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Numerical simulation is much helpful to limit the costly and time consuming experiments.
However, when chemical systems are very complex, development of good models may lead to prohibitively expensive and time consuming experiments.
Application of modern simulation methods for the prediction of the engineering properties of polymeric materials may be a substitute for more time consuming experiments.
Quantitative Structure Activity Relationships (QSAR) models become a very useful tool in this context to substantially reduce time and resources consuming experiments.
Different computational approaches for ligand discovery have been developed helping to reduce late stage attrition and to limit the number of expensive and time consuming experiments required to synthesize the active novel hits with optimized pharmacodynamic and pharmacokinetic properties [47].
The detailed information provided by the use of computational fluid dynamic models has facilitated unique opportunities to investigate alternative system designs, without the need for expensive and time consuming experiments.
However, the optimization of their productivity by assessing the impact that several environmental factors have on microalgae growth still requires intense investigation, as well as numerous and time consuming experiments.
Several expensive and time consuming experiments were performed to introduce or suppress specific flavonoid genes in ornamental plants.
The evaluation of fatigue properties of metallic materials with conventional methods requires time and cost consuming experiments.
In many networks, whether a link exists or may exist in future is a matter of time and resource consuming experiments.
The limitation of the available initial number of cells, expensive substances and time consuming experiments are the main bottlenecks in this type of processes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com