The geopolymer concept has gained wide international attention during the last two decades and is now seen as a potential alternative to ordinary Portland cement; however, before full implementation in the national and international standards, the geopolymer concept requires clarity on the commonly used definitions and mix design methodologies. The lack of a common definition and methodology has led to inconsistency and confusion across disciplines. This review aims to clarify the most existing geopolymer definitions and the diverse procedures on geopolymer methodologies to attain a good understanding of both the unary and binary geopolymer systems. This review puts into perspective the most crucial facets to facilitate the sustainable development and adoption of geopolymer design standards. A systematic review protocol was developed based on the Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and applied to the Scopus database to retrieve articles. Geopolymer is a product of a polycondensation reaction that yields a three-dimensional tecto-aluminosilicate matrix. Compared to unary geopolymer systems, binary geopolymer systems contain complex hydrated gel structures and polymerized networks that influence workability, strength, and durability. The optimum utilization of high calcium industrial by-products such as ground granulated blast furnace slag, Class-C fly ash, and phosphogypsum in unary or binary geopolymer systems give C-S-H or C-A-S-H gels with dense polymerized networks that enhance strength gains and setting times. As there is no geopolymer mix design standard, most geopolymer mix designs apply the trial-and-error approach, and a few apply the Taguchi approach, particle packing fraction method, and response surface methodology. The adopted mix designs require the optimization of certain mixture variables whilst keeping constant other nominal material factors. The production of NaOH gives less CO₂ emission compared to Na₂SiO_3, which requires higher calcination temperatures for Na₂CO₃ and SiO_2. However, their usage is considered unsustainable due to their caustic nature, high energy demand, and cost. Besides the blending of fly ash with other industrial by-products, phosphogypsum also has the potential for use as an ingredient in blended geopolymer systems. The parameters identified in this review can help foster the robust adoption of geopolymer as a potential “go-to” alternative to ordinary Portland cement for construction. Furthermore, the proposed future research areas will help address the various innovation gaps observed in current literature with a view of the environment and society.

Geopolymer is an inorganic material formed through the chemical reaction of an aluminosilicate precursor and an alkaline or acidic activating solution. It is seen as a green new alternative binder to ordinary Portland cement (OPC) for sustainable infrastructure development. The strength of the unary or blended geopolymer product is dependent on the composition and properties of the polymeric gel influenced by the ratios of Al₂O₃/SiO₂, CaO/SiO₂, CaO/(SiO₂ + Al₂O₃), Na₂SiO₃/NaOH, SiO₂/Na₂O, and liquid/binder (L/B). Essential scientific inquiry has been progressively addressed by utilizing expert assessment and research metrics. The network visualization of bibliometric co-occurrence and co-citations is of particular significance. The present study aims to highlight the trends and progress of the most influential publication sources, keywords, authors, articles, and countries in geopolymer research in the last 10 years. Bibliometric data were retrieved through Scopus and visualized in VOSviewer to create bibliometric networks. The yearly distribution and growth trends (April 2011–2022) of geopolymer, geopolymer mortar, and geopolymer concrete before (after) applying inclusion criteria were from 754 to 9887 (5186), 47 to 1374 (866), and 145 to 3721 (2253), respectively, attributed to the discoveries in more precursor materials such as laterite and the growing interest in fire and heat-resistant structures, water and wastewater treatment, cement and concrete, and brick manufacturing. The top three journals in terms of prestige for geopolymer publications were the Journal of Hazardous Materials with an impact factor equal to 14.224 and h-index equal to 307, Cement and Concrete Research with an impact factor equal to 11.958 and h-index equal to 239, and the Journal of Cleaner Production with an impact factor equal to 11.072 and h-index equal to 232. The top three journals in terms of average citation per document were Cement and Concrete Research (135.75), Materials and Design (75), and Cement and Concrete Composites (68.35). Keywords such as “geopolymers”, “inorganic polymer”, “geopolymer”, “compressive strength”, “fly ash”, and “geopolymer concrete” had the highest occurrences in publications. John Provis—University of Sheffield, Prinya Chindaprasirt—Khon Kaen University, and Jay Sanjayan—Swinburne University of Technology had the highest total citations of 6377, 5626, and 4311, respectively. The highest number of publications were from China, India, Australia, the United States of America, and Malaysia. The bibliometric findings from this study can act as a tool for academicians and policymakers to exchange research expertise, collaborate on novel geopolymer research, and create innovative joint ventures.

