Best Materials Science Software in New Zealand - Page 2

BIOVIA ONE Lab serves as a robust laboratory informatics platform aimed at optimizing workflows, fostering collaboration, and expediting research efforts in diverse scientific fields. This solution offers a cohesive environment for the management of laboratory data and processes, allowing researchers to make informed decisions more swiftly. It is utilized by organizations in various sectors such as Life Sciences, Consumer Packaged Goods, and Energy & Materials, among others. ONE Lab is adaptable for use in Research, Development, and Quality Assurance/Quality Control, catering to the unique requirements of scientists within each discipline. It effectively oversees samples, experiments, data, inventory, and equipment, as well as workflows, by integrating seamlessly with a variety of laboratory instruments and software. By utilizing a singular data model across all functional areas, ONE Lab eliminates artificial barriers that typically exist between Electronic Lab Notebooks (ELN), Laboratory Information Management Systems (LIMS), Laboratory Execution Systems (LES), and inventory management. This cohesive integration promotes efficiency and enhances the overall productivity of laboratory operations. Ultimately, BIOVIA ONE Lab empowers scientists to focus on innovation and discovery without the hindrances of fragmented systems.

Thermo-Calc is an advanced thermodynamic modeling tool utilized by materials scientists and engineers to derive data on material properties, deepen their understanding of materials, clarify specific phenomena, and address targeted inquiries regarding certain materials and their processing techniques. This software comes equipped with a variety of standard calculators included in all licenses, such as the Equilibrium Calculator, Scheil Solidification Simulations, Property Model Calculator, General Model Library, Material to Material Calculator, Pourbaix Diagram Module, and the Data Optimization Module (PARROT). Additionally, users can enhance Thermo-Calc's capabilities with multiple Add-on Modules and access over 40 databases, all seamlessly integrated into a single platform, creating a cohesive working environment. The software allows for the calculation of the state of a specified thermodynamic system, yielding valuable insights into phase quantities and compositions, transformation temperatures, solubility thresholds, and the driving forces behind phase formation, among other important metrics. Furthermore, this powerful modeling tool facilitates innovative research and development in materials science by enabling users to simulate various scenarios and predict outcomes effectively.

QSimulate presents an array of quantum simulation platforms that harness the principles of quantum mechanics to address intricate, large-scale challenges in life sciences and materials science. The QSP Life platform introduces innovative quantum-enhanced techniques for drug discovery and optimization, facilitating pioneering quantum simulations of ligand-protein interactions that are relevant throughout the entire computational drug discovery journey. Meanwhile, the QUELO platform enables hybrid quantum/classical free energy calculations, empowering users to conduct relative free energy assessments via the free energy perturbation (FEP) method. Furthermore, QSimulate's advancements enable significant progress in quantum mechanics/molecular mechanics (QM/MM) simulations tailored for extensive protein modeling. In the realm of materials science, the QSP Materials platform opens up quantum mechanical simulations to a broader audience, allowing experimentalists to streamline complex workflows without requiring specialized expertise, ultimately fostering greater innovation in the field. This democratization of technology marks a pivotal shift in how researchers can approach and solve scientific problems.

The CrowdChem Data Platform serves as an innovative knowledge hub tailored for the chemistry sector, utilizing data gathered through independent means. This platform empowers users to efficiently choose raw materials and identify potential customers via its advanced data analysis capabilities and text mining techniques. For instance, it facilitates the exploration of novel raw material combinations, enhances the precision of chemical product usage research, and generates lists of prospective customers for various companies. Users benefit from the ability to navigate a vast repository of information sourced from patents, academic papers, catalogs, and news articles, thus streamlining the process of data retrieval. By leveraging machine learning and natural language processing technologies, the platform allows for seamless raw material selection and customer identification, while also supporting competitive analysis and additional functionalities. Ultimately, this integration of cutting-edge technology enhances overall efficiency and decision-making in the chemistry domain.

Atinary's Self-Driving Labs (SDLabs) platform offers a no-code solution for AI and machine learning, aimed at transforming research and development workflows by allowing conventional laboratories to move from hands-on experiments to fully autonomous experimentation. This platform enhances the design and refinement of experiments through a comprehensive closed-loop system that incorporates AI-generated hypotheses, forecasts, and decisions. Among its notable features are multi-objective optimization, efficient database management, streamlined workflow orchestration, and real-time data analysis. Users have the capability to set experimental parameters with specific constraints, enabling machine learning algorithms to determine the next steps in the process, conduct experiments either manually or with robotic aid, analyze outcomes, and update models with the latest data, thus expediting the pursuit of improved, cost-effective, and environmentally friendly products. Additionally, Atinary offers proprietary algorithms, including Emmental for tackling non-linear constrained optimization, SeMOpt for implementing transfer learning in Bayesian optimization, and Falcon, which collectively enhance the platform's functionality and effectiveness. By leveraging these advanced tools, researchers can achieve greater efficiency and innovation in their experimental processes.

