Eton Systems-a member of TMAS,the Swedish Textile Machinery Association-is taking part in the current Microfactories System Innovation project which is working on the development of a fully automated workflow for seco...Eton Systems-a member of TMAS,the Swedish Textile Machinery Association-is taking part in the current Microfactories System Innovation project which is working on the development of a fully automated workflow for second hand garments.Eton is contributing its well-proven transport system for material handling to the project,which also involves spe-cialists at the Swedish School of Textiles in Boras,the Au-tomation Region innovation cluster at Mälardalen University and the national collaboration platform iHubs Sweden.展开更多
Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Manag...Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Management System (NLIMS) for Kenya partnered with the Dedan Kimathi University of Technology on a project to develop a pilot LIMS for Nyeri County. A pilot Land Administration System (LAS) has been developed in this work and utilizes an Africanized Land Administration Domain Model (A-LADM) fitted to the Kenyan context. Various processes involved in land administration that required to be automated were identified. Informed by the numbers of applications made for the change of User service, it was picked as the first workflow to be automated. The key outputs of this work were the A-LADM and pilot LAS. The pilot solution uses a webcentric solution, with the data stored and managed centrally from a PostGIS database backend, using the Python Django framework to implement the server side and client side frontend. This solution demonstrates the importance of automating processes and supporting standards based software development. Stakeholder participation is key when implementing systems and 2 workshops are held to capture requirements and validate the developed solution.展开更多
The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties.Its execution requires control over a larger number of parameters,and therefore,its application in high-thro...The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties.Its execution requires control over a larger number of parameters,and therefore,its application in high-throughput studies is hindered by the complex and time-consuming convergence process across a multidimensional parameter space.To address these challenges,we develop a fullyautomated open-source workflow for G0W0 calculations within the AiiDA framework and the projector augmented wave(PAW)method.The workflow is based on an efficient estimation of the errors in the quasi-particle(QP)energies due to basis-set truncation and ultra-soft PAWpotentials norm violation,which allows a reduction in the dimensionality of the parameter space and avoids the need for multidimensional convergence searches.Protocol validation is conducted through a systematic comparison against established experimental and state-of-the-art GW data.To demonstrate the effectiveness of the approach,we construct a database of QP energies for a dataset of over 320 bulk structures.展开更多
We introduce an automated,flexible framework(aiida-hubbard)to self-consistently calculate Hubbard U and V parameters from first-principles.By leveraging density-functional perturbation theory,the computation of the Hu...We introduce an automated,flexible framework(aiida-hubbard)to self-consistently calculate Hubbard U and V parameters from first-principles.By leveraging density-functional perturbation theory,the computation of the Hubbard parameters is efficiently parallelized using multiple concurrent and inexpensive primitive cell calculations.Furthermore,the intersite V parameters are defined on-the-fly during the iterative procedure to account for atomic relaxations and diverse coordination environments.We devise a novel,code-agnostic data structure to store Hubbard related information together with the atomistic structure,to enhance the reproducibility of Hubbard-corrected calculations.We demonstrate the scalability and reliability of the framework by computing in high-throughput fashion the self-consistent onsite U and intersite V parameters for 115 Li-containing bulk solids with up to 32 atoms in the unit cell.Our analysis of the Hubbard parameters calculated reveals a significant correlation of the onsite U values on the oxidation state and coordination environment of the atom on which the Hubbard manifold is centered,while intersite V values exhibit a general decay with increasing interatomic distance.We find,e.g.,that the numerical values of U for the 3d orbitals of Fe and Mn can vary up to 3 eV and 6 eV,respectively;their distribution is characterized by typical shifts of about 0.5 eV and 1.0 eV upon change in oxidation state,or local coordination environment.For the intersite V a narrower spread is found,with values ranging between 0.2 eV and 1.6 eV when considering transition metal and oxygen interactions.This framework paves the way for the exploration of redox materials chemistry and high-throughput screening of d and f compounds across diverse research areas,including the discovery and design of novel energy storage materials,as well as other technologically-relevant applications.展开更多
Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workf...Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workflows,machine learning(ML)tech-niques,and robotic experiments have elevated sci-entific research to unprecedented levels.We have explored the iterative theoretical-experimental par-adigm,leveraged by robotic artificial intelligence(AI)chemists to bridge the gap between high-volume theoretical data and high-dimensional exper-imental data in this review.By combining automated high-throughput computations,ML models,and ro-botic large-scale experiments,this novel protocol aimed to accelerate data-driven chemistry innova-tion and materials discovery.Successful applications achieved by this paradigm include nanomaterials,high-entropy alloy catalysts,optical thin films,and oxygen evolution reaction(OER)catalysts from Martian meteorites.We have highlighted the potential for this paradigmatic evolution to redefine research methodologies and promote the next generation of precise and intelligent chemistry innovation.展开更多
