How can SpringerMaterials help your researchers?

Determining best conditions for manufacturing

An alloy manufacturer wishes to create a new alloy with 75% Ni and 24% Al (and the rest with other metals) and die-cast it into a part for an automobile company. A process engineer needs to know the best temperature to combine these 2 metals in order to save energy.

SCENARIO

Phase diagrams allow you to determine the most efficient conditions for manufacturing alloys.
In this case minimum temperature at which Ni and Al will combine to form an alloy is 1368 ᵒC.
At this temperature and composition of Ni and Al, the materials immediately solidifies into a solid without a long time to cool down so, if it needs to be cast into a die, it can be done around this temperature.

Know the properties of a given material

SCENARIO

A researcher at a company that makes solar cells wishes to use CuGaSe2 as material for a photovoltaic cell and wonders if it is a suitable candidate.

Band gap is an important property that determines if a material can be efficient solar cell.
Other optical and electronic properties like refractive index, absorption coefficient, dielectric constant, etc. can all be found in one location on SpringerMaterials

Predicting Properties of Materials Using Software Tools

SCENARIO

A researcher at a semiconductor company wishes to explore the properties of a new material by using experimental crystal structures of simple systems as basis to calculate properties of more complex systems

ZrNiSn intermetallic semiconductor is one of the most intensively studied thermoelectric materials due to the high efficiency of its conversion of thermal energy to electric energy.
The basic crystal structure of ZrNiSn can be imported into software programs and the effect of adding Ni atoms can be studied to find the most promising materials before proceeding to fabrication.

Experimental Data for Machine Learning

SCENARIO

A researcher at photovoltaics company is developing a machine learning tool to predict the most efficient perovskite material that can be used for a certain application. They need experimental data to train their computer models.

SpringerMaterials contains hundreds of perovskites materials and their physical properties which can be used for machine learning applications.
Many other classes of materials including alloys, ceramics, semiconductors, organic compounds can also be found on SpringerMaterials for similar applications