VIRTUAL LAB VIDEO BLOG SERIES: Ab initio discovery of new catalysts for hydrogen production

hello everyone and welcome to a new episode of the Virtual Lab series of video blog presentations on various diverse scientific Computing topics as you can see here the title of today's presentation is on the topic of discovering new materials from first principles for the purpose of developing more efficient catalysts for large-scale hydrogen production this presentation is provided by Virtual Lab the company behind the development of the materials Square online platform materials square is ent

irely dedicated to assisting and encouraging researchers from across the world to perform atomistic computational simulations on a wide range of Materials Science and molecular chemical modeling applications directly via our integrated powerful cloud computing resources being entirely online based and executable via any basic web browser interface on any device with internet access the materials Square platform makes it possible to execute such complex simulations than calculations without the n

eed to install any complicated scientific code locally on your machine and without the need to have expensive supercomputing clusters at your immediate disposal are supported atomistic simulation functionalities and solutions are mainly based on well-established scientific computational techniques such as density functional Theory and classical molecular Dynamics and have a very broad range of useful applications in computational chemistry and Materials Science r d which are thus ideally suited

for both industrial and academic users from around the globe we invite our viewers to please consult our products and services offered via the materials Square platform by visiting its corresponding website which is www.matsq.com as noted also in the video description below so let us begin our main scientific presentation of today in general first principles computational techniques in Materials Science such as density functional Theory or DFT have proven to be very powerful in the design and di

scovery of Novel materials with certain desirable physical and chemical properties the optimization of such new material compositions can in fact often result in significant gains in terms of time costs and efforts spent in the laboratory in order to synthesize such materials since these experiments are then able to start with a general knowledge of which direction to take in the immense configurational space of all materials possibilities more recently first principle computer teens for new mat

erials design and Discovery are furthermore becoming increasingly complemented or even supplanted altogether by the Advent of purely AI machine learning and data mining based techniques in this way entirely new discoveries can be made by extrapolating the available data on existing materials properties databases while significantly reducing the need for new computationally expensive physics-based modeling and simulations as a practical example of materials designed from first principles we discu

ss briefly in the present video blog presentation the topic of the optimization of Novel Catalyst materials of increasing performance and efficiency for the production of hydrogen this is in fact currently a research topic under intense Spotlight considering the promising potential of hydrogen in the production of renewable energy and is an alternative to the burning of fossil fuels hydrogen in fact presents the advantage of burning cleanly when used as an energy source while producing water as

the only residual byproduct of its energy releasing burning reaction a key challenge therefore consists in developing efficient means of production of hydrogen gas at an industrial scale and in a commercially viable way in particular ensuring that more energy is generated as an output of the hull energy generation process than it is consumed in order to manufacture such hydrogen gas and to start the hydrogen burning reaction catalytic water splitting electrolysis is one of the most promising app

roaches to achieve an efficient hydrogen production in relation to its energy conversion and storage potential one way to achieve such catalytic-based process is via the so-called hydrogen Evolution reaction coupled with the oxygen Evolution reaction in which protons are transferred from an electrolyte solution to a metal electrode which acts as a catalyst following absorption of such protons onto the Catalyst surface they're chemically reduced thus resulting in the generation of hydrogen gas in

general this water-splitting reaction includes the oxygen Evolution reaction at the anode and the hydrogen Evolution reaction at the cathode hence the development of active stable and low-cost Catalyst materials to play the role of such electrodes is of crucial importance in ensuring the commercial success of hydrogen as a renewable energy source the best performing Catalyst material F or such hydrogen production reaction has traditionally been Platinum which however presents the major drawback

of being a very rare element in the Earth's crust and thus being very expensive hence the pressing need to discover new alternative Catalyst material candidates with comparable or even Superior efficiencies and performances to platinum in terms of hydrogen yield production a significant portion of such efforts to find Platinum Replacements has revolved around the use of DFT computational materials modeling techniques when considering such dft-based approach the following two questions need to b

e first addressed in order to better Define and characterize the Quest for new Catalyst material candidates firstly we need to understand which materials properties can serve to identify a performing Catalyst material composition and secondly how such properties can be computed AB initio using DFT methods for the case of the hydrogen Evolution reaction considered here it turns out that the performance level of the Catalyst correlates strongly with the Gibbs free energy of hydrogen adsorption on

the Catalyst surface which should be minimized and made as close as possible to zero value for obtaining a maximum catalytic activity and conversion efficiency for example for the case of platinum this free energy parameter corresponds to a very small value of 0.1 electron volts it turns out that this Gibbs free energy of hydrogen adsorption can be evaluated with DFT by calculating simply the change in total energy across the unfolding of this process of absorption the Simplicity of such total e