Ductile inorganic semiconductors have recently received considerable attention due to their metal-like mechanical properties and potential applications in flexible electronics.However,the accurate determination of sli...Ductile inorganic semiconductors have recently received considerable attention due to their metal-like mechanical properties and potential applications in flexible electronics.However,the accurate determination of slip pathways,crucial for understanding the deformation mechanism,still poses a great challenge owing to the complex crystal structures of these materials.In this study,wepropose an automated workflow based on the interlayer slip potential energy surface to identify slip pathways in complex inorganic systems.Our computational approach consists of two key stages:first,an active learning strategy is utilized to efficiently and accurately model the interlayer slip potential energy surfaces;second,the climbing image nudged elastic band method is employed to identify minimum energy pathways,followed by comparative analysis to determine the final slip pathway.We discuss the validity of our selected feature vectors and models across various material systems and confirm that our approach demonstrates robust effectiveness in several case studies with both simple and complicated slip pathways.Our automated workflow opens a new avenue for the automatic identification of the slip pathways in inorganic materials,which holds promise for accelerating the high-throughput screening of ductile inorganic materials.展开更多
文摘Eton Systems-a member of TMAS,the Swedish Textile Machinery Association-is taking part in the current Microfactories System Innovation project which is working on the development of a fully automated workflow for second hand garments.Eton is contributing its well-proven transport system for material handling to the project,which also involves spe-cialists at the Swedish School of Textiles in Boras,the Au-tomation Region innovation cluster at Mälardalen University and the national collaboration platform iHubs Sweden.
文摘Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Management System (NLIMS) for Kenya partnered with the Dedan Kimathi University of Technology on a project to develop a pilot LIMS for Nyeri County. A pilot Land Administration System (LAS) has been developed in this work and utilizes an Africanized Land Administration Domain Model (A-LADM) fitted to the Kenyan context. Various processes involved in land administration that required to be automated were identified. Informed by the numbers of applications made for the change of User service, it was picked as the first workflow to be automated. The key outputs of this work were the A-LADM and pilot LAS. The pilot solution uses a webcentric solution, with the data stored and managed centrally from a PostGIS database backend, using the Python Django framework to implement the server side and client side frontend. This solution demonstrates the importance of automating processes and supporting standards based software development. Stakeholder participation is key when implementing systems and 2 workshops are held to capture requirements and validate the developed solution.
基金funded by the European Union—Next Generation EU—“PNRR - M4C2, investimento 1.1—Fondo PRIN 2022”—“Superlattices of relativistic oxides” (ID 2022L28H97, CUP D53D23002260006)The authors acknowledge the CINECA award under the ISCRA initiative, for the availability of high-performance computing resources and support, as well as computing time granted by the Vienna Scientific Cluster. Open Access funding is provided by University of Vienna.
文摘The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties.Its execution requires control over a larger number of parameters,and therefore,its application in high-throughput studies is hindered by the complex and time-consuming convergence process across a multidimensional parameter space.To address these challenges,we develop a fullyautomated open-source workflow for G0W0 calculations within the AiiDA framework and the projector augmented wave(PAW)method.The workflow is based on an efficient estimation of the errors in the quasi-particle(QP)energies due to basis-set truncation and ultra-soft PAWpotentials norm violation,which allows a reduction in the dimensionality of the parameter space and avoids the need for multidimensional convergence searches.Protocol validation is conducted through a systematic comparison against established experimental and state-of-the-art GW data.To demonstrate the effectiveness of the approach,we construct a database of QP energies for a dataset of over 320 bulk structures.
基金support from the Deutsche Forschungsgemeinschaft(DFG)under Germany’s Excellence Strategy(EXC 2077,No.390741603,University Allowance,University of Bremen),Lucio Colombi Ciacchi,the host of the“U Bremen Excellence Chair Program”C.M.and E.M acknowledge funding by MaX“Materials Design at the Exascale”,a Center of Excellence co-funded by the European High Performance Computing Joint Undertaking(JU)and participating countries under grant agreement No.101093374+4 种基金M.B.acknowledges funding by the European Centre of Excellence MaX“Materials design at the Exascale”(grant no.824143)and by the SwissTwins project,funded by the Swiss State Secretariat for Education,Research and Innovation(SERI)I.T.acknowledges funding by the Swiss National Science Foundation(grant no.200021-227641)We acknowledge support by the NCCR MARVEL,a National Centre of Competence in Research,funded by the Swiss National Science Foundation(Grant number 205602)This work was supported by a grant from the Swiss National Supercomputing Centre(CSCS)under project ID 465000416(LUMI-G).We thank Julian Geiger,Gabriel Joalland,Austin Zadoks and Timo Reents for useful discussions and feedbacks.
