Additive manufacturing (AM), also known as 3D printing, is driving major innovation in many research and industrial areas. It is now commonly used to manufacture scientific research tools to increase reproducibility, lower costs, and improve accessibility [1
]. In general, the use of 3D printing to fabricate open hardware for scientific use reduces the cost by 92% compared to proprietary commercial tools [5
] and has thus been used in a wide variety of sciences. For example, in geoscience, a number of studies have employed 3D printing techniques to investigate its capabilities in rock mechanics to reproduce strength in common rock mechanics tests [6
] in replicating natural rock joint specimens to study rock surface properties [8
], or to study internal structures [9
]. These works have aimed to develop methods to produce 3D-printed rock samples. Additional studies have focused on the process of reproducing rock specimens by the translation of X-ray scanning images (X-ray tomography images) to computer-aided design (CAD)-based models that could then be 3D printed. Others have focused on the different material options to create artificial specimens such as powder and adhesive and binding agents. In a recent study [10
], a plant root system was modeled and 3D-printed using acrylonitrile butadiene styrene (ABS) plastic. The root was planted in a soil model and then mechanical tests were conducted to investigate the response of a vegetated slope to earthquake ground motion.
Unlike in geosciences, the use of AM in soil science is a relatively new research area. Only a few articles have dealt with the use of 3D printing techniques at the service of soil science. X-ray-computed tomography and 3D printing technology have been combined to produce physical structures with replicable, complex pore geometries reflecting those of soils [11
]. Another study combined X-ray micro CT with 3D multijet printing technology to evaluate the reproducibility of 3D-printed soil structures at the original scale with a resolution of 80 μm. Results showed that soil-like prototypes were similar to the original samples in terms of total porosity and pore shape [12
]. Moreover, a spatially explicit model was developed for nutrient uptake by root hairs based on X-ray-computed tomography images of the rhizosphere soil structure [13
]. The undisturbed soil column of Ultuna clay soil was 3D-printed in ABS material based on X-ray images and the potential and limitations of reproducing this were evaluated [14
]. These studies using ABS show that further research needs to be conducted to circumvent the problem of residual material blocking pores. Moreover, regardless of the 3D printing material, the fine pore matrix cannot be printed. Therefore, there is a need to develop a printing method to produce soil with connected macropores.
Most research studies are based on X-ray tomography images to generate a digital model of the soil and then fabricating it with 3D printing. Other articles, however, adopt another approach that proposes mathematical modeling of the soil structure. Ngom et al. [15
] propose the modeling of soil microstructures using generalized cylinders, with a specific application to pore space. As the pore space defines a complex volume shape that cannot be approximated using simple analytical functions, Ngom et al. propose representing this shape using an approximation by means of generalized cylinders. This modeling is, however, not oriented towards the fabrication of soil structures by 3D printing but aims at simulating biological dynamics. Buj-Corral et al. [16
] provide a methodology to design porous structures to be 3D printed. Their model is defined with some theoretical parallel planes, with each plane having randomly distributed points on it. Then, the points are joined with lines using the marching cubes algorithm. This approach is interesting, but since the generation of points is random, this modeling is not reproducible.
Soil science experiments have been greatly impacted by the technological advances that have been developed over the past decades. However, support for these experiments has evolved very slowly. Soil samples are still taken in the “traditional” way from specific fields. For this purpose, agricultural researchers determine in advance which areas would contain the most suitable soil for an experiment. This method leads to many approximations and uncontrolled parameters, which greatly complicates the analysis of the obtained results. Thus, for some studies, there is a need for identical replicates, and 3D printing offers a good opportunity to meet this need.
The modeling of a porous structure for soil science must consider a combination of specifications (nature of the material, porosity, location of a specific substance or living organisms) [17
]. Besides, the modeling process should be based on an engineering design approach, so that the soil model should be customizable and reproducible. The main characteristics of the model will be identified and studied according to the complexity of the phenomena in the soil and then a design approach will be achieved to define the 3D printing process.
To support this design approach, one main challenge is the development of software that allows soil scientists to create their soil models according to their needs in terms of the soil structure. This software should be dedicated to scientific research and should promote data sharing and exchange across an international community.
One principle of the research is to opt for an open-source system. Indeed, open-source makes the evolution of the modeling software easier [18
]. For years, open-source software and hardware have contributed to the modernization and improvement of agriculture. For example, open-source software such as the statistical software R [21
] is used for data analysis and GeoFIS as a decision-support tool for precision agriculture data [22
]. Open-source hardware examples are found on the notion of precision agriculture and SmartFarm by integrating open-source technologies such as smart sensors, recording devices, and drones [23
In this context, the objective of this paper is to present a developed open-source toolchain that allows soil scientists to generate customizable and reproducible digital soil models, called monoliths. This open-source script is developed under the IceSL environment [27
], which is an open-source slicer. The Section 2
introduces the need for 3D-printed monoliths for soil scientists and the script development approach. It also presents the main interface of the script and shows examples of monolith settings. Four different monoliths with various settings are generated and some examples are 3D-printed to show the ability of this script to fulfill the scientist’s needs. The Section 3
presents the analysis of the monolith digital models.
This study successfully utilized an open-source toolchain consisting of a Lua script in IceSL with a free GUI to enable researchers to create and configure digital soil models without resorting to meshing algorithms. The designed monoliths were fabricated with common and accessible 3D printers in the most used filament, PLA, with layer thicknesses of 0.20, 0.12, and 0.08 mm. The images generated from the digital model slicing were analyzed using open-source ImageJ software to obtain information about internal geometrical shape, porosity, tortuosity, grain size distribution, and hydraulic conductivities. The results showed that the developed open-source script enabled all researchers to design reproducible numerical models that imitated soil structures with defined pore and grain sizes with the following observations:
The tested model settings allowed the obtainment of materials similar to gravel and coarse sands.
The “Grain Number” parameter allows to vary the grain size but keeps it small. To obtain a material with a more widespread granulometry, it is possible to use mixes of several sizes.
The “Infill” parameter also modifies the grain size, at the risk of amplifying/counteracting the effect of the “Grain Number”. This parameter also significantly modifies the total porosity, even to the point of disconnecting the grains from each other, which is not “physical” and requires adjustments to “bridges” for 3D printing. Therefore, it is recommended to not use values that are too low. The pore sizes can be modified by the grain number (via “Grain Number”) but probably also when size mixes are used.
The morphological and physical properties seem globally consistent. However, when the grains are mostly disconnected from each other, “bridges” must be created for 3D printing in order to obtain a “stable” structure. This will likely generate significant impacts on the porosity and probably on the pore size distribution.
Samples that can be generated by the developed script would be expected to increase reproducibility as well as to be more accessible because of the open-source and low-cost methods involved.
This work can be expanded in the future by using a smaller nozzle for FFF printing and applying the technique to other forms of 3D printing with higher resolution as biocompatible materials for the fabrication of the monoliths.