nergy computations lends itself very well for high throughput computational studies in the Quest for new Catalyst materials whereby hundreds or even thousands of new hypothetical material compositions can be screened simultaneously for spikes in catalytic activity through the use of large supercomputing or cloud-based computational facilities and resources in one of the early examples of such high throughput computational surveys for novel Catalyst material Discovery using DFT methods the Gibbs

free energy of hydrogen absorption was calculated for 736 distinct binary alloy compositions involving the different combinations of 16 transition metal elements as typically the case in such first principles computational surveys most of these tested material compositions were purely hypothetical and had never been synthesized experimentally before in fact assessing the air c2l synthesizability of any newly discovered material candidate exhibiting promising properties in AB initio calculations

is a completely separate experimental challenge which has to follow from such preliminary computational surveys in fact these often very difficult challenges and one therefore always needs to keep in mind that the prediction of materials with exceptional performances via DFT first principles methods does not always correspond to realistic and commercially viable experimental possibilities in this slide we reproduce some of the main results of this example study the figure here shows the values f

or the hydrogen absorption free energy for a certain subset of such binary alloy combinations already in this subset we can see that at least 49 combinations are promising in the sense that they correspond to a value of this free energy which is less than 0.1 electron volts The Benchmark value for platinum in order to narrow down the search space of all possible material candidates it is convenient at this stage to introduce additional optimization criteria for identifying highly performant cata

lysts such as the material's resistance to effects such as corrosion and oxidation in an electrochemical solution environment in the particular example study considered here the Gibbs free energies corresponding to the most common of such degradation phenomena were therefore also calculated with DFT methods and combined with the previously obtained results on the free energy of hydrogen adsorption in the end a selection of alloy Catalyst candidates was obtained which offered a good combination o

f performance in catalysis as well as in terms of stability in an electrochemical solution the figure shown in this slide demonstrates that only a minority of the previously identified performant Catalyst material candidates are actually at the same time chemically stable thus significantly reducing the total number of such favorable candidates to a more manageable amount concentrated around the bottom left corner of this diagram shown here as mentioned previously no first principle High through

out DFT computational screening of any set of candidate materials with certain desirable physical or chemical properties is actually useful by itself if such materials cannot later be realistically synthesized in experiments for their final commercial production in this particular example study the authors were able to synthesize one of the most promising candidate binary alloy compositions identified previously during the computational screening consisting in Platinum combined with bismuth as p

redicted from the DFT calculations the experimentally verified catalytic activity of this new compound turned out to be superior to that of pure platinum this successful example of computational prediction of a new Innovative material with Superior qualities demonstrates the power and effectiveness of ab initio DFT calculations in accelerating and directing the discovery process of these materials thus helping to reduce considerably the amount of time costs and effort invested in laboratory expe

riments aimed at synthesizing and characterizing such new materials to conclude our presentation today on the topic of the design and discovery of Novel catalytic materials with enhanced performances we would like to briefly introduce the catalytic cloud-based simulation scientific platform also developed by Virtual Lab which is distinct from the more General materials Square platform introduced in the beginning of the presentation the catalytic platform is in fact particularly relevant to the t

opic of today's presentation since it is entirely dedicated to computational research aimed at designing and discovering new Catalyst material structures with Innovative properties for energy generation and energy storage applications as explained here the catalytic cloud-based platform is conceived for performing high throughput simulations of oxygen Evolution reactions or oer and oxygen reduction reactions or RR using Advanced Materials simulation techniques such as DFT calculations kinetic Mo

nte Carlo and molecular Dynamics the platform also includes machine learning techniques for quickly screening potentially interesting candidate structures corresponding to the desired catalytic properties and performance levels all such functionalities thus allow the users of the catalytic platform to evaluate the activity thermal and chemical stabilities and realistic structure of their newly identified Innovative Catalyst materials ahead of their experimental synthesis this in turn can be used

to design more efficient and selective catalysts for a wide variety of industrial applications including for example fuel cells electrolyzes and batteries if you would be interested to gain a general idea of the functioning of the catalytic platform w e invite you to consult the following example of short tutorial on the process of evaluating the oxygen Evolution reaction of a nickel iron-based Catalyst material available under the link shown here at the bottom of the slide and under the video

description below this brings us to the conclusion of our presentation many thanks for your attention and we recommend once more to please give a try to our materials Square online platform for executing atomistic materials and chemical computations directly on the cloud by visiting its website at www.materialsquare.com please do not hesitate to contact us by email as shown here on this slide in case you would like to obtain further information on the various R D services and solutions that we p

rovide at Virtual Lab many thanks again for your interest and your consideration