文摘We introduce an automated,flexible framework(aiida-hubbard)to self-consistently calculate Hubbard U and V parameters from first-principles.By leveraging density-functional perturbation theory,the computation of the Hubbard parameters is efficiently parallelized using multiple concurrent and inexpensive primitive cell calculations.Furthermore,the intersite V parameters are defined on-the-fly during the iterative procedure to account for atomic relaxations and diverse coordination environments.We devise a novel,code-agnostic data structure to store Hubbard related information together with the atomistic structure,to enhance the reproducibility of Hubbard-corrected calculations.We demonstrate the scalability and reliability of the framework by computing in high-throughput fashion the self-consistent onsite U and intersite V parameters for 115 Li-containing bulk solids with up to 32 atoms in the unit cell.Our analysis of the Hubbard parameters calculated reveals a significant correlation of the onsite U values on the oxidation state and coordination environment of the atom on which the Hubbard manifold is centered,while intersite V values exhibit a general decay with increasing interatomic distance.We find,e.g.,that the numerical values of U for the 3d orbitals of Fe and Mn can vary up to 3 eV and 6 eV,respectively;their distribution is characterized by typical shifts of about 0.5 eV and 1.0 eV upon change in oxidation state,or local coordination environment.For the intersite V a narrower spread is found,with values ranging between 0.2 eV and 1.6 eV when considering transition metal and oxygen interactions.This framework paves the way for the exploration of redox materials chemistry and high-throughput screening of d and f compounds across diverse research areas,including the discovery and design of novel energy storage materials,as well as other technologically-relevant applications.
基金the Innovation Program for Quantum Science and Technology,Chinese Academy of Sciences(CASgrant no.2021ZD0303303)+3 种基金the CAS Project for Young Scientists in Basic Research(grant no.YSBR-005)the National Natural Science Foundation of China(NSFCgrant nos.22025304 and 22033007)K.C.Wong Education Foundation,China(grant no.GJTD-2020-15).
文摘Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workflows,machine learning(ML)tech-niques,and robotic experiments have elevated sci-entific research to unprecedented levels.We have explored the iterative theoretical-experimental par-adigm,leveraged by robotic artificial intelligence(AI)chemists to bridge the gap between high-volume theoretical data and high-dimensional exper-imental data in this review.By combining automated high-throughput computations,ML models,and ro-botic large-scale experiments,this novel protocol aimed to accelerate data-driven chemistry innova-tion and materials discovery.Successful applications achieved by this paradigm include nanomaterials,high-entropy alloy catalysts,optical thin films,and oxygen evolution reaction(OER)catalysts from Martian meteorites.We have highlighted the potential for this paradigmatic evolution to redefine research methodologies and promote the next generation of precise and intelligent chemistry innovation.
基金supported by the National Natural Science Foundation of China(Nos.91963208,52232010,and 52122213)the Talent Plan of Shanghai Branch,Chinese Academy of Sciences(No.CASSHB-QNPD-2023-003)+1 种基金Shanghai Government(Nos.23JC1404000 and 23ZR1472800)We thank the computational resource provided by the Supercomputer Center in Shanghai Institute of Ceramics for DFT calculations in this study.
文摘Ductile inorganic semiconductors have recently received considerable attention due to their metal-like mechanical properties and potential applications in flexible electronics.However,the accurate determination of slip pathways,crucial for understanding the deformation mechanism,still poses a great challenge owing to the complex crystal structures of these materials.In this study,wepropose an automated workflow based on the interlayer slip potential energy surface to identify slip pathways in complex inorganic systems.Our computational approach consists of two key stages:first,an active learning strategy is utilized to efficiently and accurately model the interlayer slip potential energy surfaces;second,the climbing image nudged elastic band method is employed to identify minimum energy pathways,followed by comparative analysis to determine the final slip pathway.We discuss the validity of our selected feature vectors and models across various material systems and confirm that our approach demonstrates robust effectiveness in several case studies with both simple and complicated slip pathways.Our automated workflow opens a new avenue for the automatic identification of the slip pathways in inorganic materials,which holds promise for accelerating the high-throughput screening of ductile inorganic materials.