Despite drones being successfully utilized for monitoring and detecting hazards in mines, there is limited research on their application for open-pit stockpile volumetric computation compared to traditional methods. Furthermore, time, cost, and safety have challenged the use of the traditional approach. Present study aims to fill the gaps by conducting a comparative analysis of stockpile volumetric computation utilizing a drone and traditional approach. A mapping framework is proposed to guide mine personnel on how to conduct open-pit stockpile volumetric computations. The methodology comprises using a drone and traditional survey approach to measure the volume of a known quarry stockpile. Drone-captured images are processed in Pix4D mapper software and geometric techniques are applied to the traditional survey approach. Findings show that the smaller the error of the checkpoints the more accurate the generated model making the measurements reliable. The generated Pix4D quality report showed a root mean square error of 0.019. The drone percentage error to the actual volume is 2.6% while the traditional approach is 1.3%. Both estimations are less than the maximum allowable percentage error of ± 3%. Therefore, compared to the traditional approach drone technology provides an accurate, cost-effective, fast, and safe working distance suitable for stockpile volumetric computations in open pit quarries.

With increasing awareness of geotechnical risks in civil and mining structures, taking advantage of smartphone technology to study rocky slopes can play a key role in the development of safe and economical structures for human welfare. In Malawi, there is a research gap on application of portable devices to collect geotechnical data. Geological engineers still use the unsafe tedious handmapping technique to collect geotechnical data. A road cut that experiences frequent rockfall is used as a case study to investigate if there is a role for smartphones in geotechnics by comparing set statistics of data clusters collected through photogrammetry, smartphone and clar inclinometer. Besides low cost, smartphone’ data capture speed is faster than clar inclinometer. Stereographic and kinematic analysis shows that the 75° dipping road cut is predominantly prone to wedge failure with minor planar failure. For slope stability, Q-slope suggests a new slope angle of 60–66°. An acceptable tolerance limit or error between handmapping and remote data capture systems should be less than ±15°. Set analysis on 111 comparable data points gave a maximum pole vector difference of 10.5°, with the minimum having a difference of 4.8°. For dip, the standard deviations vary from 4.9 to 9.5°, while their mean values vary from −2 to 2.75°. For dip directions, the standard deviations vary from 3.2 to 4.3°, while their mean values vary from −6 to 0.75°. Therefore, android smartphones have a role in geotechnics due to their allowable orientation errors, which show less variance in measured dip/dip direction.

The nonlinearity and heterogeneity of geopolymer mix design have urged the research community to supplement the existing experimental design approach with machine learning and empirical regression models to improve the practical strength performance of geopolymers. This systematic review aims to elaborate and consolidate the fundamental machine learning algorithms and statistical models applied in the strength prediction of geopolymers. This review specifically delves into the statistical linear/nonlinear optimization algorithms, supervised machine learning algorithms, and model performance statistical metrics. The PRISMA and Scopus databases were used for bibliometric data extraction. The search strings devised to carry out the review were “geopolymer” OR “alkali-activated materials” AND “machine learning” OR “statistical modeling”. This review observed that neural networks, random forest, support vector machines, and Gaussian process regression give better strength prediction performances with R² values > 0.9 and RMSE values < 3. The choice of activation function influenced the training performance of the algorithm and defined the prediction output accuracy. Hyperparameter tuning and Shapley additive explanations showed that input features with a greater effect on compressive strength were curing conditions and silicate modulus. This review promotes the consolidation of conventional experimental mix design approaches with machine learning techniques in solving geopolymer mix design and strength-related problems to give greater confidence to engineers and researchers in the applicability and versatility of these models to real-life practical scenarios saving time and minimizing costs.