AQChemSim is an innovative cloud-based platform created by SandboxAQ that utilizes Large Quantitative Models (LQMs) based on principles of physics and chemistry to transform the landscape of materials discovery and enhancement. By incorporating techniques such as Density Functional Theory (DFT), Iterative Full Configuration Interaction (iFCI), Generative AI, Bayesian Optimization, and Chemical Foundation Models, AQChemSim facilitates precise simulations of molecular and material dynamics in real-world scenarios. The platform's features allow it to forecast performance under diverse stress conditions, expedite formulation via in silico testing, and investigate eco-friendly chemical processes. Remarkably, AQChemSim has achieved notable progress in battery technology, cutting the prediction time for lithium-ion battery end-of-life by 95%, while also attaining 35 times greater accuracy with a mere fraction of the data previously required. This advancement not only streamlines research but also paves the way for more efficient and sustainable energy solutions in the future.

Integrate the digital and physical realms through the Dassault Systèmes 3DEXPERIENCE® platform to enable collaboration, modeling, optimization, and operational performance. Establish the layout of the plant, including the flow, assets, and resources required for effective and safe product manufacturing. Enhance the definitions of products and resources; outline and confirm a process plan while developing work instructions that align with production targets. Optimize supply chain planning across all time frames; improve visibility with scheduling and planning to reduce interruptions. Revolutionize international production processes to attain and maintain operational excellence through Manufacturing Operations Management. Additionally, oversee and regulate operational processes on a worldwide scale to ensure consistency and efficiency.

DIGIMU® creates digital polycrystalline microstructures that accurately reflect the material's heterogeneities, ensuring compliance with the intricate topological features of the microstructure. The boundary conditions applied to the Representative Elementary Volume (REV) mimic the experiences of a material point at the macroscopic level, particularly during the thermomechanical cycles relevant to that specific point. Utilizing a Finite Element formulation, the software simulates the various physical phenomena occurring in metal forming processes, such as recrystallization, grain growth, and Zener pinning caused by second phase particles. To enhance digital accuracy and minimize computation times, DIGIMU® employs advanced automated anisotropic meshing and remeshing adaptation technology, which allows for a detailed representation of grain boundaries while optimizing the number of elements used. This innovative approach not only streamlines the computational process but also improves the reliability of the simulations, making it a powerful tool for material scientists.

Microsoft Discovery is an advanced AI-powered platform designed to accelerate scientific discovery by enabling researchers to collaborate with a team of specialized AI agents. This platform leverages a graph-based knowledge engine that connects diverse scientific data, allowing for deep, contextual reasoning over complex and often contradictory theories. Researchers can customize AI agents to align with their specific domains and tasks, making it easier to manage and orchestrate research efforts. Built on Microsoft Azure, Discovery ensures a high level of trust, transparency, and compliance, offering an enterprise-ready solution. The platform has already been used to accelerate the development of a novel coolant for data centers, cutting the discovery time from months to just 200 hours. This demonstrates the transformative potential of AI in R&D, providing researchers with the tools to unlock new possibilities and innovations at scale.

Revolutionize the fields of drug discovery and materials research through cutting-edge molecular modeling techniques. Our computational platform, grounded in physics, combines unique solutions for predictive modeling, data analysis, and collaboration, facilitating swift navigation of chemical space. This innovative platform is employed by leading industries globally, serving both drug discovery initiatives and materials science applications across various sectors including aerospace, energy, semiconductors, and electronic displays. It drives our internal drug discovery projects, overseeing processes from target identification through hit discovery and lead optimization. Additionally, it enhances our collaborative research efforts aimed at creating groundbreaking medicines to address significant public health challenges. With a dedicated team of over 150 Ph.D. scientists, we commit substantial resources to research and development. Our contributions to the scientific community include more than 400 peer-reviewed publications that validate the efficacy of our physics-based methodologies, and we remain at the forefront of advancing computational modeling techniques. We are steadfast in our mission to innovate and expand the possibilities within our field.