Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design

This paper reviews past and ongoing efforts in using high-throughput ab-inito calculations in combination with machine learning models for materials design. The primary focus is on bulk materials, i.e., materials with fixed, ordered, crystal structures, although the methods naturally extend into more complicated configurations. Efficient and robust computational methods, computational power, and reliable methods for automated database-driven high-throughput computation are combined to produce high-quality data sets. This data can be used to train machine learning models for predicting the stability of bulk materials and their properties. The underlying computational methods and the tools for automated calculations are discussed in some detail. Various machine learning models and, in particular, descriptors for general use in materials design are also covered.Comment: 19 pages, 2 figure

Microfabrication of a biomimetic arcade-like electrospun scaffold for cartilage tissue engineering applications

Designing and fabricating hierarchical geometries for tissue engineering (TE) applications is the major challenge and also the biggest opportunity of regenerative medicine in recent years, being the in vitro recreation of the arcade-like cartilaginous tissue one of the most critical examples due to the current inefficient standard medical procedures and the lack of fabrication techniques capable of building scaffolds with the required architecture in a cost and time effective way. Taking this into account, we suggest a feasible and accurate methodology that uses a sequential adaptation of an electrospinning-electrospraying set up to construct a system comprising both fibres and sacrificial microparticles. Polycaprolactone (PCL) and polyethylene glycol were respectively used as bulk and sacrificial biomaterials, leading to a bi-layered PCL scaffold which presented not only a depth-dependent fibre orientation similar to natural cartilage, but also mechanical features and porosity compatible with cartilage TE approaches. In fact, cell viability studies confirmed the biocompatibility of the scaffold and its ability to guarantee suitable cell adhesion, proliferation and migration throughout the 3D anisotropic fibrous network. Additionally, likewise the natural anisotropic cartilage, the PCL scaffold was capable of inducing oriented cell-material interactions since the morphology, alignment and density of the chondrocytes changed relatively to the specific topographic cues of each electrospun layer.publishe

External beam radiotherapy in bone metastatic prostate cancer: impact on patients’ pain relief and quality of life.

Bone metastases are a severe problem in oncology, since they usually are associated with pain. External beam radiation therapy (EBRT) has been, for many years, an important component of the treatment regimen to relieve pain. We have performed a clinical study to evaluate the relationship of response to EBRT in terms of pain relief and improvement in quality of life (QoL). We were also interested in the incidence of acute toxicity with EBRT. We have prospectively evaluated 75 patients (median age 68 years, range 64-79 years) with bone metastases from prostate cancer treated with EBRT, radiographically documented from June 1999 to September 2000. Additional therapies in these patients included: second-line hormonal therapy (HT) in 20 patients, chemotherapy (CT) in 25 patients, biphosphonates in 45 patients. For all patients a pain and narcotic evaluation was done before entering the study. Assessment of response was carried out by evaluating pain relief. QoL was measured by using the EORTC QLQ-C30 questionnaire. Toxicity analysis was based on the ROTG grading system. Survival was calculated by Kaplan-Meier estimate from the start of EBRT treatment until the last follow-up or death. A total of 61 out of 75 patients (81%) experienced some type of pain relief after treatment. The complete response rate was 23%. No significant difference in the response rates was found between the group treated with EBRT alone versus the groups treated with EBRT + CT or EBRT + HT. We noted a significant improvement in some of the scales of the considered EORTC-QLQC30 questionnaire. As expected all treatment-related complications were either grade 1-2 acute or subacute and transitory in nature. The group treated with EBRT + CT experienced slightly higher toxicity rates. There were no treatment-related fatalities. Forteen patients of 61 (23%) responders was alive at 12 months. Our results confirm the ability of EBRT to relieve bony pain in the majority of the cancer patients treated as measured by prospective analysis of pain scales prior to and after EBRT. Minimal side effects were experienced and QoL improved as shown by the results of the specific questionnaire

Performance of genetic algorithms in search for water splitting perovskites

We examine the performance of genetic algorithms (GAs) in uncovering solar water light splitters over a space of almost 19,000 perovskite materials. The entire search space was previously calculated using density functional theory to determine solutions that fulfill constraints on stability, band gap, and band edge position. Here, we test over 2500 unique GA implementations in finding these solutions to determine whether GA can avoid the need for brute force search, and thereby enable larger chemical spaces to be screened within a given computational budget. We find that the best GAs tested offer almost a 6 times efficiency gain over random search, and are comparable to the performance of a search based on informed chemical rules. In addition, the GA is almost 10 times as efficient as random search in finding half the solutions within the search space. By employing chemical rules, the performance of the GA can be further improved to approximately 12–17 better than random search. We discuss the effect of population size, selection function, crossover function, mutation rate, fitness function, and elitism on the final result, finding that selection function and elitism are especially important to GA performance. In addition, we determine that parameters that perform well in finding solar water splitters can also be applied to discovering transparent photocorrosion shields. Our results indicate that coupling GAs to high-throughput density functional calculations presents a promising method to rapidly search large chemical spaces for technological materials