generated holes to the outer layers, thus boosting the catalytic performance.

scholarly journals Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery

2021 ◽  
Author(s):  
Lucas Foppa ◽  
Luca M. Ghiringhelli
Keyword(s):  
Transition Metal ◽  
Oxygen Reduction ◽  
Density Functional ◽  
Heterogeneous Catalysts ◽  
Adsorption Properties ◽  
Subgroup Discovery ◽  
Data Set ◽  
Transition Metal Alloy ◽  
Adsorption Sites ◽  
Adsorption Energies

AbstractIn order to estimate the reactivity of a large number of potentially complex heterogeneous catalysts while searching for novel and more efficient materials, physical as well as data-centric models have been developed for a faster evaluation of adsorption energies compared to first-principles calculations. However, global models designed to describe as many materials as possible might overlook the very few compounds that have the appropriate adsorption properties to be suitable for a given catalytic process. Here, the subgroup-discovery (SGD) local artificial-intelligence approach is used to identify the key descriptive parameters and constrains on their values, the so-called SG rules, which particularly describe transition-metal surfaces with outstanding adsorption properties for the oxygen-reduction and -evolution reactions. We start from a data set of 95 oxygen adsorption-energy values evaluated by density-functional-theory calculations for several monometallic surfaces along with 16 atomic, bulk and surface properties as candidate descriptive parameters. From this data set, SGD identifies constraints on the most relevant parameters describing materials and adsorption sites that (i) result in O adsorption energies within the Sabatier-optimal range required for the oxygen-reduction reaction and (ii) present the largest deviations from the linear-scaling relations between O and OH adsorption energies, which limit the catalyst performance in the oxygen-evolution reaction. The SG rules not only reflect the local underlying physicochemical phenomena that result in the desired adsorption properties, but also guide the challenging design of alloy catalysts.

An Overview of Metal-organic Frameworks-based Acid/Base Catalysts for Biofuel Synthesis

2020 ◽  
Vol 24 (16) ◽  
pp. 1876-1891
Author(s):  
Qiuyun Zhang ◽  
Yutao Zhang ◽  
Jingsong Cheng ◽  
Hu Li ◽  
Peihua Ma
Keyword(s):  
Alternative Fuels ◽  
Heterogeneous Catalysts ◽  
Supported Catalysts ◽  
Metal Organic Framework ◽  
Metal Organic Frameworks ◽  
Flexible Structures ◽  
Biodiesel Production ◽  
Biodiesel Synthesis ◽  
Metal Organic ◽  
Organic Framework

Biofuel synthesis is of great significance for producing alternative fuels. Among the developed catalytic materials, the metal-organic framework-based hybrids used as acidic, basic, or supported catalysts play major roles in the biodiesel production. This paper presents a timely and comprehensive review of recent developments on the design and preparation of metal-organic frameworks-based catalysts used for biodiesel synthesis from various oil feedstocks, including MILs-based catalysts, ZIFs-based catalysts, UiO-based catalysts, Cu-BTC-based catalysts, and MOFs-derived porous catalysts. Due to their unique and flexible structures, excellent thermal and hydrothermal stability, and tunable host-guest interactions, as compared with other heterogeneous catalysts, metal-organic framework-based catalysts have good opportunities for application in the production of biodiesel at industrial scale.

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