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Accelerators in concrete serve as admixtures to speed up the hardening process, enabling the concrete to achieve early strength faster. Although accelerators do not necessarily impact the time it takes concrete to set, they reduce this time in practice. A common accelerator is calcium chloride, which is particularly useful for hastening early strength development in cold weather or for rapid repair jobs that require quick heat generation after mixing.
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Instantaneous Acceleration

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Related Experiment Video

Updated: Jan 21, 2026

Formation of Ordered Biomolecular Structures by the Self-assembly of Short Peptides

Formation of Ordered Biomolecular Structures by the Self-assembly of Short Peptides

Published on: November 21, 2013

Google-Accelerated Biomolecular Simulations.

Kai J Kohlhoff¹

¹Research, Google, Mountain View, CA, USA. kohlhoff@google.com.

Methods in Molecular Biology (Clifton, N.J.)

|August 10, 2019

Summary

This summary is machine-generated.

Cloud computing offers an efficient alternative for biomolecular simulations, simplifying complex tasks like modeling and analysis. Utilizing Google Cloud Platform with GROMACS and Docker containers enhances reproducibility and accessibility for researchers.

Keywords:

Cloud computing Distributed computing Large-scale simulation

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Area of Science:

Computational Biology
Biomolecular Simulations
Cloud Computing

Background:

Biomolecular simulations require significant computational resources, traditionally accessed via local infrastructure or supercomputing centers.
Cloud computing presents a scalable, on-demand alternative for computational tasks in scientific research.
Recent advancements facilitate easier cloud configuration for scientific workloads.

Purpose of the Study:

To demonstrate the use of Google Cloud Platform for biomolecular simulations.
To provide a practical guide for researchers to leverage cloud resources.
To highlight the benefits of cloud computing for scientific reproducibility and collaboration.

Main Methods:

Utilizing Google Cloud Platform for computational tasks.
Employing the GROningen MAchine for Chemical Simulations (GROMACS) package.
Leveraging Docker containers for virtualization and cloud storage for data management.

Main Results:

Successful configuration and execution of biomolecular simulations on Google Cloud.
Demonstration of simplified job submission and resource scaling.
Validation of Docker containers and cloud storage for reproducible research.

Conclusions:

Google Cloud Platform provides a viable and efficient environment for biomolecular simulations.
The use of Docker containers and cloud storage addresses key challenges in research reproducibility and data sharing.
The methods presented are transferable to a wide range of scientific computing tasks.